From 6e5a0698b7165b02a1cf93e9aaf89d1b4091c4a1 Mon Sep 17 00:00:00 2001
From: npavlovikj <npavlovikj2@unl.edu>
Date: Thu, 15 Nov 2018 17:54:39 -0600
Subject: [PATCH] Add bio pages part 3

---
 .../de_novo_assembly_tools/_index.md          |   14 +-
 .../de_novo_assembly_tools/oases.md           |   60 +
 .../de_novo_assembly_tools/ray.md             |  303 +---
 .../de_novo_assembly_tools/soapdenovo2.md     |  367 ++---
 .../de_novo_assembly_tools/trinity/_index.md  |  287 +---
 .../running_trinity_in_multiple_steps.md      |  249 ++-
 .../de_novo_assembly_tools/velvet/_index.md   |  178 +--
 .../running_velvet_with_paired_end_data.md    | 1375 +----------------
 ...vet_with_single_end_and_paired_end_data.md |  162 +-
 .../running_velvet_with_single_end_data.md    |  158 +-
 static/html/oases.html                        |   68 +
 static/html/ray.html                          |   68 +
 static/html/soapdenovo2.html                  |   55 +
 static/html/trinity.html                      |   97 ++
 static/html/velvet.html                       |   77 +
 15 files changed, 920 insertions(+), 2598 deletions(-)
 create mode 100644 content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/oases.md
 create mode 100644 static/html/oases.html
 create mode 100644 static/html/ray.html
 create mode 100644 static/html/soapdenovo2.html
 create mode 100644 static/html/trinity.html
 create mode 100644 static/html/velvet.html

diff --git a/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/_index.md b/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/_index.md
index 9d7b5327..4400e3d0 100644
--- a/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/_index.md
+++ b/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/_index.md
@@ -1,13 +1,7 @@
-+++
+ +++
 title = "De Novo Assembly Tools"
+description = "How to use de novo assembly tools on HCC machines"
+weight = "52"
 +++
 
-<span id="title-text"> HCC-DOCS : De Novo Assembly Tools </span>
-================================================================
-
-Created by <span class="author"> Adam Caprez</span>, last modified by
-<span class="editor"> Natasha Pavlovikj</span> on Sep 04, 2014
-
- 
-
-
+{{% children %}}
\ No newline at end of file
diff --git a/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/oases.md b/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/oases.md
new file mode 100644
index 00000000..676ecec7
--- /dev/null
+++ b/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/oases.md
@@ -0,0 +1,60 @@
++++
+title = "Oases"
+description =  "How to run Oases on HCC resources"
+weight = "10"
++++
+
+
+Velvet by itself generates assembled contigs for DNA data. However, using the Oases extension for Velvet, a transcriptome assembly can be produced. [Oases] (https://www.ebi.ac.uk/~zerbino/oases/) is an extension of Velvet for generating de novo assembly for RNA-Seq data. Oases uses the preliminary assembly produced by Velvet as an input, and constructs transcripts.
+
+In order to be able to run Oases, after `velveth`, `velvetg` needs to be run with the `–read_trkg yes` option:
+{{< highlight bash >}}
+$ velvetg output_directory/ -min_contig_lgth 200 -read_trkg yes
+{{< /highlight >}}
+
+The `output_directory/` after `velvetg` with `-read_trkg` option on contains the following files:
+{{% panel header="`Output directory after Velvetg`"%}}
+{{< highlight bash >}}
+$ ls
+contigs.fa  Graph2  LastGraph  Log  PreGraph  Roadmaps  Sequences  stats.txt
+{{< /highlight >}}
+{{% /panel %}}
+
+Oases has a lot of parameters that can be found in its [manual] (https://www.ebi.ac.uk/~zerbino/oases/OasesManual.pdf). While Velvet is multi-threaded, Oases is not.
+
+\\
+A simple SLURM script to run Oases on the Velvet output stored in `output_directory/` with minimum transcript length of `200` is shown below:
+{{% panel header="`oases.submit`"%}}
+{{< highlight bash >}}
+#!/bin/sh
+#SBATCH --job-name=Velvet_Oases
+#SBATCH --nodes=1
+#SBATCH --ntasks-per-node=1
+#SBATCH --time=168:00:00
+#SBATCH --mem=10gb
+#SBATCH --output=Oases.%J.out
+#SBATCH --error=Oases.%J.err
+
+module load oases/0.2.8
+
+oases output_directory/ -min_trans_lgth 200
+{{< /highlight >}}
+{{% /panel %}}
+
+\\
+<span style="color: rgb(0,0,0);font-size: 20.0px;line-height: 1.5;">Oases Output</span>
+
+The `output_directory/` after Oases contains the following files:
+{{% panel header="`Output directory after Oases`"%}}
+{{< highlight bash >}}
+$ ls output_directory/
+contig-ordering.txt  contigs.fa  Graph2  LastGraph  Log  PreGraph  Roadmaps  Sequences  stats.txt  transcripts.fa
+{{< /highlight >}}
+{{% /panel %}}
+Oases produces two additional output files: `transcripts.fa` and `contig-ordering.txt`. The predicted transcript sequences are found in the fasta file `transcripts.fa`.
+
+\\
+<span style="color: rgb(0,0,0);font-size: 20.0px;line-height: 1.5;">Useful Information</span>
+
+In order to test the Oases (oases/0.2.8) performance on Tusker, we used three paired-end input fastq files, `small_1.fastq` and `small_2.fastq`, `medium_1.fastq` and `medium_2.fastq`, and `large_1.fastq` and `large_2.fastq`. Some statistics about the input files and the time and memory resources used by Oases on Tusker are shown in the table below:
+{{< readfile file="/static/html/oases.html" >}}
\ No newline at end of file
diff --git a/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/ray.md b/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/ray.md
index 9acd6ab8..15c80973 100644
--- a/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/ray.md
+++ b/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/ray.md
@@ -1,240 +1,77 @@
-1.  [HCC-DOCS](index.html)
-2.  [HCC-DOCS Home](HCC-DOCS-Home_327685.html)
-3.  [HCC Documentation](HCC-Documentation_332651.html)
-4.  [Running Applications](Running-Applications_7471153.html)
-5.  [Bioinformatics Tools](Bioinformatics-Tools_8193279.html)
-6.  [De Novo Assembly Tools](De-Novo-Assembly-Tools_8193280.html)
-
-<span id="title-text"> HCC-DOCS : Ray </span>
-=============================================
-
-Created by <span class="author"> Adam Caprez</span>, last modified by
-<span class="editor"> Natasha Pavlovikj</span> on Dec 12, 2016
-
-| Name | Version | Resource |
-|------|---------|----------|
-| ray  | 2.3     | Tusker   |
-
-|     |     |       |
-|-----|-----|-------|
-| ray | 2.3 | Crane |
-
++++
+title = "Ray"
+description =  "How to run Ray on HCC resources"
+weight = "10"
++++
  
 
-Ray
-(<a href="http://denovoassembler.sourceforge.net/" class="external-link">http://denovoassembler.sourceforge.net/</a>)
-is a de novo de Bruijn genome assembler that works with next-generation
-sequencing data (Illumina, 454, SOLiD). Ray is scalable and parallel
-software that takes advantage of multiple nodes and multiple CPUs using
-MPI (message passing interface).
+[Ray] (http://denovoassembler.sourceforge.net/) is a de novo de Bruijn genome assembler that works with next-generation sequencing data (Illumina, 454, SOLiD). Ray is scalable and parallel software that takes advantage of multiple nodes and multiple CPUs using MPI (message passing interface).
 
 Ray can be used for building multiple applications:
 
--   <span style="line-height: 1.4285715;">de novo genome assembly</span>
--   de novo meta-genome assembly
-
--   de novo transcriptome assembly
--   quantification of contig abundances, microbiome consortia members,
-    transcript expression
--   taxonomy and gene ontology profiling of samples
--   comparing DNA samples using words  
-      
+- de novo genome assembly
+- de novo meta-genome assembly
+- de novo transcriptome assembly
+- quantification of contig abundances, microbiome consortia members, transcript expression
+- taxonomy and gene ontology profiling of samples
+- comparing DNA samples using words
 
