Finished resolving merge conflicts. There were a lot.

.gitignore

@@ -9,5 +9,3 @@ examples/all_files.list
 chipathlon/test/auth.yaml
 meta/*.json
 meta/data/*.json
-doc/source/_static
-doc/source/_templates

chipathlon/conf.py

@@ -37,11 +37,47 @@ peak_tools = [
     "gem",
     "peakranger",
     "ccat",
+    "music",
     "zerone",
     "hiddendomains",
     "pepr"
 ]
 
+executables = [
+    "bedtools",
+    "samtools",
+    "idr",
+    "picard",
+    "bwa",
+    "bowtie2",
+    "macs2",
+    "gem",
+    "peakranger",
+    "MUSIC",
+    "CCAT",
+    "PePr",
+    "hiddenDomains",
+    "zerone",
+    "run_spp_nodups",
+    "chip-job-cat-peak",
+    "chip-job-ccat-format-bed",
+    "chip-job-chr-convert",
+    "chip-job-save-result",
+    "chip-job-download-encode",
+    "chip-job-download-gridfs",
+    "chip-job-music",
+    "chip-job-peakranger-format",
+    "chip-job-sort-peak",
+    "chip-job-zcat-peak",
+    "chip-job-zerone-add-cols",
+    "chip-job-hd-add-cols"
+]
+
+# Java needs to have -Xmx specified...
+java_tools = [
+    "gem"
+]
+
 # Peak_type validation
 peak_types = {
     "spp": ["narrow", "broad"],
@@ -49,9 +85,10 @@ peak_types = {
     "gem": ["narrow"],
     "peakranger": ["narrow"],
     "ccat": ["broad"],
+    "music": ["narrow", "punctate", "broad"],
     "zerone": ["broad"],
     "hiddendomains": ["broad"],
-    "pepr": ["narrow", "broad"]
+    "pepr": ["narrow", "broad"],
 }
 
 # File extensions
@@ -62,6 +99,7 @@ file_extensions = {
     "sam": ["sam"],
     "bam": ["bam"],
     "bed": ["bed", "peak", "region", "narrowPeak", "broadPeak", "tagAlign", "narrowPeak.gz", "broadPeak.gz"],
+    "bin": ["bin"],
     "bwa_genome": ["amb", "ann", "bwt", "pac", "sa"],
     "bowtie2_genome": ["1.bt2", "2.bt2", "3.bt2", "4.bt2", "rev.1.bt2", "rev.2.bt2"],
     "quality": ["quality"],
@@ -114,7 +152,8 @@ resources = {
 argument_types = {
     "argument": ["string", "numeric"],
     "file": ["file", "rawfile", "stdout", "stderr"],
-    "list": ["list"]
+    "list": ["file_list", "argument_list"],
+    "folder": ["folder", "rawfolder"]
 }
 
 # Defines information about arguments
@@ -125,21 +164,21 @@ argument_keys = {
 
 # workflow_job keys
 job_keys = {
-    "required": ["inputs", "additional_inputs", "outputs", "command", "arguments"] + resources.keys(),
+    "required": ["inputs", "outputs", "command", "arguments"] + resources.keys(),
     "optional": []
 }
 
+job_inout_keys = {
+    "required": ["type"],
+    "optional": ["file_type"]
+}
+
 # param keys
 param_keys = {
     "required": [],
     "optional": ["arguments"] + resources.keys()
 }
 
-file_list_keys = {
-    "required": ["name", "type"],
-    "optional": ["file_type"]
-}
-
 # workflow order
 workflow = ["align", "remove_duplicates", "peak_calling"]
 
@@ -154,3 +193,12 @@ genomes = {
         "additional_files": file_extensions["bowtie2_genome"]
     }
 }
+
+config_file = {
+    "required_keys": [
+        "chipathlon_bin", "idr_bin", "pegasus_home", "email"
+    ],
+    "optional_keys": [
+        "arch", "os"
+    ]
+}

