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pipeline_dfci.py
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pipeline_dfci.py
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#!/usr/bin/python
#pipeline.py
samtoolsString = 'samtools'
bamliquidator_path = 'bamliquidator_batch'
pipelineFolder = '/ark/home/cl512/pipeline/' # need to set this to where this code is stored
fastqDelimiter = '::' #delimiter for pairs in fastqs
'''
The MIT License (MIT)
Copyright (c) 2013 Charles Lin
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
THE SOFTWARE.
'''
#module of functions/code/structures from the myc project that has now been
#addapted for general use
#==========================================================================
#==========================DEPENDENCIES====================================
#==========================================================================
import sys
#sys.path.append('/mnt/d0-0/share/bradnerlab/src/cl512/pipeline/')
print('\nUsing following version of python:\n')
print(sys.version)
print('\n\n')
from utils import *
import datetime
import subprocess
import time
import re
import random
import string
import numpy
from collections import defaultdict
#==========================================================================
#===========================TABLE OF CONTENTS==============================
#==========================================================================
#CODE IN THIS MODULE IS SPLIT UP INTO SEVERAL SECTIONS
#-------------------------------------------------------------------------#
# #
# FORMATTING AND DATA INPUT #
# #
#-------------------------------------------------------------------------#
#FORMATTING FOLDERS
#formatFolder(folderName,create=False)
#FORMATTING THE MASTER DATA TABLE
#formatDataTable(dataFile):
#FORMATTING FUNCTIONS
#makePipelineTable(sampleTableFile,dirPath,bamPath,outputFile,overwrite=False):
#LOADING THE MASTER DATA TABLE
#def loadDataTable(dataFile):
#def writeDataTable(dataDict,outFile):
#def summary(dataFile,outputFile=''):
#def makeBamTable(dataFile,output):
#-------------------------------------------------------------------------#
# #
# TONY DATABASE TOOLS #
# #
#-------------------------------------------------------------------------#
#INTERACTING WITH TONY
#getTONYInfo(uniqueID,column =''):
#-------------------------------------------------------------------------#
# #
# ALIGNMENT #
# #
#-------------------------------------------------------------------------#
#CALLING BOWTIE TO MAP DATA
#def makeBowtieBashJobs(pipelineFile,namesList = [],launch=True,overwrite=False):
#def callBowtie(dataFile,dataList = [],overwrite = False):
#GETTING MAPPING STATS
#def bowtieStats(dataFile,namesList=[]):
#MERGING BAMS
#def mergeBams(dataFile,mergedName,namesList,color='',background =''):
#FILTERING BAMS
#def filterBams(dataFile,namesList = [],tempFolder = '/raider/BOWTIE_TEMP/',bamFolder='/grail/bam/filtered/'):
#-------------------------------------------------------------------------#
# #
# PEAK FINDING #
# #
#-------------------------------------------------------------------------#
#CALLING MACS
#def callMacsQsub(dataFile,macsFolder,namesList = [],overwrite=False,pvalue='1e-9'):
#def callMacs(dataFile,macsFolder,namesList = [],overwrite=False,pvalue='1e-9',useBackground =True):
#def callMacs2(dataFile,macsFolder,namesList = [],broad=True,noBackground = False,pairedEnd = False,overwrite=False,pvalue='1e-9'):
#FORMATTING MACS OUTPUT
#def formatMacsOutput(dataFile,macsFolder,macsEnrichedFolder,wiggleFolder,wigLink='',useBackground=True):
#-------------------------------------------------------------------------#
# #
# GFF TOOLS #
# #
#-------------------------------------------------------------------------#
#MAKING GFFS OF TSS REGIONS
#def makeGeneGFFs(annotFile,gffFolder,species='HG18'):
#MAKING GFFS OF CHROMS
#def makeChromGFFs(chromLengthFile,gffFolder,chromList = [],genome='HG18',binSize = 100000,singleGFF = True):
#MAKING GFFS OF ENHANCER REGIONS
#def makeEnhancerGFFs(dataFile,gffName,namesList,annotFile,gffFolder,enrichedFolder,window=2000,macs=True):
#MAKING GFFS OF ENRICHED REGIONS
#def makeEnrichedGFFs(dataFile,namesList,gffFolder,enrichedFolder,macs=True,window=0):
#MAKING GFFS OF PROMOTER REGIONS
#def makePromoterGFF(dataFile,annotFile,promoterFactor,enrichedFolder,gffFolder,window=0,transcribedGeneFile=''):
#-------------------------------------------------------------------------#
# #
# MAPPING TOOLS #
# #
#-------------------------------------------------------------------------#
#MAP ENRICHED REGIONS TO GFF
#def mapEnrichedToGFF(dataFile,setName,gffList,cellTypeList,enrichedFolder,mappedFolder,macs=True,namesList=[],useBackground=True):