 In order to see all options available for running Ray, just type:
-
-**Ray Options**
-
-``` syntaxhighlighter-pre
-[<username>@login.tusker ~]$ mpiexec Ray -help
-```
-
-All options used for Ray can be defined in the command line:
-
-**General Ray Usage**
-
-``` syntaxhighlighter-pre
-[<username>@login.tusker ~]$ mpiexec Ray -k <kmer_value> -p input_reads_pair_1.[fa|fq] input_reads_pair_2.[fa|fq] -s input_reads.[fa|fq] -o <output_directory>
-```
-
-or can be stored in a configuration file *.conf* (one option per line):
-
-**General Ray Usage with Configuration File**
-
-``` syntaxhighlighter-pre
-[<username>@login.tusker ~]$ mpiexec Ray Ray.conf
-```
-
-Ray supports both paired-end (*-p*) and single-end reads (*-s*).
-Moreover, Ray can detect the input files automatically if the input
-directory is provided (*-detect-sequence-files input\_directory*). Ray
-supports odd values for k-mer larger or equal to 21 (*-k
-&lt;kmer\_value&gt;*). Ray supports multiple file formats: **fasta**,
-**fa**, **fasta.gz**, **fa.gz**, **fasta.bz2**, **fa.bz2**, **fastq**,
-**fq**, **fastq.gz**, **fq.gz**, **fastq.bz2**, **fq.bz2**, **sff**,
-**csfasta**, **csfa**.  
- 
-
-Simple SLURM script for running Ray on Tusker with both paired-end and
-single-end data with **k-mer=31**, **8 CPUs** and **4 GB RAM per
-CPU** is shown below:
-
-**ray.submit**
-
-\#!/bin/sh  
-\#SBATCH --job-name=Ray  
-\#SBATCH --ntasks=8  
-\#SBATCH --time=168:00:00  
-\#SBATCH --mem-per-cpu=4gb  
-\#SBATCH --output=Ray.%J.out  
-\#SBATCH --error=Ray.%J.err
-
- 
-
-|                                                  |
-|--------------------------------------------------|
-| module load compiler/gcc/4.7 openmpi/1.6 ray/2.3 |
-
-mpiexec Ray -k 31 -p input\_reads\_pair\_1.fastq
-input\_reads\_pair\_2.fastq -s input\_reads.fasta -o output\_directory
-
-where **input\_reads\_pair\_1.fastq**
-and **input\_reads\_pair\_2.fastq** are the paired-end input files in
-**fastq** format, while **input\_reads.fasta** is the single-end input
-file in **fasta** format.
-
-<span
-class="aui-icon aui-icon-small aui-iconfont-warning confluence-information-macro-icon"></span>
-
- It is **not** necessary to specify the number of processes with
-the `-n `option to `mpiexec`.  OpenMPI will determine that automatically
-from SLURM based on the value of the `--ntasks `option.
-
- 
-
-**Ray Output**
-
-In the output folder (*-o **output\_directory*) Ray prints a lot of
-files with information about different steps and statistics from the
-execution process. Information about all output files can be found in
-Ray's manual. One of the most important results are:
-
--   <span
-    style="line-height: 1.4285715;">**Scaffolds.fasta**: </span>scaffold
-    sequences in FASTA format
--   <span style="line-height: 1.4285715;">**ScaffoldComponents.txt**:
-    components of each scaffold</span>
--   <span style="line-height: 1.4285715;">**Contigs.fasta**: contiguous
-    sequences in FASTA format </span>
--   <span style="line-height: 1.4285715;">**OutputNumbers.txt**: overall
-    numbers for the assembly</span>
-
-  
-
-**Useful Information**
-
-In order to test the Ray performance on Tusker, we used three paired-end
-input fastq
-files: **small\_1.fastq**, **small\_2.fastq**, **medium\_1.fastq**, **medium\_2.fastq**, **large\_1.fastq**, **large\_2.fastq**.
-Some statistics about the input files and the time and memory resources
-required for Ray are shown on the table below:
-
- 
-
-**total \# of sequences**
-
-**total \# of bases**
-
-**total size in MB**
-
-**RAY required time**
-
-**RAY required memory**
-
-\# of used CPUs
-
-**small\_1.fastq**
-
-50,121
-
-2,506,050
-
-8.010 MB
-
-\~ 3 minutes
-
-\~ 1 GB
-
-8
-
-**small\_2.fastq**
-
-50,121
-
-2,506,050
-
-8.010 MB
-
-**medium\_1.fastq**
-
-786,742
-
-59,792,392
-
-152 MB
-
-\~ 15 minutes
-
-\~ 1.5 GB
-
-8
-
-**medium\_2.fastq**
-
-786,742
-
-59,792,392
-
-152 MB
-
-**large\_1.fastq**
-
-10,174,715
-
-1,027,646,215
-
-3,376 MB
-
-\~ 5 hours
-
-\~ 17 GB
-
-8
-
-**large\_2.fastq**
-
-10,174,715
-
-1,027,646,215
-
-3,376 MB
-
-Attachments:
-------------
-
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[tusker\_ray\_version.xsl](attachments/9470322/9863497.xsl)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[crane\_ray\_version.xsl](attachments/9470322/9863498.xsl)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[cb\_ray\_module.xsl](attachments/9470322/9863499.xsl)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[crane\_modules.xml](attachments/9470322/9863500.xml)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[tusker\_modules.xml](attachments/9470322/9863501.xml)
-(application/octet-stream)  
-
-
+{{< highlight bash >}}
+$ mpiexec Ray -help
+{{< /highlight >}}
+
+All options used for Ray can be defined on the command line:
+{{< highlight bash >}}
+$ mpiexec Ray -k <kmer_value> -p input_reads_pair_1.[fa|fq] input_reads_pair_2.[fa|fq] -s input_reads.[fa|fq] -o <output_directory>
+{{< /highlight >}}
+or can be stored in a configuration file `.conf` (one option per line):
+{{< highlight bash >}}
+$ mpiexec Ray Ray.conf
+{{< /highlight >}}
+
+\\
+Ray supports both paired-end (`-p`) and single-end reads (`-s`). Moreover, Ray can detect the input files automatically if the input directory is provided (`-detect-sequence-files input_directory`).
+
+Ray supports odd values for k-mer equal to or greater than 21 (`-k <kmer_value>`). Ray supports multiple file formats such as `fasta`, `fa`, `fasta.gz`, `fa.gz, `fasta.bz2`, `fa.bz2`, `fastq`, `fq`, `fastq.gz`, `fq.gz`, `fastq.bz2`, `fq.bz2`, `sff`, `csfasta`, `csfa`.
+
+\\
+Simple SLURM script for running Ray on Tusker with both paired-end and single-end data with `k-mer=31`, `8 CPUs` and `4 GB RAM per CPU` is shown below:
+{{% panel header="`ray.submit`"%}}
+{{< highlight bash >}}
+#!/bin/sh
+#SBATCH --job-name=Ray
+#SBATCH --ntasks=8
+#SBATCH --time=168:00:00
+#SBATCH --mem-per-cpu=4gb
+#SBATCH --output=Ray.%J.out
+#SBATCH --error=Ray.%J.err
+
+module load compiler/gcc/4.7 openmpi/1.6 ray/2.3
+
+mpiexec Ray -k 31 -p input_reads_pair_1.fastq input_reads_pair_2.fastq -s input_reads.fasta -o output_directory
+{{< /highlight >}}
+{{% /panel %}}
+where **input_reads_pair_1.fastq** and **input_reads_pair_2.fastq** are the paired-end input files in `fastq` format, and **input_reads.fasta** is the single-end input file in `fasta` format.
+
+{{% notice tip %}}
+It is **not** necessary to specify the number of processes with the `-n` option to `mpiexec`. OpenMPI will determine that automatically from SLURM based on the value of the `--ntasks` option.
+{{% /notice %}}
+
+\\
+<span style="color: rgb(0,0,0);font-size: 20.0px;line-height: 1.5;">Ray Output</span>
+
+In the output folder (`-o output_directory`) Ray prints a lot of files with information about different steps and statistics from the execution process. Information about all output files can be found in Ray's manual.
+
+One of the most important results are:
+
+- **Scaffolds.fasta**: scaffold sequences in FASTA format
+- **ScaffoldComponents.txt**: components of each scaffold
+- **Contigs.fasta**: contiguous sequences in FASTA format
+- **OutputNumbers.txt**: overall numbers for the assembly
+
+\\
+<span style="color: rgb(0,0,0);font-size: 20.0px;line-height: 1.5;">Useful Information</span>
+
+In order to test the Ray performance on Tusker, we used three paired-end input fastq files, `small_1.fastq` and `small_2.fastq`, `medium_1.fastq` and `medium_2.fastq`, and `large_1.fastq` and `large_2.fastq`. Some statistics about the input files and the time and memory resources used by Ray on Tusker are shown in the table below:
+{{< readfile file="/static/html/ray.html" >}}
\ No newline at end of file
diff --git a/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/soapdenovo2.md b/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/soapdenovo2.md
index d6e46921..7e285d1f 100644
--- a/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/soapdenovo2.md
+++ b/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/soapdenovo2.md
@@ -1,289 +1,130 @@
-1.  [HCC-DOCS](index.html)
-2.  [HCC-DOCS Home](HCC-DOCS-Home_327685.html)
-3.  [HCC Documentation](HCC-Documentation_332651.html)
-4.  [Running Applications](Running-Applications_7471153.html)
-5.  [Bioinformatics Tools](Bioinformatics-Tools_8193279.html)
-6.  [De Novo Assembly Tools](De-Novo-Assembly-Tools_8193280.html)
++++
+title = "SOAPdenovo2"
+description =  "How to run SOAPdenovo2 on HCC resources"
+weight = "10"
++++
 
-<span id="title-text"> HCC-DOCS : SOAPdenovo2 </span>
-=====================================================
 
-Created by <span class="author"> Adam Caprez</span>, last modified by
-<span class="editor"> Natasha Pavlovikj</span> on Dec 12, 2016
+[SOAPdenovo] (http://soap.genomics.org.cn/soapdenovo.html) is a de novo genome assembler for short reads. It is specially designed for Illumina GA short reads and large plant and animal genomes. SOAPdenovo2 is a newer version of SOAPdenovo with improved algorithm that reduces memory consumption, resolves more repeat regions, increases coverage, and optimizes the assembly for large genomes.
 
-| Name        | Version | Resource |
-|-------------|---------|----------|
-| soapdenovo2 | r240    | Tusker   |
-
-|             |      |       |
-|-------------|------|-------|
-| soapdenovo2 | r240 | Crane |
-
- 
-
-SOAPdenovo
-(<a href="http://soap.genomics.org.cn/soapdenovo.html" class="external-link">http://soap.genomics.org.cn/soapdenovo.html</a>) is
-a de novo genome assembler for short reads. It is specially designed for
-Illumina GA short reads and large plant and animal genomes. SOAPdenovo2
-is a newer version of SOAPdenovo with improved algorithm that reduces
-memory consumption, resolves more repeat regions, increases coverage,
-and optimizes the assembly for large genomes.
-
-SOAPdenovo2 has two commands, **SOAPdenovo-63mer** and
-**SOAPdenovo-127mer**. The first one is suitable for assembly with k-mer
-values less than 63 bp, requires less memory and runs faster. The latter
-one works for k-mer values less than 127 bp.
+SOAPdenovo2 has two commands, **SOAPdenovo-63mer** and **SOAPdenovo-127mer**. The first one is suitable for assembly with k-mer values less than 63 bp, requires less memory and runs faster. The latter one works for k-mer values less than 127 bp.
 
 In order to see the options available for **SOAPdenovo-63mer** just
 type:
+{{< highlight bash >}}
+$ SOAPdenovo-63mer
+{{< /highlight >}}
 
-**SOAPdenovo-63mer Options**
-
-``` syntaxhighlighter-pre
-[<username>@login.tusker ~]$ SOAPdenovo-63mer
-```
+SOAPdenovo2 provides a mechanism to run the whole workflow at once, or in 5 separate steps.
 
-SOAPdenovo2 provides a mechanism to run the whole workflow at once, or
-in 5 separate steps.  
 The basic usage of SOAPdenovo2 is:
+{{< highlight bash >}}
+$ SOAPdenovo-63mer all -s configFile -o output_directory/outputGraph -K <kmer_value> [options]
+{{< /highlight >}}
+where **configFile** is a defined configuration file, **outputGraph** is the prefix of the output files, and **kmer_value** is the value of k-mer used for building the assembly (`<=63` for SOAPdenovo-63mer and `<=127` for SOAPdenovo-127mer).
 
-**General SOAPdenovo-63mer Usage**
-
-``` syntaxhighlighter-pre
-[<username>@login.tusker ~]$ SOAPdenovo-63mer all -s configFile -o output_directory/outputGraph -K <kmer_value> [options]
-```
-
-where **configFile** is a defined configuration file, **outputGraph** is
-the prefix of the output files, and **kmer\_value** is the value of
-k-mer used for building the assembly (&lt;=63 for SOAPdenovo-63mer and
-&lt;=127 for SOAPdenovo-127mer).
-
-If you want to run the assembly process step by step, then use the
-following sequential commands:
-
-**Step 1:**
+\\
+If you want to run the assembly process step by step, then use the following sequential commands:
 
-**SOAPdenovo2 Step 1 Options**
-
-``` syntaxhighlighter-pre
+{{% panel theme="info" header="SOAPdenovo2 Step 1 Options" %}}
+{{< highlight bash >}}
 SOAPdenovo-63mer pregraph -s configFile -o outputGraph [options]
 OR
 SOAPdenovo-63mer sparse_pregraph -s configFile -K <kmer_value> -z <genome_size> -o outputGraph [options]
-```
-
-**Step 2: **
+{{< /highlight >}}
+{{% /panel %}}
 
-**SOAPdenovo2 Step 2 Options**
-
-``` syntaxhighlighter-pre
+{{% panel theme="info" header="SOAPdenovo2 Step 2 Options" %}}
+{{< highlight bash >}}
 SOAPdenovo-63mer contig -g inputGraph [options]
-```
-
-**Step 3:**
+{{< /highlight >}}
+{{% /panel %}}
 
-**SOAPdenovo2 Step 3 Options**
-
-``` syntaxhighlighter-pre
+{{% panel theme="info" header="SOAPdenovo2 Step 3 Options" %}}
+{{< highlight bash >}}
 SOAPdenovo-63mer map -s configFile -g inputGraph [options]
-```
-
-**Step 4:**
+{{< /highlight >}}
+{{% /panel %}}
 
