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aknecht2 created page: run times
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Jan 13, 2017
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aknecht2
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===========
*
Modify ExpressOrtho perl script to confirm to perl style standards.
*
Fetch bams or fastqs.
*
Specify file accession for control and experiment instead of experiment accession.
*
Add IDR for 2 replicates. Wait on response to figure out. (IDR / FDR?)
*
MongoDB read only database to clone. MongoDB helper scripts to update database. Need to create own db instance for saving results.
*
Don't need to save output files back to the database.
*
Generate report log at the end.
*
Remove Duplicates yes / no & duplicates.
*
Pooled & Pseudo replicates - pooled concatenate, pseudo shuffled (bam -> sam for plaintext). Configurable option.
*
Sphinx documentation at the same time.
*
Most conditions don't exist, exist for some.
*
Collapse Bed & Peak Collections
*
Only need one of score or signal_value
*
Need to derive read length from downloaded fastq
*
Randomly select experiment to control for peak calling, only use possible_controls
*
Only need human / mouse
*
DFBS keep everything same except one of condition OR cell type. (ignore for now)
*
Restrict to database, add genome collection.
2016-03-03
============
*
Run on Myc / Max -- wait on correct experiments to use!
*
Nothing else!
2016-03-10
==============
*
Don't use the assembly from the samples record, use the Grch assembly.
*
bowtie2 standard error continues quality measures!
*
for now focus on bowtie2
*
MXI1
*
Add aggregation pipelines to meta to extract relevant transcription factors
2016-03-17
============
*
Potentially do comparison paper of no SQL -> sql for bioinformatics. Run similar setup/design/analysis in SQL and see how it compares.
*
3 Papers (Biological paper, Pegasus paper, MongoDB paper)!?
2016-04-05
2016-12-13
============
*
Created dummy sample entries to run pipeline faster!
*
Look into better downloading tools to increase speed
*
Organize files by organism -> cell_type -> tf/hm -> (biorep1, biorep2, idr)
2016-
04-12
2016-
12-07
=============
*
Add gem
*
For DFBS: macs2, csaw, jmosaic
*
Human: CHD2 for k562 H1-hESC cells
2016-09-22
===============
*
macs2 paired end reads need to be run differently check accordingly.
*
convert/sort/idr for individual samples.
2016-09-15
=============
...
...
@@ -53,28 +36,47 @@ End Goals:
*
Merged replicates in workflow
*
Don't need GUI
2016-09-22
===============
*
macs2 paired end reads need to be run differently check accordingly.
*
convert/sort/idr for individual samples.
2016-12-07
2016-04-12
=============
*
Human: CHD2 for k562 H1-hESC cells
*
Add gem
*
For DFBS: macs2, csaw, jmosaic
2016-
12-13
2016-
04-05
============
*
Organize files by organism -> cell_type -> tf/hm -> (biorep1, biorep2, idr)
*
Created dummy sample entries to run pipeline faster!
*
Look into better downloading tools to increase speed
2017-01-13
2016-03-17
============
*
Potentially do comparison paper of no SQL -> sql for bioinformatics. Run similar setup/design/analysis in SQL and see how it compares.
*
3 Papers (Biological paper, Pegasus paper, MongoDB paper)!?
2016-03-10
==============
*
Don't use the assembly from the samples record, use the Grch assembly.
*
bowtie2 standard error continues quality measures!
*
for now focus on bowtie2
*
MXI1
*
Add aggregation pipelines to meta to extract relevant transcription factors
2016-03-03
============
*
Run on Myc / Max -- wait on correct experiments to use!
*
Nothing else!
2016-02-25
===========
*
Modify ExpressOrtho perl script to confirm to perl style standards.
*
Fetch bams or fastqs.
*
Specify file accession for control and experiment instead of experiment accession.
*
Add IDR for 2 replicates. Wait on response to figure out. (IDR / FDR?)
*
MongoDB read only database to clone. MongoDB helper scripts to update database. Need to create own db instance for saving results.
*
Don't need to save output files back to the database.
*
Generate report log at the end.
*
Remove Duplicates yes / no & duplicates.
*
Pooled & Pseudo replicates - pooled concatenate, pseudo shuffled (bam -> sam for plaintext). Configurable option.
*
Sphinx documentation at the same time.
*
Most conditions don't exist, exist for some.
*
Collapse Bed & Peak Collections
*
Only need one of score or signal_value
*
Need to derive read length from downloaded fastq
*
Randomly select experiment to control for peak calling, only use possible_controls
*
Only need human / mouse
*
DFBS keep everything same except one of condition OR cell type. (ignore for now)
*
Restrict to database, add genome collection.