#MAPPING BAMS TO GFFS
#def mapBams(dataFile,cellTypeList,gffList,mappedFolder,nBin = 200,overWrite =False,nameList = []):
#def mapBamsQsub(dataFile,cellTypeList,gffList,mappedFolder,nBin = 200,overWrite =False,nameList = []):
#def mapBamsBatch(dataFile,gffList,mappedFolder,overWrite =False,namesList = [],extension=200)
#FORMATTING MAPPING SIGNAL
#def makeSignalTable(dataFile,gffFile,mappedFolder,namesList = [],medianNorm=False,output =''):
#MAKING GFF LISTS
#def makeGFFListFile(mappedEnrichedFile,setList,output,annotFile=''):
#-------------------------------------------------------------------------#
# #
# PLOTTING TOOLS #
# #
#-------------------------------------------------------------------------#
#PLOTTING INDIVIDUAL GENES
#def callGenePlot(dataFile,geneID,plotName,annotFile,namesList,outputFolder,region='TXN',yScale = 'UNIFORM'):
#BATCH PLOTTING REGIONS
#def callBatchPlot(dataFile,inputFile,plotName,outputFolder,namesList=[],uniform=True):
#-------------------------------------------------------------------------#
# #
# META TOOLS #
# #
#-------------------------------------------------------------------------#
#MAKING META GFFS OF TXN REGIONS
#def makeMetaGFFs(annotFile,gffFolder,genome,geneListFile =''):
#MAPPING BAMS FOR METAS
#def mapMetaBams(dataFile,metaName,gffList,cellTypeList,metaFolder,nameList= [],overwrite=False):
#FINISHING METAS
#def finishMetas(metaFolder,settingsFileList=[]):
#MAKING ORDERED HEATMAPS
#def callHeatPlotOrdered(dataFile,gffFile,namesList,orderByName,geneListFile,outputFolder,mappedFolder,relative=False):
#-------------------------------------------------------------------------#
# #
# ROSE TOOLS #
# #
#-------------------------------------------------------------------------#
#CALLING ROSE
#def callRose(dataFile,macsEnrichedFolder,parentFolder,namesList=[],extraMap = [],inputFile='',tss=2500,stitch=12500,bashFileName ='',mask=''):
#def callRose2(dataFile,macsEnrichedFolder,parentFolder,namesList=[],extraMap = [],inputFile='',tss=2500,stitch='',bashFileName ='',mask=''):
#-------------------------------------------------------------------------#
# #
# EXPRESSION TOOLS #
# #
#-------------------------------------------------------------------------#
#MAKING EXPRESSION TABLES
#def makeCuffTable(dataFile,analysisName,gtfFile,cufflinksFolder,groupList=[],bashFileName = ''):
#-------------------------------------------------------------------------#
# #
# GECKO TOOLS #
# #
#-------------------------------------------------------------------------#
#============================================================================================================
#============================================================================================================
#============================================================================================================
#-------------------------------------------------------------------------#
# #
# FORMATTING AND DATA INPUT #
# #
#-------------------------------------------------------------------------#
#==========================================================================
#==========================DATA TABLE FORMAT===============================
#==========================================================================
#the master data table
#everything starts with this
#format is as follows
#FILE_PATH UNIQUE_ID NAME BACKGROUND ENRICHED_REGION ENRICHED_MACS COLOR
#FILE_PATH = FOLDER WHERE THE BAM FILE LIVES
#UNIQUE_ID = TONY UNIQUE ID
#GENOME = GENOME USED. MM9, HG18 ARE SUPPORTED
#NAME = IDENTIFIER OF THE DATASET NEEDS TO BE UNIQUE
#BACKGROUND = NAME OF THE BACKGROUND DATASET
#ENRICHED_REGION = NAME OF THE ERROR MODEL ENRICHED REGION OUTPUT
#ENRICHED_MACS = NAME OF THE MACS PEAKS BED FILE
#COLOR = COMMA SEPARATED RGB CODE
#==========================================================================
#===================FORMATTING FOLDERS=====================================
#==========================================================================
def formatFolder(folderName,create=False):
'''
makes sure a folder exists and if not makes it
returns a bool for folder
'''
if folderName[-1] != '/':
folderName +='/'
try:
foo = os.listdir(folderName)
return folderName
except OSError:
print('folder %s does not exist' % (folderName))
if create:
os.system('mkdir %s' % (folderName))
return folderName
else:
return False
#==========================================================================
#===================FORMATTING THE MASTER DATA TABLE=======================
#==========================================================================
def formatDataTable(dataFile):
'''
formats the dataFile and rewrites.