-**SOAPdenovo2 Step 4 Options**
-
-``` syntaxhighlighter-pre
+{{% panel theme="info" header="SOAPdenovo2 Step 4 Options" %}}
+{{< highlight bash >}}
 SOAPdenovo-63mer scaff -g inputGraph [options]
-```
-
-As you can notice from the commands above, in order to run SOAPdenovo2,
-you first need to create a config file (**configFile**) that contains
-different information about the read files (*read length*, *insert
-size*, *reads location*). SOAPdenovo2 accepts read files in 3 formats:
-fasta, fastq and bam.
-
-The example configuration file **configFile** for 2 paired-end fastq
-files, 1 paired-end fasta file and 1 single-end fastq file looks like
-this:
-
-**configFile**
-
-<span style="color: rgb(0,0,0);">\#maximal read length</span>  
-<span style="color: rgb(0,0,0);">max\_rd\_len=150</span>  
-<span style="color: rgb(0,0,0);">\[LIB\]</span>  
-<span style="color: rgb(0,0,0);">\#average insert size of the
-library</span>  
-<span style="color: rgb(0,0,0);">avg\_ins=300</span>  
-<span style="color: rgb(0,0,0);">\#if sequences are forward-reverse of
-reverse-forward</span>  
-<span style="color: rgb(0,0,0);">reverse\_seq=0</span>  
-<span style="color: rgb(0,0,0);">\#in which part(s) the reads are used
-(only contigs, only scaffolds, both contigs and scaffolds, only gap
-closure)</span>  
-<span style="color: rgb(0,0,0);">asm\_flags=3</span>  
-<span style="color: rgb(0,0,0);">\#cut the reads to the given
-length</span>  
-<span style="color: rgb(0,0,0);">rd\_len\_cutoff=100</span>  
-<span style="color: rgb(0,0,0);">\#in which order the reads are used
-while scaffolding</span>  
-<span style="color: rgb(0,0,0);">rank=1</span>  
-<span style="color: rgb(0,0,0);">\# cutoff of pair number for a reliable
-connection (at least 3 for short insert size)</span>  
-<span style="color: rgb(0,0,0);">pair\_num\_cutoff=3</span>  
-<span style="color: rgb(0,0,0);">\#minimum aligned length to contigs for
-a reliable read location (at least 32 for short insert size)</span>  
-<span style="color: rgb(0,0,0);">map\_len=32</span>  
-<span style="color: rgb(0,0,0);">\#paired-end fastq files, read 1 file
-should always be followed by read 2 file</span>  
-<span style="color: rgb(0,0,0);">q1=input\_reads1\_pair\_1.fq</span>  
-<span style="color: rgb(0,0,0);">q2=input\_reads1\_pair\_2.fq</span>  
-<span style="color: rgb(0,0,0);">\#another pair of paired-end fastq
-files, read 1 file should always be followed by read 2 file</span>  
-<span style="color: rgb(0,0,0);">q1=input\_reads2\_pair\_1.fq</span>  
-<span style="color: rgb(0,0,0);">q2=input\_reads2\_pair\_2.fq</span>  
-<span style="color: rgb(0,0,0);">\#paired-end fasta files, read 1 file
-should always be followed by read 2 file</span>  
-<span style="color: rgb(0,0,0);">f1=input\_reads\_pair\_1.fa</span>  
-<span style="color: rgb(0,0,0);">f2=input\_reads\_pair\_2.fa</span>  
-<span style="color: rgb(0,0,0);">\#fastq file for single reads</span>  
-<span style="color: rgb(0,0,0);">q=input\_reads.fq</span>
-
-After creating the configuration file **configFile**, the next step is
-to run the assembler using this file.  
-Simple SLURM script for running SOAPdenovo2 with **k-mer=31**, **8
-CPUSs** and **50GB of RAM** on Tusker is shown below:
-
-**soapdenovo2.submit**
-
-\#!/bin/sh  
-\#SBATCH --job-name=SOAPdenovo2  
-\#SBATCH --nodes=1  
-\#SBATCH --ntasks-per-node=8  
-\#SBATCH --time=168:00:00  
-\#SBATCH --mem=50gb  
-\#SBATCH --output=SOAPdenovo2.%J.out  
-\#SBATCH --error=SOAPdenovo2.%J.err  
-  
-
-|                              |
-|------------------------------|
-| module load soapdenovo2/r240 |
-
-SOAPdenovo-63mer all -s configFile -K 31 -o output\_directory/output31
--p $SLURM\_NTASKS\_PER\_NODE
-
- 
-
-**SOAPdenovo2 Output**
-
-SOAPdenovo2 outputs number of files in its *output\_directory/* after
-each executed step. The final assembly output is in the **.contig**
-file.
-
-**Output Directory After SOAPdenovo2**
-
-``` syntaxhighlighter-pre
-[<username>@login.tusker output_directory]$ ls
+{{< /highlight >}}
+{{% /panel %}}
+
+As you can notice from the commands above, in order to run SOAPdenovo2, you first need to create a config file (`configFile`) that contains different information about the read files (`read length`, `insert size`, `reads location`). SOAPdenovo2 accepts read files in 3 formats: fasta, fastq and bam.
+
+The example configuration file **configFile** for 2 paired-end fastq files, 1 paired-end fasta file and 1 single-end fastq file looks like:
+{{% panel header="`configFile`"%}}
+{{< highlight bash >}}
+#maximal read length
+max_rd_len=150
+[LIB]
+#average insert size of the library
+avg_ins=300
+#if sequences are forward-reverse of reverse-forward
+reverse_seq=0
+#in which part(s) the reads are used (only contigs, only scaffolds, both contigs and scaffolds, only gap closure)
+asm_flags=3
+#cut the reads to the given length
+rd_len_cutoff=100
+#in which order the reads are used while scaffolding
+rank=1
+# cutoff of pair number for a reliable connection (at least 3 for short insert size)
+pair_num_cutoff=3
+#minimum aligned length to contigs for a reliable read location (at least 32 for short insert size)
+map_len=32
+#paired-end fastq files, read 1 file should always be followed by read 2 file
+q1=input_reads1_pair_1.fq
+q2=input_reads1_pair_2.fq
+#another pair of paired-end fastq files, read 1 file should always be followed by read 2 file
+q1=input_reads2_pair_1.fq
+q2=input_reads2_pair_2.fq
+#paired-end fasta files, read 1 file should always be followed by read 2 file
+f1=input_reads_pair_1.fa
+f2=input_reads_pair_2.fa
+#fastq file for single reads
+q=input_reads.fq
+{{< /highlight >}}
+{{% /panel %}}
+
+After creating the configuration file **configFile**, the next step is to run the assembler using this file.
+
+Simple SLURM script for running SOAPdenovo2 with `k-mer=31`, `8 CPUSs` and `50GB of RAM` on Tusker is shown below:
+{{% panel header="`soapdenovo2.submit`"%}}
+{{< highlight bash >}}
+#!/bin/sh
+#SBATCH --job-name=SOAPdenovo2
+#SBATCH --nodes=1
+#SBATCH --ntasks-per-node=8
+#SBATCH --time=168:00:00
+#SBATCH --mem=50gb
+#SBATCH --output=SOAPdenovo2.%J.out
+#SBATCH --error=SOAPdenovo2.%J.err
+
+module load soapdenovo2/r240
+
+SOAPdenovo-63mer all -s configFile -K 31 -o output_directory/output31 -p $SLURM_NTASKS_PER_NODE
+{{< /highlight >}}
+{{% /panel %}}
+
+\\
+<span style="color: rgb(0,0,0);font-size: 20.0px;line-height: 1.5;">SOAPdenovo2 Output</span>
+
+SOAPdenovo2 outputs number of files in its `output_directory/` after each executed step. The final assembly output is in the `.contig` file.
+{{% panel header="`Output directory after SOAPdenovo2`"%}}
+{{< highlight bash >}}
+$ ls
 output31.Arc            output31.ContigIndex       output31.gapSeq    output31.newContigInde
 output31.bubbleInScaff  output31.contigPosInscaff  output31.kmerFreq  output31.peGrads
 output31.contig         output31.edge.gz           output31.links     output31.preArc
-```
-
-**  
-**
-
-**Useful Information**
-
-In order to test the SOAPdenovo2 (soapdenovo2/r240) performance on
-Tusker, we used three different size input files. Some statistics about
-these input files and the time and memory resources required for
-SOAPdenovo2 are shown on the table below:
-
- 
-
-**total \# of sequences**
-
-**total \# of bases**
-
-**total size in GB**
-
-SOAPdenovo2 required memory
-
-SOAPdenovo2 required time
-
-K-mer value
-
-\# of used CPUs
-
-**Input Data 1**
-
-49,720,374
-
-7,295,342,636
-
-10 GB
-
-\~ 32 GB
-
-\~ 1.5 hours
-
-31
-
-8
-
-**Input Data 2**
-
-166,040,440
-
-25,072,106,440
-
-62 GB
-
-\~ 125 GB
-
-\~ 6.5 hours
-
-31
-
-8
-
-**Input Data 3**
-
-318,681,730
-
-48,120,941,230
-
-115 GB
-
-\~ 125 GB
-
-\~ 13 hours
-
-31
-
-8
-
-In general, SOAPdenovo2 is a memory intensive assembler that requires
-approximately 30\~60 GB memory for assembling 50 million reads.
-Moreover, SOAPdenovo2 is a fast assembler and it takes around an hour to
-assemble 50 million reads.
-
-Attachments:
-------------
+{{< /highlight >}}
+{{% /panel %}}
 
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[tusker\_soapdenovo2\_version.xsl](attachments/9470140/9863306.xsl)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[crane\_soapdenovo2\_version.xsl](attachments/9470140/9863307.xsl)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[cb\_soapdenovo2\_module.xsl](attachments/9470140/9863308.xsl)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[tusker\_modules.xml](attachments/9470140/9863309.xml)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[crane\_modules.xml](attachments/9470140/9863310.xml)
-(application/octet-stream)  
+\\
+<span style="color: rgb(0,0,0);font-size: 20.0px;line-height: 1.5;">Useful Information</span>
 
+In order to test the SOAPdenovo2 (soapdenovo2/r240) performance on Tusker, we used three different size input files. Some statistics about the input files and the time and memory resources used by SOAPdenovo2 are shown in the table below:
+{{< readfile file="/static/html/soapdenovo2.html" >}}
 
+In general, SOAPdenovo2 is a memory intensive assembler that requires approximately 30-60 GB memory for assembling 50 million reads. However, SOAPdenovo2 is a fast assembler and it takes around an hour to assemble 50 million reads.
\ No newline at end of file
diff --git a/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/trinity/_index.md b/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/trinity/_index.md
index 1219ab95..9d4cb8fb 100644
--- a/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/trinity/_index.md
+++ b/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/trinity/_index.md
@@ -1,265 +1,58 @@
-1.  [HCC-DOCS](index.html)
-2.  [HCC-DOCS Home](HCC-DOCS-Home_327685.html)
-3.  [HCC Documentation](HCC-Documentation_332651.html)
-4.  [Running Applications](Running-Applications_7471153.html)
-5.  [Bioinformatics Tools](Bioinformatics-Tools_8193279.html)
-6.  [De Novo Assembly Tools](De-Novo-Assembly-Tools_8193280.html)
-
-<span id="title-text"> HCC-DOCS : Trinity </span>
-=================================================
-
-Created by <span class="author"> Adam Caprez</span>, last modified by
-<span class="editor"> Natasha Pavlovikj</span> on Feb 26, 2018
-
-| Name    | Version       | Resource |
-|---------|---------------|----------|
-| trinity | r2013-02-25   | Tusker   |
-| trinity | r2013-11-10   | Tusker   |
-| trinity | r2014-04-13p1 | Tusker   |
-
-|         |               |       |
-|---------|---------------|-------|
-| trinity | r2013-11-10   | Crane |
-| trinity | r2014-04-13p1 | Crane |
-
++++
+title = "Trinity"
+description = "How to use Trinity on HCC machines"
+weight = "52"
++++
  
 
-Trinity
-(<a href="http://trinityrnaseq.sourceforge.net/" class="external-link">http://trinityrnaseq.sourceforge.net/</a>)
-is a method for efficient and robust de novo reconstruction of
-transcriptomes from RNA-Seq data. Trinity combines three independent
-software modules: Inchworm, Chrysalis, and Butterfly. All these modules
-can be applied sequentially to process large RNA-Seq datasets. 
+[Trinity] (https://github.com/trinityrnaseq/trinityrnaseq/wiki) is a method for efficient and robust de novo reconstruction of transcriptomes from RNA-Seq data. Trinity combines three independent software modules: `Inchworm`, `Chrysalis`, and `Butterfly`. All these modules can be applied sequentially to process large RNA-Seq datasets.
 
 The basic usage of Trinity is:
+{{< highlight bash >}}
+$ Trinity --seqType [fa|fq] --JM <jellyfish_memory> --left input_reads_pair_1.[fa|fq] --right input_reads_pair_2.[fa|fq] [options]
+{{< /highlight >}}
+where **input_reads_pair_1.[fa|fq]** and **input_reads_pair_2.[fa|fq]** are the input paired-end files of sequence reads in fasta/fastq format, and **--seqType** is the type of these input reads. The option **--JM** defines the number of GB of system memory required for k-mer counting by jellyfish.
 