chipathlon/db.py

@@ -6,10 +6,25 @@ import traceback
 import os
 import itertools
 import time
+import collections
 import chipathlon.conf
 from pprint import pprint
 import hashlib
-
+from chipathlon.utils import progress
+import bson
+
+def download_from_gridfs(host, gridfs_id, local_path, username=None, password=None, retries=3, overwrite=True, checkmd5=False):
+    mdb = chipathlon.db.MongoDB(host, username, password)
+    if not os.path.isfile(local_path) or overwrite:
+        for i in range(0, retries):
+            print "Attempt #%s, downloading file with ID '%s' to '%s'" % (i + 1, gridfs_id, local_path)
+            if mdb.fetch_from_gridfs(bson.objectid.ObjectId(gridfs_id), localpath, checkmd5):
+                return True
+            else:
+                print "Download attempt #%s from GridFS failed, retrying..." % (i + 1)
+    else:
+         print "File already exists, skipping download.\n"
+    return False
 
 class MongoDB(object):
     """
@@ -28,29 +43,30 @@ class MongoDB(object):
     operations much easier.
     """
 
-    def __init__(self, host, username, password, debug=False):
+    def __init__(self, host="localhost", username=None, password=None, debug=False):
         self.debug = debug
         self.host = host
         self.username = username
         self.password = password
         self.client = MongoClient(host)
         self.db = self.client.chipseq
-        self.cache = {}
-        try:
-            self.db.authenticate(username, password, mechanism="SCRAM-SHA-1")
-        except:
-            print("Could not authenticate to db %s!" % (host,))
-            print traceback.format_exc()
-            sys.exit(1)
+        self.cache = collections.defaultdict(dict)
+        if username and password:
+            try:
+                self.db.authenticate(username, password, mechanism="SCRAM-SHA-1")
+            except:
+                print("Could not authenticate to db %s!" % (host,))
+                print traceback.format_exc()
+                sys.exit(1)
         self.gfs = gridfs.GridFS(self.db)
         return
 
-    def add_cache(self, function, key, data):
+    def add_cache(self, accession, file_type, data):
         """
-        :param function: The function name
-        :type function: str
-        :param key: The key to add the cache entry under.
-        :type key: Any hashable
+        :param accession: The accession of the file to store.
+        :type accession: str
+        :param file_type: The type of file to store.
+        :type file_type: str
         :param data: The data to add to the cache.
         :type data: Object
 
@@ -60,23 +76,20 @@ class MongoDB(object):
         peak calling tools.  In these cases we don't want to request info
         from the database multiple times for the same data.
         """
-        if function not in self.cache:
-            self.cache[function] = {}
-        self.cache[function][key] = data
+        self.cache[accession][file_type] = data
         return
 
-    def get_cache(self, function, key):
+    def get_cache(self, accession, file_type):
         """
-        :param function: The function name
-        :type function: str
-        :param key: The key to get from the cache.
-        :type key: Any hashable
+        :param accession: The accession of the file to retrieve.
+        :type accession: str
+        :param file_type: The type of file to retrieve.
+        :type file_type: str
 
         Gets a data item from the internal cache.
         """
-        if function in self.cache:
-            if key in self.cache[function]:
-                return self.cache[function][key]
+        if accession in self.cache:
+            return self.cache[accession].get(file_type)
         return None
 
     def delete_result(self, result, genome):
@@ -321,6 +334,7 @@ class MongoDB(object):
         :type accession: string
         :param file_type: The file type of the target sample.
         :type file_type: string
+        :returns: A tuple (valid, msg, data)
 
         Gets the associated sample based on accession number and file_type.
         For loading input files for workflows the file_type should be fastq
@@ -330,7 +344,7 @@ class MongoDB(object):
         valid = True
         msg = ""
         data = {}
-        check_cache = self.get_cache("get_sample", accession)
+        check_cache = self.get_cache(accession, file_type)
         if check_cache is not None:
             msg = "Retrieved data from cache."
             data = check_cache
@@ -341,7 +355,7 @@ class MongoDB(object):
             })
             if cursor.count() == 1:
                 data = cursor.next()
-                self.add_cache("get_sample", accession, data)
+                self.add_cache(accession, file_type, data)
             else:
                 valid = False
                 msg = "Found %s files with accession: %s, file_type: %s. Should only be 1." % (
@@ -351,12 +365,49 @@ class MongoDB(object):
                 )
         return (valid, msg, data)
 