first 3 columns are required for every line.
if they aren't there the line is deleted
'''
print('reformatting data table')
dataTable = parseTable(dataFile,'\t')
newDataTable = [['FILE_PATH','UNIQUE_ID','GENOME','NAME','BACKGROUND','ENRICHED_REGION','ENRICHED_MACS','COLOR','FASTQ_FILE']]
#first check to make sure the table is formatted correctly
for line in dataTable[1:]:
if len(line) < 3:
continue
#this spots header lines that may be out of place
if line[0] == 'FILE_PATH':
continue
#check if it at least has the first 3 columns filled in
if len(line[0]) == 0 or len(line[1]) == 0 or len(line[2]) == 0:
print('ERROR required fields missing in line')
print(line)
#if the first three are filled in, check to make sure there are 8 columns
else:
if len(line) > 3 and len(line) < 9:
newLine = line + (9-len(line))*['']
newDataTable.append(newLine)
elif len(line) >= 9:
newLine = line[0:9]
newDataTable.append(newLine)
#lower case all of the genomes
#make the color 0,0,0 for blank lines and strip out any " marks
for i in range(1,len(newDataTable)):
newDataTable[i][2] = string.lower(newDataTable[i][2])
color = newDataTable[i][7]
if len(color) == 0:
newDataTable[i][7] = '0,0,0'
unParseTable(newDataTable,dataFile,'\t')
return newDataTable
#========================================================================
#=======================FORAMTTING FUNCTIONS=============================
#========================================================================
def makePipelineTable(sampleTableFile,dirPath,bamPath,outputFile,overwrite=False):
'''
makes a standard pipeline table in the same directory as the sample Table File
which should be the project directory file
uses a standard WI annotation xls
'''
if sampleTableFile.split('.')[-1] == 'xls':
sampleTable = parseTable(sampleTableFile,'\t',excel=True)
else:
sampleTable = parseTable(sampleTableFile,'\t',excel=False)
#check if the outputfile exists
#if it does, append
if overwrite:
pipelineTable = [['FILE_PATH','UNIQUE_ID','GENOME','NAME','BACKGROUND','ENRICHED_REGIONS','ENRICHED_MACS','COLOR','FASTQ_FILE']]
else:
try:
pipelineTable = parseTable(outputFile,'\t')
except IOError:
pipelineTable = [['FILE_PATH','UNIQUE_ID','GENOME','NAME','BACKGROUND','ENRICHED_REGIONS','ENRICHED_MACS','COLOR','FASTQ_FILE']]
for line in sampleTable[1:]:
if line[0] == '':
break
uniqueID = "%s_%s" % (line[8],line[4])
genome = line[14]
name = line[4]
cellLine = string.lower(line[4].split('_')[0])
filePath = "%s%s/%s/" % (bamPath,genome,cellLine)
barcode = line[5].split('-')[1]
fastqFile = "%s%s-s_%s_1_sequence.txt.tar.gz" % (dirPath,barcode,line[0])
if name.count('WCE') == 0:
newLine = [filePath,uniqueID,genome,name,'NONE','NONE','','0,0,0',fastqFile]
background = line[3]
if len(background) == 0:
newLine = [filePath,uniqueID,genome,name,'','','','0,0,0',fastqFile]
else:
newLine = [filePath,uniqueID,genome,name,line[3],'','','0,0,0',fastqFile]
pipelineTable.append(newLine)
unParseTable(pipelineTable,outputFile,'\t')
#==========================================================================
#===================LOADING THE MASTER DATA TABLE==========================
#==========================================================================
def loadDataTable(dataFile):
if type(dataFile) == str:
dataTable = parseTable(dataFile,'\t')
else:
dataTable = list(dataFile)
#first check to make sure the table is formatted correctly
for line in dataTable:
#print(line)
if len(line) != 9:
print('this line did not pass')
print(line)
dataTable = formatDataTable(dataFile)
break
dataDict = {}
for line in dataTable[1:]:
dataDict[line[3]] = {}
dataDict[line[3]]['folder'] = formatFolder(line[0],False)
dataDict[line[3]]['uniqueID'] = line[1]
dataDict[line[3]]['genome']=string.upper(line[2])
genome = line[2]
dataDict[line[3]]['sam'] = line[0]+line[1]+'.'+genome+'.bwt.sam'
dataDict[line[3]]['ylf'] = line[0]+line[1]+'.'+genome+'.bwt.ylf'
dataDict[line[3]]['enriched'] = line[5]
dataDict[line[3]]['background'] = line[4]
dataDict[line[3]]['enrichedMacs'] = line[6]
dataDict[line[3]]['color'] = line[7]
dataDict[line[3]]['fastq']=line[8]
#figure out which bam convention we are using
#default will be new convention
#look in the bamFolder for all bams that might fit the bill
bamFolder = "%s" % (line[0])
bamFileList = [x for x in os.listdir(bamFolder) if len(x) > 0 and x[0] != '.']