-**General Trinity Usage**
-
-``` syntaxhighlighter-pre
-Trinity --seqType [fa|fq] --JM <jellyfish_memory> --left input_reads_pair_1.[fa|fq] --right input_reads_pair_2.[fa|fq] [options]
-```
+Additional Trinity **options** can be found in the Trinity website, or by typing:
+{{< highlight bash >}}
+$ Trinity
+{{< /highlight >}}
 
-where **input\_reads\_pair\_1.\[fa\|fq\]**
-and **input\_reads\_pair\_2.\[fa\|fq\]** are the input paired-end files
-of sequence reads in fasta/fastq format, and **--seqType** is the type
-of these input reads. The option **--JM** defines the number of GB of
-system memory required for k-mer counting by jellyfish. Additional
-Trinity **options** can be found in the Trinity website, or by typing:
+Running the Trinity pipeline from beginning to end on large datasets may exceed the walltime limit for a single job. Therefore, Trinity provides a mechanism to run the workflow in four separate steps, where each step resumes from the previous one. The same Trinity command and options are run for each step, with an additional option that is included for the different steps. On the last step, the Trinity command is run as normal.
 
-**Additional Trinity Options**
-
-``` syntaxhighlighter-pre
-[<username>@login.tusker ~]$ Trinity
-```
-
-Running the Trinity pipeline from beginning to end on large datasets may
-exceed the walltime limit for a single job. Therefore, Trinity provides
-a mechanism to run the workflow in four separate steps, where each step
-resumes from the previous one. The same Trinity command and options are
-run for each step, with difference of an additional option that is
-included for the different steps. On the last step, the Trinity command
-is run as normal.
-
-**Step 1:**
-
-**Trinity Step 1 Options**
-
-``` syntaxhighlighter-pre
+{{% panel theme="info" header="Step 1 Options" %}}
+{{< highlight bash >}}
 Trinity.pl [options] --no_run_chrysalis
-```
-
-**Step 2: **
+{{< /highlight >}}
+{{% /panel %}}
 
-**Trinity Step 2 Options**
-
-``` syntaxhighlighter-pre
+{{% panel theme="info" header="Step 2 Options" %}}
+{{< highlight bash >}}
 Trinity.pl [options] --no_run_quantifygraph
-```
-
-**Step 3:**
-
-**Trinity Step 3 Options**
+{{< /highlight >}}
+{{% /panel %}}
 
-``` syntaxhighlighter-pre
+{{% panel theme="info" header="Step 3 Options" %}}
+{{< highlight bash >}}
 Trinity.pl [options] --no_run_butterfly
-```
+{{< /highlight >}}
+{{% /panel %}}
 
-**Step 4:**
-
-**Trinity Step 4 Options**
-
-``` syntaxhighlighter-pre
+{{% panel theme="info" header="Step 4 Options" %}}
+{{< highlight bash >}}
 Trinity.pl [options]
-```
-
-Each step may be run as its own job, providing a workaround for the
-single job walltime limit. The following page describes how to run each
-step of Trinity as a single job under the SLURM scheduler on HCC:
-
- 
-
-**Useful Information**
-
-In order to test the TRINITY (trinity/r2014-04-13p1) performance on
-Tusker, we used three paired-end input fastq files: **small\_1.fastq**,
-**small\_2.fastq**, **medium\_1.fastq**, **medium\_2.fastq**,
-**large\_1.fastq**, **large\_2.fastq. **Some statistics about the input
-files and the time and memory resources required for TRINITY are shown
-on the table below:
-
- 
-
-**total \# of sequences**
-
-**total \# of bases**
-
-**total size in MB**
-
-**Trinity Step 1 required time**
-
-**Trinity Step 1 required memory**
-
-Trinity Step 2 required time
-
-Trinity Step 2 required memory
-
-Trinity Step 3 required time
-
-Trinity Step 3 required memory
-
-Trinity Step 4 required time
-
-Trinity Step 4 required memory
-
-\# of used CPUs
-
-**small\_1.fastq**
-
-50,121
-
-2,506,050
-
-8.010 MB
-
-\~ 1 minute
-
-\~ 35 GB
-
-\~ 0.01 hours
-
-\~ 0.6 GB
-
-\~ 0.2 minutes
-
-\~ 0.07 GB
-
-\~ 0.008 hours
-
-\~ 0.8 GB
-
-8
-
-**small\_2.fastq**
-
-50,121
-
-2,506,050
-
-8.010 MB
-
-**medium\_1.fastq**
-
-786,742
-
-59,792,392
-
-152 MB
-
-\~ 3 minutes
-
-\~ 68 GB
-
-\~ 0.1 hours
-
-\~ 3 GB
-
-\~ 0.8 minutes
-
-\~ 0.6 GB
-
-\~ 0.3 hours
-
-\~ 5 GB
-
-8
-
-**medium\_2.fastq**
-
-786,742
-
-59,792,392
-
-152 MB
-
-**large\_1.fastq**
-
-10,174,715
-
-1,027,646,215
-
-3,376 MB
-
-\~ 58 minutes
-
-\~ 80 GB
-
-\~ 5 hours
-
-\~ 30 GB
-
-\~ 35 minutes
-
-\~ 8 GB
-
-\~ 13 hours
-
-\~ 30 GB
-
-8
-
-**large\_2.fastq**
-
-10,174,715
-
-1,027,646,215
-
-3,376 MB
-
-Memory Requirement
-
-<span
-class="aui-icon aui-icon-small aui-iconfont-warning confluence-information-macro-icon"></span>
-
-<span style="color: rgb(0,0,0);">The Inchworm (step 1) and Chrysalis
-(step 2) steps can be memory intensive. A basic recommendation is to
-have **1GB of RAM per 1M** </span><span
-style="color: rgb(0,0,0);">**\~76 base Illumina paired-end
-reads**.</span>
+{{< /highlight >}}
+{{% /panel %}}
 
-Attachments:
-------------
+Each step may be run as its own job, providing a workaround for the single job walltime limit. To see how to run each step of Trinity as a single job under the SLURM scheduler on HCC, please check:
+{{% children %}}
 
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[crane\_modules.xml](attachments/8193286/8127532.xml)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[crane\_trinity\_version.xsl](attachments/8193286/8127533.xsl)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[tusker\_modules.xml](attachments/8193286/8127534.xml)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[tusker\_trinity\_version.xsl](attachments/8193286/8127535.xsl)
-(application/octet-stream)  
+\\
+<span style="color: rgb(0,0,0);font-size: 20.0px;line-height: 1.5;">Useful Information</span>
 
+In order to test the Trinity (trinity/r2014-04-13p1) performance on Tusker, we used three paired-end input fastq files, `small_1.fastq` and `small_2.fastq`, `medium_1.fastq` and `medium_2.fastq`, and `large_1.fastq` and `large_2.fastq`. Some statistics about the input files and the time and memory resources used by Trinity on Tusker are shown in the table below:
+{{< readfile file="/static/html/trinity.html" >}}
 