+    def clean_gfs(self):
+        """
+        This function finds all files stored in gridfs that are not currently
+        referenced by any result file and removes them.
+        A clean database is a happy database.
+        """
+        cursor = self.db.results.aggregate([
+            {
+                "$group": {
+                    "_id": 1,
+                    "valid_ids": {"$push": "$gridfs_id"}
+                }
+            }
+        ])
+        # Doc contains all our valid ids
+        id_doc = cursor.next()
+        # Find all fs.files documents
+        gfs_cursor = self.db.fs.files.find({
+            "_id": {
+                "$nin": id_doc["valid_ids"]
+            }
+        })
+        # Iterate through file, delete fs.chunks then fs.files
+        total_files = gfs_cursor.count()
+        print "Found %s unused gridfs files.  Preparing to delete...." % (total_files,)
+        for i, fs_file in enumerate(gfs_cursor):
+            progress(i, total_files)
+            self.db.fs.chunks.remove({
+                "files_id": fs_file["_id"]
+            })
+            self.db.fs.files.remove({
+                "_id": fs_file["_id"]
+            })
+        progress(total_files, total_files)
+        return
+
     def get_samples(self, experiment_accession, file_type):
         """
         :param experiment_accession: Accession number of the experiment to grab samples from.
         :type experiment_accession: str
         :param file_type: File type of samples to grab usually fastq or bam
         :type file_type: str
+        :returns: A tuple (valid, msg, data)
 
         Validates and gets samples for the given experiment.  Experiments must
         have control and signal samples of the provided file_type to be

chipathlon/generators/align_generator.py

@@ -2,27 +2,38 @@ from module_generator import ModuleGenerator
 from chipathlon.result import Result
 
 class AlignGenerator(ModuleGenerator):
-
-    def __init__(self, dax, master_jobs, master_files, mdb, workflow_module, workflow_jobs, base_path, debug=False):
-        """
-        :param dax: The workflow graph object
-        :type dax: Peagasus.DAX3.ADAG
-        :param master_jobs: The dictionary mapping job name -> pegasus job object.
-        :type master_jobs: dict
-        :param master_files: The dictionary mapping file name -> pegasus file object.
-        :type master_files: dict
-        :param mdb: A MongoDB database class for fetching sample meta data.
-        :type mdb: :py:class:chipathlon.db.MongoDB
-        :param workflow_module: The actual module being used.
-        :type workflow_module: chipathlon.workflow_module.WorkflowModule
-        :param workflow_jobs: Dictionary mapping workflow_job name -> workflow_job instance
-        :type workflow_jobs: dict
-        :param base_path: Base location of the workflow, used to save metadata files.
-        :type base_path: str
-        :param debug: If true, prints out params for each job & module.
-        :type debug: bool
-        """
-        super(AlignGenerator, self).__init__(dax, master_jobs, master_files, mdb, workflow_module, workflow_jobs, base_path, debug)
+    """
+    :param dax: The workflow graph object
+    :type dax: Peagasus.DAX3.ADAG
+    :param master_jobs: The dictionary mapping job name -> pegasus job object.
+    :type master_jobs: dict
+    :param master_files: The dictionary mapping file name -> pegasus file object.
+    :type master_files: dict
+    :param mdb: A MongoDB database class for fetching sample meta data.
+    :type mdb: :py:class:`~chipathlon.db.MongoDB`
+    :param workflow_module: The actual module being used.
+    :type workflow_module: `~chipathlon.workflow_module.WorkflowModule`
+    :param workflow_jobs: Dictionary mapping workflow_job name -> workflow_job instance
+    :type workflow_jobs: dict
+    :param base_path: Base location of the workflow, used to save metadata files.
+    :type base_path: str
+    :param save_db: Whether or not we want to save results to the database.
+        True by default.
+    :type save_db: bool
+    :param rewrite: Whether or not to rewrite existing files.  If true, it will
+        ignore files in Mongo and recreate them.  If false, it will download
+        files based on the latest available completed job.
+    :type rewrite: bool
+    :param debug: If true, prints out params for each job & module.
+    :type debug: bool
+    """
+
+    def __init__(self, dax, master_jobs, master_files, mdb, workflow_module,
+                workflow_jobs, base_path, save_db=True, rewrite=False, debug=False):
+        super(AlignGenerator, self).__init__(
+            dax, master_jobs, master_files, mdb, workflow_module, workflow_jobs,
+            base_path, save_db=save_db, rewrite=rewrite, debug=debug
+        )
         self.generate_calls = {
             "bwa": {
                 1: self._bwa_single,
@@ -40,7 +51,7 @@ class AlignGenerator(ModuleGenerator):
     def _bwa_init(self, run):
         """
         :param run: The run to load genome files for
-        :type run: :py:class:chipathlon.run.Run
+        :type run: :py:class:`~chipathlon.run.Run`
 