bamFileCandidates = [x for x in bamFileList if x.count(line[1]) == 1 and x.split('.')[-1] =='bam' and x.count('bai') ==0]
if len(bamFileCandidates) == 0:
print("UNABLE TO FIND A BAM FILE IN %s WITH UNIQUE ID %s" % (bamFolder,line[1]))
fullBamPath = ''
elif len(bamFileCandidates) > 1:
print("MUTLIPLE BAM FILES IN %s WITH UNIQUE ID %s. NO BAM ASISGNED" % (bamFolder,line[1]))
fullBamPath = ''
else:
bamFile = bamFileCandidates[0]
fullBamPath = '%s%s' % (bamFolder,bamFile)
fullBaiPath = fullBamPath + '.bai'
if len(fullBamPath) > 0:
try:
bam = open(fullBamPath,'r')
bam.close()
except IOError:
print("ERROR: BAM FILE %s DOES NOT EXIST" % (fullBamPath))
fullBamPath = ''
try:
bai = open(fullBaiPath,'r')
bai.close()
except IOError:
print("ERROR: BAM FILE %s DOES NOT HAVE BAI INDEX" % (fullBamPath))
fullBamPath = ''
dataDict[line[3]]['bam'] = fullBamPath
return dataDict
def writeDataTable(dataDict,dataFile):
'''
writes a dataDict to a dataFile
'''
newDataTable = [['FILE_PATH','UNIQUE_ID','GENOME','NAME','BACKGROUND','ENRICHED_REGION','ENRICHED_MACS','COLOR','FASTQ_FILE']]
namesList = dataDict.keys()
namesList.sort()
for name in namesList:
file_path = dataDict[name]['folder']
uniqueID = dataDict[name]['uniqueID']
genome = dataDict[name]['genome']
background = dataDict[name]['background']
enriched = dataDict[name]['enriched']
macsEnriched = dataDict[name]['enrichedMacs']
color = dataDict[name]['color']
fastq = dataDict[name]['fastq']
newLine = [file_path,uniqueID,genome,name,background,enriched,macsEnriched,color,fastq]
newDataTable.append(newLine)
unParseTable(newDataTable,dataFile,'\t')
def summary(dataFile,outputFile=''):
'''
gives a summary of the data and its completeness
'''
dataDict = loadDataTable(dataFile)
dataList = dataDict.keys()
dataList.sort()
output= []
for name in dataList:
uniqueID = dataDict[name]['uniqueID']
#cmd = 'perl /nfs/young_ata/scripts/getTONY_info.pl -i %s -f 2' % (uniqueID)
#tonyQuery = os.popen(cmd)
#tonyName = tonyQuery.read().rstrip()
#print('dataset name\t%s\tcorresponds to tony name\t%s' % (name,tonyName))
#output.append('dataset name\t%s\tcorresponds to tony name\t%s' % (name,tonyName))
#for each dataset
for name in dataList:
#check for the bam
try:
bam = open(dataDict[name]['bam'],'r')
hasBam = True
except IOError:
hasBam = False
#check for ylf
try:
ylf = open(dataDict[name]['ylf'],'r')
hasYlf = True
except IOError:
hasYlf = False
if hasBam == False:
print('No .bam file for %s' % (name))
output.append('No .bam file for %s' % (name))
if hasYlf == False:
print('No .ylf file for %s' % (name))
output.append('No .ylf file for %s' % (name))
if outputFile:
unParseTable(output,outputFile,'')
def makeBamTable(dataFile,output):
'''
converts a data table into a bam table for jenkins
schema = [['SOURCE','CELL_TYPE','GENOME','BAMFILE']]
'''
#sources are manually curated here in this sourceDict
sourceDict = {'MM1S':'Multiple Myeloma',
'KMS11':'Multiple Myeloma',
'LY1': 'Diffuse large B-cell lymphoma',
'LY3': 'Diffuse large B-cell lymphoma',
'LY4': 'Diffuse large B-cell lymphoma',
'LY18': 'Diffuse large B-cell lymphoma',
'K422': 'Diffuse large B-cell lymphoma',
'PFEIFFER':'Diffuse large B-cell lymphoma',
'DHL6':'Diffuse large B-cell lymphoma',
'HBL1':'Diffuse large B-cell lymphoma',
'TOLEDO':'Diffuse large B-cell lymphoma',
'P397':'Diffuse large B-cell lymphoma',
'P286':'Diffuse large B-cell lymphoma',