+{{% notice tip %}}
+The Inchworm (step 1) and Chrysalis (step 2) steps can be memory intensive. A basic recommendation is to have **1GB of RAM per 1M ~76 base Illumina paired-end reads**.
+{{% /notice %}}
\ No newline at end of file
diff --git a/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/trinity/running_trinity_in_multiple_steps.md b/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/trinity/running_trinity_in_multiple_steps.md
index e64b4a4f..789f8826 100644
--- a/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/trinity/running_trinity_in_multiple_steps.md
+++ b/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/trinity/running_trinity_in_multiple_steps.md
@@ -1,161 +1,88 @@
-1.  [HCC-DOCS](index.html)
-2.  [HCC-DOCS Home](HCC-DOCS-Home_327685.html)
-3.  [HCC Documentation](HCC-Documentation_332651.html)
-4.  [Running Applications](Running-Applications_7471153.html)
-5.  [Bioinformatics Tools](Bioinformatics-Tools_8193279.html)
-6.  [De Novo Assembly Tools](De-Novo-Assembly-Tools_8193280.html)
-7.  [Trinity](Trinity_8193286.html)
-
-<span id="title-text"> HCC-DOCS : Running Trinity in Multiple Steps </span>
-===========================================================================
-
-Created by <span class="author"> Adam Caprez</span>, last modified by
-<span class="editor"> Natasha Pavlovikj</span> on Dec 12, 2016
-
-**Running Trinity with Paired-End fastq data with 8 CPUs and 100GB of
-RAM**
-
-<span style="color: rgb(0,0,0);">The first step of running Trinity is to
-run Trinity with the option  **--no\_run\_chrysalis**:</span>
-
-**trinity\_step1.submit**
-
-\#!/bin/sh  
-\#SBATCH --job-name=Trinity\_Step1  
-\#SBATCH --nodes=1  
-\#SBATCH --ntasks-per-node=8  
-\#SBATCH --time=168:00:00  
-\#SBATCH --mem=100gb  
-\#SBATCH --output=Trinity\_Step1.%J.out  
-\#SBATCH --error=Trinity\_Step1.%J.err
-
- 
-
-|                                                             |
-|-------------------------------------------------------------|
-| module load bowtie/1.0.0 samtools/0.1 trinity/r2014-04-13p1 |
-
-Trinity --seqType fq --JM 100G --left input\_reads\_pair\_1.fastq
---right input\_reads\_pair\_2.fastq --SS\_lib\_type FR --output
-trinity\_out/ --CPU $SLURM\_NTASKS\_PER\_NODE --no\_run\_chrysalis
-
-<span style="color: rgb(0,0,0);">  
-</span>
-
-<span style="color: rgb(0,0,0);">The second step of running Trinity is
-to run Trinity with the option </span><span
-style="color: rgb(0,0,0);"> </span><span
-style="color: rgb(0,0,0);"> </span>**--no\_run\_quantifygraph**<span
-style="color: rgb(0,0,0);">:</span>
-
-**trinity\_step2.submit**
-
-\#!/bin/sh  
-\#SBATCH --job-name=Trinity\_Step2  
-\#SBATCH --nodes=1  
-\#SBATCH --ntasks-per-node=8  
-\#SBATCH --time=168:00:00  
-\#SBATCH --mem=100gb  
-\#SBATCH --output=Trinity\_Step2.%J.out  
-\#SBATCH --error=Trinity\_Step2.%J.err
-
- 
-
-|                                                             |
-|-------------------------------------------------------------|
-| module load bowtie/1.0.0 samtools/0.1 trinity/r2014-04-13p1 |
-
-Trinity --seqType fq --JM 100G --left input\_reads\_pair\_1.fastq
---right input\_reads\_pair\_2.fastq --SS\_lib\_type FR --output
-trinity\_out/ --CPU $SLURM\_NTASKS\_PER\_NODE --no\_run\_quantifygraph
-
-<span style="color: rgb(0,0,0);">  
-</span>
-
-<span style="color: rgb(0,0,0);">The third step of running Trinity is to
-run Trinity with the option </span><span
-style="line-height: 1.4285715;"> **--no\_run\_butterfly**:</span>
-
-**trinity\_step3.submit**
-
-\#!/bin/sh  
-\#SBATCH --job-name=Trinity\_Step3  
-\#SBATCH --nodes=1  
-\#SBATCH --ntasks-per-node=8  
-\#SBATCH --time=168:00:00  
-\#SBATCH --mem=100gb  
-\#SBATCH --output=Trinity\_Step3.%J.out  
-\#SBATCH --error=Trinity\_Step3.%J.err
-
- 
-
-|                                                             |
-|-------------------------------------------------------------|
-| module load bowtie/1.0.0 samtools/0.1 trinity/r2014-04-13p1 |
-
-Trinity --seqType fq --JM 100G --left input\_reads\_pair\_1.fastq
---right input\_reads\_pair\_2.fastq --SS\_lib\_type FR --output
-trinity\_out/ --CPU $SLURM\_NTASKS\_PER\_NODE --no\_run\_butterfly
-
-<span style="line-height: 1.4285715;">  
-</span>
-
-<span style="color: rgb(0,0,0);">The fourth step of running Trinity is
-to run Trinity without any additional option</span><span
-style="color: rgb(0,0,0);">:</span>
-
-**trinity\_step4.submit**
-
-\#!/bin/sh  
-\#SBATCH --job-name=Trinity\_Step4  
-\#SBATCH --nodes=1  
-\#SBATCH --ntasks-per-node=8  
-\#SBATCH --time=168:00:00  
-\#SBATCH --mem=100gb  
-\#SBATCH --output=Trinity\_Step4.%J.out  
-\#SBATCH --error=Trinity\_Step4.%J.err
-
- 
-
-|                                                             |
-|-------------------------------------------------------------|
-| module load bowtie/1.0.0 samtools/0.1 trinity/r2014-04-13p1 |
-
-Trinity --seqType fq --JM 100G --left input\_reads\_pair\_1.fastq
---right input\_reads\_pair\_2.fastq --SS\_lib\_type FR --output
-trinity\_out/ --CPU $SLURM\_NTASKS\_PER\_NODE
-
- 
-
-**<span style="color: rgb(0,0,0);">Trinity Output</span>**
-
-<span style="color: rgb(0,0,0);">Trinity outputs number of files in its
-*trinity\_out/* output directory after each executed step. The output
-file *Trinity.fasta* is the final Trinity output that contains the
-assembled transcripts.</span>
-
-<span style="color: rgb(0,0,0);">  
-</span>
-
-Memory Requirement
-
-<span
-class="aui-icon aui-icon-small aui-iconfont-warning confluence-information-macro-icon"></span>
-
-<span style="color: rgb(0,0,0);">The Inchworm (step 1) and Chrysalis
-(step 2) steps can be memory intensive. A basic recommendation is to
-have **1GB of RAM per 1M **</span><span
-style="color: rgb(0,0,0);">**\~76 base Illumina paired-end
-reads**.</span>
-
-Attachments:
-------------
-
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[cb\_trinity\_module.xsl](attachments/8193287/8127536.xsl)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[tusker\_modules.xml](attachments/8193287/8127537.xml)
-(application/octet-stream)  
-
-
++++
+title = "Running Trinity in Multiple Steps"
+description =  "How to run Trinity in multiple steps on HCC resources"
+weight = "10"
++++
+
+<span style="color: rgb(0,0,0);font-size: 20.0px;line-height: 1.5;">Running Trinity with Paired-End fastq data with 8 CPUs and 100GB of RAM</span>
+
+The first step of running Trinity is to run Trinity with the option **--no_run_chrysalis**:
+{{% panel header="`trinity_step1.submit`"%}}
+{{< highlight bash >}}
+#!/bin/sh
+#SBATCH --job-name=Trinity_Step1
+#SBATCH --nodes=1
+#SBATCH --ntasks-per-node=8
+#SBATCH --time=168:00:00
+#SBATCH --mem=100gb
+#SBATCH --output=Trinity_Step1.%J.out
+#SBATCH --error=Trinity_Step1.%J.err
+
+module load trinity/2.6
+
+Trinity --seqType fq --JM 100G --left input_reads_pair_1.fastq --right input_reads_pair_2.fastq --SS_lib_type FR --output trinity_out/ --CPU $SLURM_NTASKS_PER_NODE --no_run_chrysalis
+{{< /highlight >}}
+{{% /panel %}}
+
+The second step of running Trinity is to run Trinity with the option **--no_run_quantifygraph**:
+{{% panel header="`trinity_step2.submit`"%}}
+{{< highlight bash >}}
+#!/bin/sh
+#SBATCH --job-name=Trinity_Step2
+#SBATCH --nodes=1
+#SBATCH --ntasks-per-node=8
+#SBATCH --time=168:00:00
+#SBATCH --mem=100gb
+#SBATCH --output=Trinity_Step2.%J.out
+#SBATCH --error=Trinity_Step2.%J.err
+
+module load trinity/2.6
+
+Trinity --seqType fq --JM 100G --left input_reads_pair_1.fastq --right input_reads_pair_2.fastq --SS_lib_type FR --output trinity_out/ --CPU $SLURM_NTASKS_PER_NODE --no_run_quantifygraph
+{{< /highlight >}}
+{{% /panel %}}
+
+The third step of running Trinity is to run Trinity with the option **--no_run_butterfly**:
+{{% panel header="`trinity_step3.submit`"%}}
+{{< highlight bash >}}
+#!/bin/sh
+#SBATCH --job-name=Trinity_Step3
+#SBATCH --nodes=1
+#SBATCH --ntasks-per-node=8
+#SBATCH --time=168:00:00
+#SBATCH --mem=100gb
+#SBATCH --output=Trinity_Step3.%J.out
+#SBATCH --error=Trinity_Step3.%J.err
+
+module load trinity/2.6
+
+Trinity --seqType fq --JM 100G --left input_reads_pair_1.fastq --right input_reads_pair_2.fastq --SS_lib_type FR --output trinity_out/ --CPU $SLURM_NTASKS_PER_NODE --no_run_butterfly
+{{< /highlight >}}
+{{% /panel %}}
+
+The fourth step of running Trinity is to run Trinity without any additional option:
+{{% panel header="`trinity_step4.submit`"%}}
+{{< highlight bash >}}
+#!/bin/sh
+#SBATCH --job-name=Trinity_Step4
+#SBATCH --nodes=1
+#SBATCH --ntasks-per-node=8
+#SBATCH --time=168:00:00
+#SBATCH --mem=100gb
+#SBATCH --output=Trinity_Step4.%J.out
+#SBATCH --error=Trinity_Step4.%J.err
+
+module load trinity/2.6
+
+Trinity --seqType fq --JM 100G --left input_reads_pair_1.fastq --right input_reads_pair_2.fastq --SS_lib_type FR --output trinity_out/ --CPU $SLURM_NTASKS_PER_NODE
+{{< /highlight >}}
+{{% /panel %}}
+
+\\
+<span style="color: rgb(0,0,0);font-size: 20.0px;line-height: 1.5;">Trinity Output</span>
+
+Trinity outputs number of files in its `trinity_out/` output directory after each executed step. The output file `Trinity.fasta` is the final Trinity output that contains the assembled transcripts.
+
+{{% notice tip %}}
+The Inchworm (step 1) and Chrysalis (step 2) steps can be memory intensive. A basic recommendation is to have **1GB of RAM per 1M ~76 base Illumina paired-end reads**.
+{{% /notice %}}
\ No newline at end of file
diff --git a/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/velvet/_index.md b/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/velvet/_index.md
index 087f8ce7..bd734325 100644
--- a/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/velvet/_index.md
+++ b/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/velvet/_index.md
@@ -1,171 +1,21 @@
-1.  [HCC-DOCS](index.html)
-2.  [HCC-DOCS Home](HCC-DOCS-Home_327685.html)
-3.  [HCC Documentation](HCC-Documentation_332651.html)
-4.  [Running Applications](Running-Applications_7471153.html)
-5.  [Bioinformatics Tools](Bioinformatics-Tools_8193279.html)
-6.  [De Novo Assembly Tools](De-Novo-Assembly-Tools_8193280.html)
++++
+title = "Velvet"
+description = "How to use Velvet on HCC machines"
+weight = "52"
++++
 
-<span id="title-text"> HCC-DOCS : Velvet </span>
-================================================
 
-Created by <span class="author"> Adam Caprez</span> on Sep 04, 2014
+[Velvet] (https://www.ebi.ac.uk/~zerbino/velvet/) is a general sequence assembler designed to produce assembly from short, as well as long reads. Running Velvet consists of a sequence of two commands **velveth** and **velvetg**. **velveth** produces a hash table of k-mers, while **velvetg** constructs the genome assembly. The k-mer length, also known as hash length corresponds to the length, in base pairs, of the words of the reads being hashed.
 
-| Name   | Version | Resource | Additional Information                                                                              |
-|--------|---------|----------|-----------------------------------------------------------------------------------------------------|
-| velvet | 1.2     | Tusker   | Velvet is compiled with CATEGORIES=4, MAXKMERLENGTH=64, OPENMP=1, LONGSEQUENCES=1 and BIGASSEMBLY=1 |
+Velvet has lots of parameters that can be found in its [manual] (https://www.ebi.ac.uk/~zerbino/velvet/Manual.pdf). However, the k-mer value is crucial in obtaining optimal assemblies. Higher k-mer values increase the specificity, and lower k-mer values increase the sensitivity.
 
-|        |     |       |                                                                                                     |
-|--------|-----|-------|-----------------------------------------------------------------------------------------------------|
-| velvet | 1.2 | Crane | Velvet is compiled with CATEGORIES=4, MAXKMERLENGTH=64, OPENMP=1, LONGSEQUENCES=1 and BIGASSEMBLY=1 |
+Velvet supports multiple file formats: `fasta`, `fastq`, `fasta.gz`, `fastq.gz`, `sam`, `bam`, `eland`, `gerald`. Velvet also supports different read categories for different sequencing technologies and libraries, e.g. `short`, `shortPaired`, `short2`, `shortPaired2`, `long`, `longPaired`.
 
- 
-
-Velvet
-(<a href="http://www.ebi.ac.uk/~zerbino/velvet/" class="external-link">http://www.ebi.ac.uk/~zerbino/velvet/</a>)
-is a general sequence assembler designed to produce assembly from short,
-as well as long reads. Running Velvet consists of a sequence of two
-commands: **velveth** and **velvetg**. **Velveth** produces a hash table
-of k-mers, while **velvetg** constructs the genome assembly. The k-mer
-length, also known as hash length corresponds to the length, in base
-pairs, of the words of the reads being hashed.
-
-Velvet has a lot of parameters that can be found in its manual:
-<a href="https://www.ebi.ac.uk/~zerbino/velvet/Manual.pdf" class="external-link">https://www.ebi.ac.uk/~zerbino/velvet/Manual.pdf</a>.
-However, the k-mer value is crucial in obtaining optimal assemblies.
-Higher k-mer values increase the specificity, and lower k-mer values
-increase the sensitivity.
-
-Velvet supports multiple file formats: **fasta**, **fastq**,
-**fasta.gz**, **fastq.gz**, **sam**, **bam**, **eland**,
-**gerald. **Velvet also supports different read categories for different
-sequencing technologies and libraries: **short**, **shortPaired**,
-**short2**, **shortPaired2**, **long**, **longPaired**.
-
-Each step of Velvet (**velveth** and **velvetg**) may be run as its own
-job. This following pages describe how to run Velvet in this manner
-under the SLURM scheduler on HCC and provide example submit scripts:
-
- 
-
-**Useful Information**
-
-In order to test the VELVET (velvet/1.2) performance on Tusker, we used
-three paired-end input fastq files: **small\_1.fastq**,
-**small\_2.fastq**, **medium\_1.fastq**, **medium\_2.fastq**,
-**large\_1.fastq**, **large\_2.fastq**. Some statistics about the input
-files and the time and memory resources required for VELVET are shown on
-the table below:
-
- 
-
-**total \# of sequences**
-
-**total \# of bases**
-
-**total size in MB**
-
-**VELVETH required time**
-
-**VELVETH required memory**
-
-**VELVETG required time**
-
-**VELVETG required memory**
-
-\# of used CPUs
-
-**small\_1.fastq**
-
-50,121
-
-2,506,050
-
-8.010 MB
-
-\~ 0.02 minutes
-
-\~ 0.3 GB
-
-\~ 0.08 minutes
-
-\~ 0.2 GB
-
-8
-
-**small\_2.fastq**
-
-50,121
-
-2,506,050
-
-8.010 MB
-
-**medium\_1.fastq**
-
-786,742
-
-59,792,392
-
-152 MB
-
-\~ 0.4 minutes
-
-\~ 1.5 GB
-
-\~ 0.8 minutes
-
-\~ 0.9 GB
-
-8
-
-**medium\_2.fastq**
-
-786,742
-
-59,792,392
-
-152 MB
-
-**large\_1.fastq**
-
-10,174,715
-
-1,027,646,215
-
-3,376 MB
-
-\~ 7 minutes
-
-\~ 23 GB
-
-\~ 45 minutes
-
-\~ 51 GB
-
-8
-
-**large\_2.fastq**
-
-10,174,715
-
-1,027,646,215
-
-3,376 MB
-
-Attachments:
-------------
-
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[crane\_modules.xml](attachments/8193281/8127519.xml)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[crane\_velvet\_version.xsl](attachments/8193281/8127520.xsl)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[tusker\_modules.xml](attachments/8193281/8127521.xml)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[tusker\_velvet\_version.xsl](attachments/8193281/8127522.xsl)
-(application/octet-stream)  
+Each step of Velvet (**velveth** and **velvetg**) may be run as its own job. The following pages describe how to run Velvet in this manner on HCC and provide example submit scripts:
+{{% children %}}
 