         Loads required genome files for bwa in to the dictionary structure
         expected by the actual workflow module.  Specifically, this maps:
@@ -51,16 +62,15 @@ class AlignGenerator(ModuleGenerator):
         """
         base_file = run.genome.get_base_file()
         inputs = {"ref_genome": base_file["name"]}
-        additional_inputs = {}
         for f in run.genome.get_additional_files():
             ext = f["name"].split(".")[-1]
-            additional_inputs["ref_genome.%s" % (ext,)] = f["name"]
-        return (inputs, additional_inputs)
+            inputs["ref_genome.%s" % (ext,)] = f["name"]
+        return inputs
 
     def _bowtie2_init(self, run):
         """
         :param run: The run to load genome files for
-        :type run: :py:class:chipathlon.run.Run
+        :type run: :py:class:`~chipathlon.run.Run`
 
         Loads required genome files for bowtie2 in to the dictionary structure
         expected by the actual workflow module.  Specifically, this maps:
@@ -72,81 +82,83 @@ class AlignGenerator(ModuleGenerator):
         """
         base_file = run.genome.get_base_file()
         additional_files = run.genome.get_additional_files()
-        inputs = {"ref_genome_prefix": run.genome.file_prefix}
-        additional_inputs = {"ref_genome": base_file["name"]}
+        inputs = {
+            "ref_genome_prefix": run.genome.file_prefix,
+            "ref_genome": base_file["name"]
+        }
         for f in run.genome.get_additional_files():
             ext = ".".join(f["name"].split(".")[-3 if "rev" in f["name"] else -2:])
-            additional_inputs["ref_genome.%s" % (ext,)] = f["name"]
-        return (inputs, additional_inputs)
+            inputs["ref_genome.%s" % (ext,)] = f["name"]
+        return inputs
 
     def _bwa_single(self, run, result):
         """
         :param run: The run to generate jobs for
-        :type run: :py:class:chipathlon.run.Run
+        :type run: :py:class:`~chipathlon.run.Run`
         :param result: The result to generate jobs for.
-        :type result: :py:class:chipathlon.result.Result
+        :type result: :py:class:`~chipathlon.result.Result`
 
         Creates inputs, additional_inputs, and outputs for bwa alignment
         jobs with single end reads.  Only the first file in prev_results will
         be processed
         """
         markers = {"tool": "bwa", "read_end": "single"}
-        inputs, additional_inputs = self._bwa_init(run)
+        inputs = self._bwa_init(run)
         prev_results = self.get_prev_results(run, result)
         inputs["download_1.fastq"] = prev_results[0].full_name
-        return (markers, inputs, additional_inputs)
+        return (markers, inputs)
 
     def _bwa_paired(self, run, result):
         """
         :param run: The run to generate jobs for
-        :type run: :py:class:chipathlon.run.Run
+        :type run: :py:class:`~chipathlon.run.Run`
         :param result: The result to generate jobs for.
-        :type result: :py:class:chipathlon.result.Result
+        :type result: :py:class:`~chipathlon.result.Result`
 
         Creates inputs, additional_inputs, and outputs for bwa alignment
         jobs with paired end reads.
         """
         markers = {"tool": "bwa", "read_end": "paired"}
-        inputs, additional_inputs = self._bwa_init(run)
+        inputs = self._bwa_init(run)
         prev_results = self.get_prev_results(run, result)
         inputs["download_1.fastq"] = prev_results[0].full_name
         inputs["download_2.fastq"] = prev_results[1].full_name
-        return (markers, inputs, additional_inputs)
+        return (markers, inputs)
 
     def _bowtie2_single(self, run, result):
         """
         :param run: The run to generate jobs for
-        :type run: :py:class:chipathlon.run.Run
+        :type run: :py:class:`~chipathlon.run.Run`
         :param result: The result to generate jobs for.
-        :type result: :py:class:chipathlon.result.Result
+        :type result: :py:class:`~chipathlon.result.Result`
 