'P14A':'Lymph node',
'P107A':'Tonsil',
'P448': 'Diffuse large B-cell lymphoma',
'P265': 'Diffuse large B-cell lymphoma',
'CD19': 'B-cell',
'PROB': 'Pro B-cell',
'SKNAS': 'Neuroblastoma',
'BE2C': 'Neuroblastoma',
'HSC': 'Hematopoeitic stem cell',
'EC': 'Human umbilical cord endothelial cell',
'3T3L1': 'Fibroblast',
'KBM7': 'Haploid Chronic Myeloid Leukemia',
'P493-6': 'Burkitt Lymphoma',
'NUT797':'Nut midline carcinoma',
'MAC': 'Macrophage',
'MMP1': 'Primary multiple myeloma',
'MEF': 'Mouse embryonic fibroblast',
}
dataDict= loadDataTable(dataFile)
namesList = dataDict.keys()
namesList.sort()
#bamTable = [['SOURCE','CELL_TYPE','GENOME','BAMFILE']]
bamTable =[]
for name in namesList:
cellType = name.split('_')[0]
if sourceDict.has_key(cellType):
source = sourceDict[cellType]
else:
source = 'Unknown'
genome = dataDict[name]['genome']
bamFile = dataDict[name]['bam']
bamTable.append([genome,source,cellType,name,bamFile])
#sort by source
sourceOrder = order([x[1] for x in bamTable])
sortedTable = [['GENOME','SOURCE','CELL_TYPE','NAME','BAMFILE']] + [bamTable[i] for i in sourceOrder]
unParseTable(sortedTable,output,'\t')
#mapping the data
#-------------------------------------------------------------------------#
# #
# TONY DATABASE TOOLS #
# #
#-------------------------------------------------------------------------#
#==========================================================================
#=======================INTERACTING WITH TONY==============================
#==========================================================================
def getTONYInfo(uniqueID,column =''):
'''
returns a TONY db column parameter
'''
column = str(column)
if len(column) == 0:
cmd = 'perl /ark/tony/admin/getDB_Data.pl -h'
os.system(cmd)
return
else:
cmd = 'perl /ark/tony/admin/getDB_Data.pl -i %s -c %s -o TAB' % (uniqueID,column)
output = subprocess.Popen(cmd,stdin = subprocess.PIPE,stderr = subprocess.PIPE,stdout = subprocess.PIPE,shell = True)
outputLines = output.stdout.readlines()
output.stdout.close()
if outputLines.count('not a valid ID') == 1:
print("NO RECORD OF %s" % (uniqueID))
return False
else:
return outputLines[1].rstrip().split('\t')[-1]
#-------------------------------------------------------------------------#
# #
# ALIGNMENT #
# #
#-------------------------------------------------------------------------#
#==========================================================================
#===================CALLING BOWTIE TO MAP DATA=============================
#==========================================================================
def makeBowtieBashJobs(dataFile,namesList = [],launch=True,overwrite=False,paramString=''):
'''
makes a mapping bash script and launches
'''
#hardCoded index locations
dataDict = loadDataTable(dataFile)
#print(dataDict)
if len(namesList) == 0:
namesList = dataDict.keys()
namesList.sort()
for name in namesList:
fastqFile = dataDict[name]['fastq']
#paired end files will be comma separated
if fastqFile.count(fastqDelimiter) == 1:
pairedEnd = True
elif fastqFile.count(fastqDelimiter) > 1:
print("UNABLE TO PARSE OUT FASTQ FILES FOR %s" % (name))
else:
pairedEnd = False
genome = dataDict[name]['genome']
#get the unique ID
uniqueID = dataDict[name]['uniqueID']
#see if the dataset is already entered into TONY
#get the parent tony folder
tonyFolder = getTONYInfo(uniqueID,column = 30)
print(tonyFolder)