+\\
+<span style="color: rgb(0,0,0);font-size: 20.0px;line-height: 1.5;">Useful Information</span>
 
+In order to test the Velvet (velvet/1.2) performance on Tusker, we used three paired-end input fastq files, `small_1.fastq` and `small_2.fastq`, `medium_1.fastq` and `medium_2.fastq`, and `large_1.fastq` and `large_2.fastq`. Some statistics about the input files and the time and memory resources used by Velvet on Tusker are shown in the table below:
+{{< readfile file="/static/html/velvet.html" >}}
\ No newline at end of file
diff --git a/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/velvet/running_velvet_with_paired_end_data.md b/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/velvet/running_velvet_with_paired_end_data.md
index 9e26ef77..dc7fe9ae 100644
--- a/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/velvet/running_velvet_with_paired_end_data.md
+++ b/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/velvet/running_velvet_with_paired_end_data.md
@@ -1,1329 +1,64 @@
-1.  [HCC-DOCS](index.html)
-2.  [HCC-DOCS Home](HCC-DOCS-Home_327685.html)
-3.  [HCC Documentation](HCC-Documentation_332651.html)
-4.  [Running Applications](Running-Applications_7471153.html)
-5.  [Bioinformatics Tools](Bioinformatics-Tools_8193279.html)
-6.  [De Novo Assembly Tools](De-Novo-Assembly-Tools_8193280.html)
-7.  [Velvet](Velvet_8193281.html)
++++
+title = "Running Velvet with Paired-End Data"
+description =  "How to run velvet with paired-end data on HCC resources"
+weight = "10"
++++
 
-<span id="title-text"> HCC-DOCS : Running Velvet with Paired-End Data </span>
-=============================================================================
-
-Created by <span class="author"> Adam Caprez</span>, last modified by
-<span class="editor"> Natasha Pavlovikj</span> on Dec 12, 2016
-
-**Running Velvet with Paired-End long fastq data with k-mer = 43, 8 CPUs
-and 100GB of RAM**
+<span style="color: rgb(0,0,0);font-size: 20.0px;line-height: 1.5;">Running Velvet with Paired-End long fastq data with k-mer=43, 8 CPUs and 100GB of RAM</span>
 
 The first step of running Velvet is to run **velveth**:
-
-**velveth.submit**
-
-\#!/bin/sh  
-\#SBATCH --job-name=Velvet\_Velveth  
-\#SBATCH --nodes=1  
-\#SBATCH --ntasks-per-node=8  
-\#SBATCH --time=168:00:00  
-\#SBATCH --mem=100gb  
-\#SBATCH --output=Velveth.%J.out  
-\#SBATCH --error=Velveth.%J.err
-
- 
-
-|                        |
-|------------------------|
-| module load velvet/1.2 |
-
-export OMP\_NUM\_THREADS=$SLURM\_NTASKS\_PER\_NODE
-
-velveth output\_directory/ 43 -fastq -longPaired -separate
-input\_reads\_pair\_1.fastq input\_reads\_pair\_2.fastq
-
-<span style="line-height: 1.4285715;">After
-running </span>**velveth**<span style="line-height: 1.4285715;">, the
-next step is to run </span>**velvetg**<span
-style="line-height: 1.4285715;"> on the *output\_directory/* and files
-generated from </span>**velveth:**
-
-**velvetg.submit**
-
-\#!/bin/sh  
-\#SBATCH --job-name=Velvet\_Velvetg  
-\#SBATCH --nodes=1  
-\#SBATCH --ntasks-per-node=8  
-\#SBATCH --time=168:00:00  
-\#SBATCH --mem=100gb  
-\#SBATCH --output=Velvetg.%J.out  
-\#SBATCH --error=Velvetg.%J.err
-
- 
-
-|                        |
-|------------------------|
-| module load velvet/1.2 |
-
-export OMP\_NUM\_THREADS=$SLURM\_NTASKS\_PER\_NODE
-
-velvetg output\_directory/ -min\_contig\_lgth 200
+{{% panel header="`velveth.submit`"%}}
+{{< highlight bash >}}
+#!/bin/sh
+#SBATCH --job-name=Velvet_Velveth
+#SBATCH --nodes=1
+#SBATCH --ntasks-per-node=8
+#SBATCH --time=168:00:00
+#SBATCH --mem=10gb
+#SBATCH --output=Velveth.%J.out
+#SBATCH --error=Velveth.%J.err
+
+module load velvet/1.2
+export OMP_NUM_THREADS=$SLURM_NTASKS_PER_NODE
+
+velveth output_directory/ 43 -fastq -longPaired -separate input_reads_pair_1.fastq input_reads_pair_2.fastq
+{{< /highlight >}}
+{{% /panel %}}
+
+After running **velveth**, the next step is to run **velvetg** on the `output_directory/` and files generated from **velveth**:
+{{% panel header="`velvetg.submit`"%}}
+{{< highlight bash >}}
+#!/bin/sh
+#SBATCH --job-name=Velvet_Velvetg
+#SBATCH --nodes=1
+#SBATCH --ntasks-per-node=8
+#SBATCH --time=168:00:00
+#SBATCH --mem=100gb
+#SBATCH --output=Velvetg.%J.out
+#SBATCH --error=Velvetg.%J.err
+
+module load velvet/1.2
+export OMP_NUM_THREADS=$SLURM_NTASKS_PER_NODE
+
+velvetg output_directory/ -min_contig_lgth 200
+{{< /highlight >}}
+{{% /panel %}}
 
 Both **velveth** and **velvetg** are multi-threaded.
-
- 
-
-**Check *output\_directory/* after velveth:**
-
-**Check Output Directory After Velveth**
-
-``` syntaxhighlighter-pre
-[<username>@login.tusker ~]$ ls output_directory/
+\\
+\\
+{{% panel header="`Output directory after velveth`"%}}
+{{< highlight bash >}}
+$ ls output_directory/
 Log  Roadmaps  Sequences
-```
+{{< /highlight >}}
+{{% /panel %}}
 
-************Check ***output\_directory/*** after velvetg:************
-
-**Check Output Directory After Velvetg**
-
-``` syntaxhighlighter-pre
-[<username>@login.tusker ~]$ ls output_directory/
+{{% panel header="`Output directory after velvetg`"%}}
+{{< highlight bash >}}
+$ ls output_directory/
 contigs.fa  Graph  LastGraph  Log  PreGraph  Roadmaps  Sequences  stats.txt
-```
-
-The output fasta file *contigs.fa* is the final Velvet output that
-contains the assembled contigs. More information about the output files
-is provided in the Velvet manual.
-
-Attachments:
-------------
-
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[cb\_velvet\_module.xsl](attachments/8193283/8127525.xsl)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[tusker\_modules.xml](attachments/8193283/9863458.xml)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[tusker\_modules.xml](attachments/8193283/9863557.xml)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[tusker\_modules.xml](attachments/8193283/9863659.xml)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[tusker\_modules.xml](attachments/8193283/9863716.xml)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[tusker\_modules.xml](attachments/8193283/9863800.xml)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[tusker\_modules.xml](attachments/8193283/9863852.xml)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[tusker\_modules.xml](attachments/8193283/9863913.xml)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[tusker\_modules.xml](attachments/8193283/10387514.xml)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[tusker\_modules.xml](attachments/8193283/10944563.xml)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[tusker\_modules.xml](attachments/8193283/10944603.xml)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[tusker\_modules.xml](attachments/8193283/11632801.xml)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[tusker\_modules.xml](attachments/8193283/11632889.xml)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[tusker\_modules.xml](attachments/8193283/11632939.xml)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[tusker\_modules.xml](attachments/8193283/11633014.xml)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[tusker\_modules.xml](attachments/8193283/11633091.xml)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[tusker\_modules.xml](attachments/8193283/11633161.xml)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[tusker\_modules.xml](attachments/8193283/11633240.xml)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[tusker\_modules.xml](attachments/8193283/11633291.xml)
-(application/octet-stream)  
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-[tusker\_modules.xml](attachments/8193283/35324633.xml)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[tusker\_modules.xml](attachments/8193283/35324923.xml)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[tusker\_modules.xml](attachments/8193283/35325655.xml)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[tusker\_modules.xml](attachments/8193283/35325768.xml)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[tusker\_modules.xml](attachments/8193283/35326755.xml)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[tusker\_modules.xml](attachments/8193283/9863422.xml)
-(application/octet-stream)  
-
+{{< /highlight >}}
+{{% /panel %}}
 
+The output fasta file `contigs.fa` is the final Velvet output that contains the assembled contigs. More information about the output files is provided in the Velvet manual.
\ No newline at end of file
diff --git a/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/velvet/running_velvet_with_single_end_and_paired_end_data.md b/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/velvet/running_velvet_with_single_end_and_paired_end_data.md
index a11de810..33a53174 100644
--- a/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/velvet/running_velvet_with_single_end_and_paired_end_data.md
+++ b/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/velvet/running_velvet_with_single_end_and_paired_end_data.md
@@ -1,106 +1,64 @@
-1.  [HCC-DOCS](index.html)
-2.  [HCC-DOCS Home](HCC-DOCS-Home_327685.html)
-3.  [HCC Documentation](HCC-Documentation_332651.html)
-4.  [Running Applications](Running-Applications_7471153.html)
-5.  [Bioinformatics Tools](Bioinformatics-Tools_8193279.html)
-6.  [De Novo Assembly Tools](De-Novo-Assembly-Tools_8193280.html)
-7.  [Velvet](Velvet_8193281.html)
-
-<span id="title-text"> HCC-DOCS : Running Velvet with Single-End and Paired-End Data </span>
-============================================================================================
-
-Created by <span class="author"> Adam Caprez</span>, last modified by
-<span class="editor"> Natasha Pavlovikj</span> on Dec 12, 2016
-
-**Running Velvet with Single-End and Paired-End short fasta data with
-k-mer = 51, 8 CPUs and 100GB of RAM**
-
-The first step of running Velvet is to run** **velveth**:**
-
-**velveth.submit**
-
-\#!/bin/sh  
-\#SBATCH --job-name=Velvet\_Velveth  
-\#SBATCH --nodes=1  
-\#SBATCH --ntasks-per-node=8  
-\#SBATCH --time=168:00:00  
-\#SBATCH --mem=100gb  
-\#SBATCH --output=Velveth.%J.out  
-\#SBATCH --error=Velveth.%J.err
-
- 
-
-|                        |
-|------------------------|
-| module load velvet/1.2 |
-
-export OMP\_NUM\_THREADS=$SLURM\_NTASKS\_PER\_NODE
-
-velveth output\_directory/ 51 -fasta -short input\_reads.fasta -fasta
--shortPaired2 -separate input\_reads\_pair\_1.fasta
-input\_reads\_pair\_2.fasta
-
-<span style="line-height: 1.4285715;">After
-running </span>**velveth**<span style="line-height: 1.4285715;">, the
-next step is to run </span>**velvetg**<span
-style="line-height: 1.4285715;"> on the *output\_directory/* and files
-generated from </span>**velveth:**
-
-**velvetg.submit**
-
-\#!/bin/sh  
-\#SBATCH --job-name=Velvet\_Velvetg  
-\#SBATCH --nodes=1  
-\#SBATCH --ntasks-per-node=8  
-\#SBATCH --time=168:00:00  
-\#SBATCH --mem=100gb  
-\#SBATCH --output=Velvetg.%J.out  
-\#SBATCH --error=Velvetg.%J.err
-
- 
-
-|                        |
-|------------------------|
-| module load velvet/1.2 |
-
-export OMP\_NUM\_THREADS=$SLURM\_NTASKS\_PER\_NODE
-
-velvetg output\_directory/ -min\_contig\_lgth 200
-
-Both **velveth** and **velvetg** are multi-threaded.
-
- 
-
-**Check *output\_directory/* after velveth:**
-
-**Check Output Directory After Velveth**
-
-``` syntaxhighlighter-pre
-[<username>@login.tusker ~]$ ls output_directory/
++++
+title = "Running Velvet with Single-End and Paired-End Data"
+description =  "How to run velvet with single-end and paired-end data on HCC resources"
+weight = "10"
++++
+
+<span style="color: rgb(0,0,0);font-size: 20.0px;line-height: 1.5;">Running Velvet with Single-End and Paired-End short fasta data with k-mer=51, 8 CPUs and 100GB of RAM</span>
+
+The first step of running Velvet is to run **velveth**:
+{{% panel header="`velveth.submit`"%}}
+{{< highlight bash >}}
+#!/bin/sh
+#SBATCH --job-name=Velvet_Velveth
+#SBATCH --nodes=1
+#SBATCH --ntasks-per-node=8
+#SBATCH --time=168:00:00
+#SBATCH --mem=10gb
+#SBATCH --output=Velveth.%J.out
+#SBATCH --error=Velveth.%J.err
+
+module load velvet/1.2
+export OMP_NUM_THREADS=$SLURM_NTASKS_PER_NODE
+
+velveth output_directory/ 51 -fasta -short input_reads.fasta -fasta -shortPaired2 -separate input_reads_pair_1.fasta input_reads_pair_2.fasta
+{{< /highlight >}}
+{{% /panel %}}
+
+After running **velveth**, the next step is to run **velvetg** on the `output_directory/` and files generated from **velveth**:
+{{% panel header="`velvetg.submit`"%}}
+{{< highlight bash >}}
+#!/bin/sh
+#SBATCH --job-name=Velvet_Velvetg
+#SBATCH --nodes=1
+#SBATCH --ntasks-per-node=8
+#SBATCH --time=168:00:00
+#SBATCH --mem=100gb
+#SBATCH --output=Velvetg.%J.out
+#SBATCH --error=Velvetg.%J.err
+
+module load velvet/1.2
+export OMP_NUM_THREADS=$SLURM_NTASKS_PER_NODE
+
+velvetg output_directory/ -min_contig_lgth 200
+{{< /highlight >}}
+{{% /panel %}}
+
+Both **velveth** and **velvetg** are multi-threaded.
+\\
+\\
+{{% panel header="`Output directory after velveth`"%}}
+{{< highlight bash >}}
+$ ls output_directory/
 Log  Roadmaps  Sequences
-```
-
-************Check *output\_directory/* after velvetg:************
+{{< /highlight >}}
+{{% /panel %}}
 