         Creates inputs, additional_inputs, and outputs for bowtie2 alignment
         jobs with single end reads.  Only the first file in prev_results will
         be processed.
         """
         markers = {"tool": "bowtie2", "read_end": "single"}
-        inputs, additional_inputs = self._bowtie2_init(run)
+        inputs = self._bowtie2_init(run)
         prev_results = self.get_prev_results(run, result)
         inputs["download_1.fastq"] = prev_results[0].full_name
-        return (markers, inputs, additional_inputs)
+        return (markers, inputs)
 
 
     def _bowtie2_paired(self, run, result):
         """
         :param run: The run to generate jobs for
-        :type run: :py:class:chipathlon.run.Run
+        :type run: :py:class:`~chipathlon.run.Run`
         :param result: The result to generate jobs for.
-        :type result: :py:class:chipathlon.result.Result
+        :type result: :py:class:`~chipathlon.result.Result`
 
         Creates inputs, additional_inputs, and outputs for bowtie2 alignment
         jobs with paired end reads.
         """
         markers = {"tool": "bowtie2", "read_end": "paired"}
-        inputs, additional_inputs = self._bowtie2_init(run)
+        inputs = self._bowtie2_init(run)
         prev_results = self.get_prev_results(run, result)
         inputs["download_1.fastq"] = prev_results[0].full_name
         inputs["download_2.fastq"] = prev_results[1].full_name
-        return (markers, inputs, additional_inputs)
+        return (markers, inputs)
 
     def _find_pairs(self, sample_list):
         """
@@ -178,7 +190,7 @@ class AlignGenerator(ModuleGenerator):
     def create_final_results(self, run):
         """
         :param run: The target run to generate jobs for.
-        :type run: :py:class:chipathlon.run.Run
+        :type run: :py:class:`~chipathlon.run.Run`
         """
         control_samples = run.get_samples("control")
         signal_samples = run.get_samples("signal")
@@ -214,9 +226,9 @@ class AlignGenerator(ModuleGenerator):
     def find_prev_results(self, run, result):
         """
         :param run: The target run to generate jobs for.
-        :type run: :py:class:chipathlon.run.Run
+        :type run: :py:class:`~chipathlon.run.Run`
         :param result: The target result to create jobs for.
-        :type result: :py:class:chipathlon.result.Result
+        :type result: :py:class:`~chipathlon.result.Result`
         """
         download_samples = run.get_results("download", "encode.fastq.gz")
         prev_results = []
@@ -231,11 +243,11 @@ class AlignGenerator(ModuleGenerator):
     def parse_result(self, run, result):
         """
         :param run: The target run to generate jobs for.
-        :type run: :py:class:chipathlon.run.Run
+        :type run: :py:class:`~chipathlon.run.Run`
         :param result: The target result to create jobs for.
-        :type result: :py:class:chipathlon.result.Result
+        :type result: :py:class:`~chipathlon.result.Result`
         """
         prev_results = self.get_prev_results(run, result)
-        markers, inputs, additional_inputs = self.generate_calls[run.genome.tool][len(prev_results)](run, result)
+        markers, inputs = self.generate_calls[run.genome.tool][len(prev_results)](run, result)
         results = self.create_results(run, result)
-        return markers, inputs, additional_inputs, self.get_outputs(results)
+        return markers, inputs, self.get_outputs(results)

chipathlon/generators/idr_generator.py

 from module_generator import ModuleGenerator
 from chipathlon.result import Result
+import collections
 