-**Check Output Directory After Velvetg**
-
-``` syntaxhighlighter-pre
-[<username>@login.tusker ~]$ ls output_directory/
+{{% panel header="`Output directory after velvetg`"%}}
+{{< highlight bash >}}
+$ ls output_directory/
 contigs.fa  Graph  LastGraph  Log  PreGraph  Roadmaps  Sequences  stats.txt
-```
-
-The output fasta file *contigs.fa* is the final Velvet output that
-contains the assembled contigs. More information about the output files
-is provided in the Velvet manual.
-
-Attachments:
-------------
-
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[cb\_velvet\_module.xsl](attachments/8193284/8127527.xsl)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[tusker\_modules.xml](attachments/8193284/8127528.xml)
-(application/octet-stream)  
-
+{{< /highlight >}}
+{{% /panel %}}
 
+The output fasta file `contigs.fa` is the final Velvet output that contains the assembled contigs. More information about the output files is provided in the Velvet manual.
\ No newline at end of file
diff --git a/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/velvet/running_velvet_with_single_end_data.md b/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/velvet/running_velvet_with_single_end_data.md
index 83be874c..0545429d 100644
--- a/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/velvet/running_velvet_with_single_end_data.md
+++ b/content/guides/running_applications/bioinformatics_tools/de_novo_assembly_tools/velvet/running_velvet_with_single_end_data.md
@@ -1,102 +1,64 @@
-1.  [HCC-DOCS](index.html)
-2.  [HCC-DOCS Home](HCC-DOCS-Home_327685.html)
-3.  [HCC Documentation](HCC-Documentation_332651.html)
-4.  [Running Applications](Running-Applications_7471153.html)
-5.  [Bioinformatics Tools](Bioinformatics-Tools_8193279.html)
-6.  [De Novo Assembly Tools](De-Novo-Assembly-Tools_8193280.html)
-7.  [Velvet](Velvet_8193281.html)
-
-<span id="title-text"> HCC-DOCS : Running Velvet with Single-End Data </span>
-=============================================================================
-
-Created by <span class="author"> Adam Caprez</span>, last modified by
-<span class="editor"> Natasha Pavlovikj</span> on Dec 12, 2016
-
-**Running Velvet with Single-End short fasta data with k-mer = 31, 8
-CPUs and 100GB of RAM**
-
-The first step of running Velvet is to run **velveth**:
-
-**velveth.submit**
-
-\#!/bin/sh  
-\#SBATCH --job-name=Velvet\_Velveth  
-\#SBATCH --nodes=1  
-\#SBATCH --ntasks-per-node=8  
-\#SBATCH --time=168:00:00  
-\#SBATCH --mem=100gb  
-\#SBATCH --output=Velveth.%J.out  
-\#SBATCH --error=Velveth.%J.err
-
- 
-
-|                        |
-|------------------------|
-| module load velvet/1.2 |
-
-export OMP\_NUM\_THREADS=$SLURM\_NTASKS\_PER\_NODE
-
-velveth output\_directory/ 31 -fasta -short input\_reads.fasta
-
-After running **velveth**, the next step is to run **velvetg** on the
-*output\_directory/* and files generated from **velveth:**
-
-**velvetg.submit**
-
-\#!/bin/sh  
-\#SBATCH --job-name=Velvet\_Velvetg  
-\#SBATCH --nodes=1  
-\#SBATCH --ntasks-per-node=8  
-\#SBATCH --time=168:00:00  
-\#SBATCH --mem=100gb  
-\#SBATCH --output=Velvetg.%J.out  
-\#SBATCH --error=Velvetg.%J.err
-
- 
-
-|                        |
-|------------------------|
-| module load velvet/1.2 |
-
-export OMP\_NUM\_THREADS=$SLURM\_NTASKS\_PER\_NODE
-
-velvetg output\_directory/ -min\_contig\_lgth 200
-
-Both **velveth** and **velvetg** are multi-threaded.
-
-****  
-****
-
-****Check *output\_directory/* after velveth:****
-
-**Check Output Directory After Velveth**
-
-``` syntaxhighlighter-pre
-[<username>@login.tusker ~]$ ls output_directory/
++++
+title = "Running Velvet with Single-End Data"
+description =  "How to run velvet with single-end data on HCC resources"
+weight = "10"
++++
+
+<span style="color: rgb(0,0,0);font-size: 20.0px;line-height: 1.5;">Running Velvet with Single-End short fasta data with k-mer=31, 8 CPUs and 100GB of RAM</span>
+
+The first step of running Velvet is to run **velveth**:
+{{% panel header="`velveth.submit`"%}}
+{{< highlight bash >}}
+#!/bin/sh
+#SBATCH --job-name=Velvet_Velveth
+#SBATCH --nodes=1
+#SBATCH --ntasks-per-node=8
+#SBATCH --time=168:00:00
+#SBATCH --mem=10gb
+#SBATCH --output=Velveth.%J.out
+#SBATCH --error=Velveth.%J.err
+
+module load velvet/1.2
+export OMP_NUM_THREADS=$SLURM_NTASKS_PER_NODE
+
+velveth output_directory/ 31 -fasta -short input_reads.fasta
+{{< /highlight >}}
+{{% /panel %}}
+
+After running **velveth**, the next step is to run **velvetg** on the `output_directory/` and files generated from **velveth**:
+{{% panel header="`velvetg.submit`"%}}
+{{< highlight bash >}}
+#!/bin/sh
+#SBATCH --job-name=Velvet_Velvetg
+#SBATCH --nodes=1
+#SBATCH --ntasks-per-node=8
+#SBATCH --time=168:00:00
+#SBATCH --mem=100gb
+#SBATCH --output=Velvetg.%J.out
+#SBATCH --error=Velvetg.%J.err
+
+module load velvet/1.2
+export OMP_NUM_THREADS=$SLURM_NTASKS_PER_NODE
+
+velvetg output_directory/ -min_contig_lgth 200
+{{< /highlight >}}
+{{% /panel %}}
+
+Both **velveth** and **velvetg** are multi-threaded.
+\\
+\\
+{{% panel header="`Output directory after velveth`"%}}
+{{< highlight bash >}}
+$ ls output_directory/
 Log  Roadmaps  Sequences
-```
-
-************Check *output\_directory/* after velvetg:************
+{{< /highlight >}}
+{{% /panel %}}
 
-**Check Output Directory After Velvetg**
-
-``` syntaxhighlighter-pre
-[<username>@login.tusker ~]$ ls output_directory/
+{{% panel header="`Output directory after velvetg`"%}}
+{{< highlight bash >}}
+$ ls output_directory/
 contigs.fa  Graph  LastGraph  Log  PreGraph  Roadmaps  Sequences  stats.txt
-```
-
-The output fasta file *contigs.fa* is the final Velvet output that
-contains the assembled contigs. More information about the output files
-is provided in the Velvet manual.
-
-Attachments:
-------------
-
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[cb\_velvet\_module.xsl](attachments/8193282/8127523.xsl)
-(application/octet-stream)  
-<img src="assets/images/icons/bullet_blue.gif" width="8" height="8" />
-[tusker\_modules.xml](attachments/8193282/8127524.xml)
-(application/octet-stream)  
-
+{{< /highlight >}}
+{{% /panel %}}
 
+The output fasta file `contigs.fa` is the final Velvet output that contains the assembled contigs. More information about the output files is provided in the Velvet manual.
\ No newline at end of file
diff --git a/static/html/oases.html b/static/html/oases.html
new file mode 100644
index 00000000..75f74c13
--- /dev/null
+++ b/static/html/oases.html
@@ -0,0 +1,68 @@
+ <table style="font-size: small">
+  <colgroup>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+  </colgroup>
+ <tbody>
+ <tr style="font-size: x-small">
+  <th></th>
+  <th>total # of sequences</th>
+  <th>total # of bases</th>
+  <th>total size in MB</th>
+  <th>used time</th>
+  <th>used memory</th>
+  <th># of used CPUs</th>
+ </tr>
+
+ <tr>
+  <td colspan="1"><strong>small_1.fastq</strong></td>
+  <td colspan="1">50,121</td>
+  <td colspan="1">2,506,050</td>
+  <td colspan="1">8.010</td>
+  <td colspan="1" rowspan="2">~ 0.05 minutes</td>
+  <td colspan="1" rowspan="2">~ 0.02 GB</td>
+  <td colspan="1" rowspan="2">1</td>
+ </tr>
+ <tr>
+  <td colspan="1"><strong>small_2.fastq</strong></td>
+  <td colspan="1">50,121</td>
+  <td colspan="1">2,506,050</td>
+  <td colspan="1">8.010</td>
+ </tr>
+ <tr>
+  <td colspan="1"><strong>medium_1.fastq</strong></td>
+  <td colspan="1">786,742</td>
+  <td colspan="1">59,792,392</td>
+  <td colspan="1">152</td>
+  <td colspan="1" rowspan="2">~ 0.25 minutes</td>
+  <td colspan="1" rowspan="2">~ 0.315 GB</td>
+  <td colspan="1" rowspan="2">1</td>
+ </tr>
+ <tr>
+  <td colspan="1"><strong>medium_2.fastq</strong></td>
+  <td colspan="1">786,742</td>
+  <td colspan="1">59,792,392</td>
+  <td colspan="1">152</td>
+ </tr>
+ <tr>
+  <td colspan="1"><strong>large_1.fastq</strong></td>
+  <td colspan="1">10,174,715</td>
+  <td colspan="1">1,027,646,215</td>
+  <td colspan="1">3,376</td>
+  <td colspan="1" rowspan="2">~ 15 minutes</td>
+  <td colspan="1" rowspan="2">~ 30 GB</td>
+  <td colspan="1" rowspan="2">1</td>
+ </tr>
+ <tr>
+  <td colspan="1"><strong>large_2.fastq</strong></td>
+  <td colspan="1">10,174,715</td>
+  <td colspan="1">1,027,646,215</td>
+  <td colspan="1">3,376</td>
+ </tr>
+ </tbody>
+ </table>
\ No newline at end of file
diff --git a/static/html/ray.html b/static/html/ray.html
new file mode 100644
index 00000000..9302b051
--- /dev/null
+++ b/static/html/ray.html
@@ -0,0 +1,68 @@
+ <table style="font-size: small">
+  <colgroup>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+  </colgroup>
+ <tbody>
+ <tr style="font-size: x-small">
+  <th></th>
+  <th>total # of sequences</th>
+  <th>total # of bases</th>
+  <th>total size in MB</th>
+  <th>used time</th>
+  <th>used memory</th>
+  <th># of used CPUs</th>
+ </tr>
+
+ <tr>
+  <td colspan="1"><strong>small_1.fastq</strong></td>
+  <td colspan="1">50,121</td>
+  <td colspan="1">2,506,050</td>
+  <td colspan="1">8.010</td>
+  <td colspan="1" rowspan="2">~ 3 minutes</td>
+  <td colspan="1" rowspan="2">~ 1 GB</td>
+  <td colspan="1" rowspan="2">8</td>
+ </tr>
+ <tr>
+  <td colspan="1"><strong>small_2.fastq</strong></td>
+  <td colspan="1">50,121</td>
+  <td colspan="1">2,506,050</td>
+  <td colspan="1">8.010</td>
+ </tr>
+ <tr>
+  <td colspan="1"><strong>medium_1.fastq</strong></td>
+  <td colspan="1">786,742</td>
+  <td colspan="1">59,792,392</td>
+  <td colspan="1">152</td>
+  <td colspan="1" rowspan="2">~ 15 minutes</td>
+  <td colspan="1" rowspan="2">~ 1.5 GB</td>
+  <td colspan="1" rowspan="2">8</td>
+ </tr>
+ <tr>
+  <td colspan="1"><strong>medium_2.fastq</strong></td>
+  <td colspan="1">786,742</td>
+  <td colspan="1">59,792,392</td>
+  <td colspan="1">152</td>
+ </tr>
+ <tr>
+  <td colspan="1"><strong>large_1.fastq</strong></td>
+  <td colspan="1">10,174,715</td>
+  <td colspan="1">1,027,646,215</td>
+  <td colspan="1">3,376</td>
+  <td colspan="1" rowspan="2">~ 5 hours</td>
+  <td colspan="1" rowspan="2">~ 17 GB</td>
+  <td colspan="1" rowspan="2">8</td>
+ </tr>
+ <tr>
+  <td colspan="1"><strong>large_2.fastq</strong></td>
+  <td colspan="1">10,174,715</td>
+  <td colspan="1">1,027,646,215</td>
+  <td colspan="1">3,376</td>
+ </tr>
+ </tbody>
+ </table>
\ No newline at end of file
diff --git a/static/html/soapdenovo2.html b/static/html/soapdenovo2.html
new file mode 100644
index 00000000..082d2015
--- /dev/null
+++ b/static/html/soapdenovo2.html
@@ -0,0 +1,55 @@
+ <table style="font-size: small">
+  <colgroup>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+  </colgroup>
+ <tbody>
+ <tr style="font-size: x-small">
+  <th></th>
+  <th>total # of sequences</th>
+  <th>total # of bases</th>
+  <th>total size in GB</th>
+  <th>used time</th>
+  <th>used memory</th>
+  <th>used k-mer value</th>
+  <th># of used CPUs</th>
+ </tr>
+
+ <tr>
+  <td colspan="1"><strong>Input data 1</strong></td>
+  <td colspan="1">49,720,374</td>
+  <td colspan="1">7,295,342,636</td>
+  <td colspan="1">10</td>
+  <td colspan="1">~ 1.5 hours</td>
+  <td colspan="1">~ 32 GB</td>
+  <td colspan="1">31</td>
+  <td colspan="1">8</td>
+ </tr>
+ <tr>
+  <td colspan="1"><strong>Input data 2</strong></td>
+  <td colspan="1">166,040,440</td>
+  <td colspan="1">25,072,106,440</td>
+  <td colspan="1">62</td>
+  <td colspan="1">~ 6.5 hours</td>
+  <td colspan="1">~ 125 GB</td>
+  <td colspan="1">31</td>
+  <td colspan="1">8</td>
+ </tr>
+ <tr>
+  <td colspan="1"><strong>Input data 3</strong></td>
+  <td colspan="1">318,681,730</td>
+  <td colspan="1">48,120,941,230</td>
+  <td colspan="1">115</td>
+  <td colspan="1">~ 13 hours</td>
+  <td colspan="1">~ 125 GB</td>
+  <td colspan="1">31</td>
+  <td colspan="1">8</td>
+ </tr>
+ </tbody>
+ </table>
diff --git a/static/html/trinity.html b/static/html/trinity.html
new file mode 100644
index 00000000..928574aa
--- /dev/null
+++ b/static/html/trinity.html
@@ -0,0 +1,97 @@
+ <table style="font-size: small">
+  <colgroup>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+  </colgroup>
+ <tbody>
+ <tr style="font-size: x-small">
+  <th></th>
+  <th>total # of sequences</th>
+  <th>total # of bases</th>
+  <th>total size in MB</th>
+  <th>Trinity step 1 used time</th>
+  <th>Trinity step 1 used memory</th>
+  <th>Trinity step 2 used time</th>
+  <th>Trinity step 2 used memory</th>
+  <th>Trinity step 3 used time</th>
+  <th>Trinity step 3 used memory</th>
+  <th>Trinity step 4 used time</th>
+  <th>Trinity step 4 used memory</th>
+  <th># of used CPUs</th>
+ </tr>
+
+ <tr>
+  <td colspan="1"><strong>small_1.fastq</strong></td>
+  <td colspan="1">50,121</td>
+  <td colspan="1">2,506,050</td>
+  <td colspan="1">8.010</td>
+  <td colspan="1" rowspan="2">~ 1 minute</td>
+  <td colspan="1" rowspan="2">~ 35 GB</td>
+  <td colspan="1" rowspan="2">~ 0.01 hours</td>
+  <td colspan="1" rowspan="2">~ 0.6 GB</td>
+  <td colspan="1" rowspan="2">~ 0.2 minutes</td>
+  <td colspan="1" rowspan="2">~ 0.07 GB</td>
+  <td colspan="1" rowspan="2">~ 0.008 hours</td>
+  <td colspan="1" rowspan="2">~ 0.8 GB</td>
+  <td colspan="1" rowspan="2">8</td>
+ </tr>
+ <tr>
+  <td colspan="1"><strong>small_2.fastq</strong></td>
+  <td colspan="1">50,121</td>
+  <td colspan="1">2,506,050</td>
+  <td colspan="1">8.010</td>
+ </tr>
+ <tr>
+  <td colspan="1"><strong>medium_1.fastq</strong></td>
+  <td colspan="1">786,742</td>
+  <td colspan="1">59,792,392</td>
+  <td colspan="1">152</td>
+  <td colspan="1" rowspan="2">~ 3 minutes</td>
+  <td colspan="1" rowspan="2">~ 68 GB</td>
+  <td colspan="1" rowspan="2">~ 0.1 hours</td>
+  <td colspan="1" rowspan="2">~ 3 GB</td>
+  <td colspan="1" rowspan="2">~ 0.8 minutes</td>
+  <td colspan="1" rowspan="2">~ 0.6 GB</td>
+  <td colspan="1" rowspan="2">~ 0.3 hours</td>
+  <td colspan="1" rowspan="2">~ 5 GB</td>
+  <td colspan="1" rowspan="2">8</td>
+ </tr>
+ <tr>
+  <td colspan="1"><strong>medium_2.fastq</strong></td>
+  <td colspan="1">786,742</td>
+  <td colspan="1">59,792,392</td>
+  <td colspan="1">152</td>
+ </tr>
+ <tr>
+  <td colspan="1"><strong>large_1.fastq</strong></td>
+  <td colspan="1">10,174,715</td>
+  <td colspan="1">1,027,646,215</td>
+  <td colspan="1">3,376</td>
+  <td colspan="1" rowspan="2">~ 58 minutes</td>
+  <td colspan="1" rowspan="2">~ 80 GB</td>
+  <td colspan="1" rowspan="2">~ 5 hours</td>
+  <td colspan="1" rowspan="2">~ 30 GB</td>
+  <td colspan="1" rowspan="2">~ 35 minutes</td>
+  <td colspan="1" rowspan="2">~ 8 GB</td>
+  <td colspan="1" rowspan="2">~ 13 hours</td>
+  <td colspan="1" rowspan="2">~ 30 GB</td>
+  <td colspan="1" rowspan="2">8</td>
+ </tr>
+ <tr>
+  <td colspan="1"><strong>large_2.fastq</strong></td>
+  <td colspan="1">10,174,715</td>
+  <td colspan="1">1,027,646,215</td>
+  <td colspan="1">3,376</td>
+ </tr>
+ </tbody>
+ </table>
\ No newline at end of file
diff --git a/static/html/velvet.html b/static/html/velvet.html
new file mode 100644
index 00000000..b8edb9e9
--- /dev/null
+++ b/static/html/velvet.html
@@ -0,0 +1,77 @@
+ <table style="font-size: small">
+  <colgroup>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+   <col style="width: 6.80757%;"/>
+  </colgroup>
+ <tbody>
+ <tr style="font-size: x-small">
+  <th></th>
+  <th>total # of sequences</th>
+  <th>total # of bases</th>
+  <th>total size in MB</th>
+  <th>velveth used time</th>
+  <th>velveth used memory</th>
+  <th>velvetg used time</th>
+  <th>velvetg used memory</th>
+  <th># of used CPUs</th>
+ </tr>
+
+ <tr>
+  <td colspan="1"><strong>small_1.fastq</strong></td>
+  <td colspan="1">50,121</td>
+  <td colspan="1">2,506,050</td>
+  <td colspan="1">8.010</td>
+  <td colspan="1" rowspan="2">~ 0.02 minutes</td>
+  <td colspan="1" rowspan="2">~ 0.3 GB</td>
+  <td colspan="1" rowspan="2">~ 0.08 minutes</td>
+  <td colspan="1" rowspan="2">~ 0.2 GB</td>
+  <td colspan="1" rowspan="2">8</td>
+ </tr>
+ <tr>
+  <td colspan="1"><strong>small_2.fastq</strong></td>
+  <td colspan="1">50,121</td>
+  <td colspan="1">2,506,050</td>
+  <td colspan="1">8.010</td>
+ </tr>
+ <tr>
+  <td colspan="1"><strong>medium_1.fastq</strong></td>
+  <td colspan="1">786,742</td>
+  <td colspan="1">59,792,392</td>
+  <td colspan="1">152</td>
+  <td colspan="1" rowspan="2">~ 0.4 minutes</td>
+  <td colspan="1" rowspan="2">~ 1.5 GB</td>
+  <td colspan="1" rowspan="2">~ 0.8 minutes</td>
+  <td colspan="1" rowspan="2">~ 0.9 GB</td>
+  <td colspan="1" rowspan="2">8</td>
+ </tr>
+ <tr>
+  <td colspan="1"><strong>medium_2.fastq</strong></td>
+  <td colspan="1">786,742</td>
+  <td colspan="1">59,792,392</td>
+  <td colspan="1">152</td>
+ </tr>
+ <tr>
+  <td colspan="1"><strong>large_1.fastq</strong></td>
+  <td colspan="1">10,174,715</td>
+  <td colspan="1">1,027,646,215</td>
+  <td colspan="1">3,376</td>
+  <td colspan="1" rowspan="2">~ 7 minutes</td>
+  <td colspan="1" rowspan="2">~ 23 GB</td>
+  <td colspan="1" rowspan="2">~ 45 minutes</td>
+  <td colspan="1" rowspan="2">~ 51 GB</td>
+  <td colspan="1" rowspan="2">8</td>
+ </tr>
+ <tr>
+  <td colspan="1"><strong>large_2.fastq</strong></td>
+  <td colspan="1">10,174,715</td>
+  <td colspan="1">1,027,646,215</td>
+  <td colspan="1">3,376</td>
+ </tr>
+ </tbody>
+ </table>
\ No newline at end of file
-- 
GitLab