 class IdrGenerator(ModuleGenerator):
+    """
+    :param dax: The workflow graph object
+    :type dax: Peagasus.DAX3.ADAG
+    :param master_jobs: The dictionary mapping job name -> pegasus job object.
+    :type master_jobs: dict
+    :param master_files: The dictionary mapping file name -> pegasus file object.
+    :type master_files: dict
+    :param mdb: A MongoDB database class for fetching sample meta data.
+    :type mdb: :py:class:`~chipathlon.db.MongoDB`
+    :param workflow_module: The actual module being used.
+    :type workflow_module: `~chipathlon.workflow_module.WorkflowModule`
+    :param workflow_jobs: Dictionary mapping workflow_job name -> workflow_job instance
+    :type workflow_jobs: dict
+    :param base_path: Base location of the workflow, used to save metadata files.
+    :type base_path: str
+    :param save_db: Whether or not we want to save results to the database.
+        True by default.
+    :type save_db: bool
+    :param rewrite: Whether or not to rewrite existing files.  If true, it will
+        ignore files in Mongo and recreate them.  If false, it will download
+        files based on the latest available completed job.
+    :type rewrite: bool
+    :param debug: If true, prints out params for each job & module.
+    :type debug: bool
+    """
 
-    def __init__(self, dax, master_jobs, master_files, mdb, workflow_module, workflow_jobs, base_path, debug=False):
-        """
-        :param dax: The workflow graph object
-        :type dax: Peagasus.DAX3.ADAG
-        :param master_jobs: The dictionary mapping job name -> pegasus job object.
-        :type master_jobs: dict
-        :param master_files: The dictionary mapping file name -> pegasus file object.
-        :type master_files: dict
-        :param mdb: A MongoDB database class for fetching sample meta data.
-        :type mdb: :py:class:chipathlon.db.MongoDB
-        :param workflow_module: The actual module being used.
-        :type workflow_module: chipathlon.workflow_module.WorkflowModule
-        :param workflow_jobs: Dictionary mapping workflow_job name -> workflow_job instance
-        :type workflow_jobs: dict
-        :param base_path: Base location of the workflow, used to save metadata files.
-        :type base_path: str
-        :param debug: If true, prints out params for each job & module.
-        :type debug: bool
-        """
-        super(IdrGenerator, self).__init__(dax, master_jobs, master_files, mdb, workflow_module, workflow_jobs, base_path, debug)
+    def __init__(self, dax, master_jobs, master_files, mdb, workflow_module,
+                workflow_jobs, base_path, save_db=True, rewrite=False, debug=False):
+        super(IdrGenerator, self).__init__(
+            dax, master_jobs, master_files, mdb, workflow_module, workflow_jobs,
+            base_path, save_db=save_db, rewrite=rewrite, debug=debug
+        )
         self.module_name = "idr"
         self.result_dict = {}
-        self.output_files = {
-            "peakranger": ["region_sorted.bed", "summit_sorted.bed"],
-            "ccat": ["region_sorted.bed", "peak_sorted.bed"],
-            "gem": ["results_GEM_sorted.bed", "results_GPS_sorted.bed"],
-            "spp": ["results_sorted.bed"],
-            "zerone": ["results_sorted_final.bed"],
-            "hiddendomains": ["results_final.bed"],
-            "macs2": ["results_sorted.bed"],
-            "pepr": ["pepr_result.bed"]
-        }
+        self.output_files = collections.defaultdict(dict)
+
+        self.output_files["peakranger"]["narrow"] = ["region_sorted.bed", "summit_sorted.bed"]
+        self.output_files["ccat"]["broad"] = ["region_sorted.bed", "peak_sorted.bed"]
+        self.output_files["gem"]["narrow"] = ["results_GEM_sorted.bed", "results_GPS_sorted.bed"]
+        self.output_files["spp"]["narrow"] = self.output_files["spp"]["broad"] = ["results_sorted.bed"]
+        self.output_files["macs2"]["narrow"] = self.output_files["macs2"]["broad"] = ["results_sorted.bed"]
+        self.output_files["music"]["narrow"] = ["sorted_scale_%s_all.bed" % (i,) for i in [129, 194, 291]]
+        self.output_files["music"]["punctate"] = ["sorted_scale_%s_all.bed" % (i,) for i in [129, 194, 291, 437, 656, 985, 1477, 2216]]
+        self.output_files["music"]["broad"] = ["sorted_scale_%s_all.bed" % (i,) for i in [1459, 2189, 3284, 4926, 7389, 11084, 16626]]
+        self.output_files["zerone"]["broad"] = ["results_sorted.bed"]
+        self.output_files["hiddendomains"]["broad"] = ["results_sorted.bed"]
+        self.output_files["pepr"]["broad"] = ["results_sorted.bed"]
+        self.output_files["pepr"]["narrow"] = ["results_sorted.bed"]