if tonyFolder:
outputFolder = tonyFolder
else:
outputFolder = dataDict[name]['folder']
outputFolder = formatFolder(outputFolder,create=True)
#setting up the folder for linking
linkFolder = '/grail/bam/%s/' % (string.lower(genome))
#decide whether or not to run
try:
foo = open(dataDict[name]['bam'],'r')
if not overwrite:
print('BAM file already exists for %s. OVERWRITE = FALSE' % (name))
sys.exit()
else:
run = True
except IOError:
print('no bam file found for %s, making mapping bash script' % (name))
run = True
if run:
cmd = "python /ark/home/cl512/pipeline/callBowtie2.py -f %s -g %s -u %s -o %s --link-folder %s" % (fastqFile,genome,uniqueID,outputFolder,linkFolder)
#add the param string
cmd += " --param '%s'" % (paramString)
if pairedEnd:
cmd += ' -p'
print(cmd)
os.system(cmd)
if launch:
time.sleep(1)
cmd = "bash %s%s_bwt2.sh &" % (outputFolder,uniqueID)
os.system(cmd)
###
### DEPRECATED FUNCTION FROM TAK
###
# def callBowtie(dataFile,dataList = [],overwrite = False,pairedEnd = False):
# '''
# calls bowtie for the dataset names specified. if blank, calls everything
# '''
# dataDict = loadDataTable(dataFile)
# if len(dataList) == 0:
# dataList = dataDict.keys()
# for name in dataList:
# #make sure the output folder exists
# try:
# foo = os.listdir(dataDict[name]['folder'])
# except OSError:
# print('no output folder %s for dataset %s. Creating directory %s now.' % (dataDict[name]['folder'],name,dataDict[name]['folder']))
# os.system('mkdir %s' % (dataDict[name]['folder']))
# if string.upper(dataDict[name]['genome']) == 'HG18' or string.upper(dataDict[name]['genome']) == 'MM8':
# cmd = 'perl /nfs/young_ata/scripts/generateSAM_file.pl -R -G -c 4 -B -i %s -o %s' % (dataDict[name]['uniqueID'],dataDict[name]['folder'])
# elif string.upper(dataDict[name]['genome']) == 'RN5':
# cmd = 'perl /nfs/young_ata/CYL_code/generateSam_rat.pl -R -c 4 -B -i %s -o %s' % (dataDict[name]['uniqueID'],dataDict[name]['folder'])
# else:
# cmd = 'perl /nfs/young_ata/scripts/generateSAM_file.pl -R -c 4 -B -i %s -o %s' % (dataDict[name]['uniqueID'],dataDict[name]['folder'])
# #first check if the bam exists
# if overwrite:
# print(cmd)
# os.system(cmd)
# else:
# try:
# foo = open(dataDict[name]['bam'],'r')
# print('BAM file already exists for %s. OVERWRITE = FALSE' % (name))
# except IOError:
# print('no bam file found for %s, mapping now' % (name))
# print(cmd)
# os.system(cmd)
#==========================================================================
#===================GETTING MAPPING STATS==================================
#==========================================================================
def bowtieStats(dataFile,namesList=[]):
'''
gets stats from the bowtie out file for each bam
does not assume bowtie output format is always the same
'''
dataDict = loadDataTable(dataFile)
print('DATASET\t\tSEED LENGTH\tTOTAL READS (MILLIONS)\tALIGNED\tFAILED\tMULTI')
if len(namesList) == 0:
namesList= dataDict.keys()
for name in namesList:
readLength,readCount,alignedReads,failedReads,multiReads = False,False,False,False,False
bowtieOutFile = dataDict[name]['folder'] + dataDict[name]['uniqueID']+ '.bowtie.output'
try:
bowtieOut = open(bowtieOutFile,'r')
except IOError:
print('NO BOWTIE OUTPUT FOR %s' % (name))
continue
for line in bowtieOut:
#get the read length
if line[0] == '':
continue
if line[0:4] == 'File':
readLength = line.split('=')[1][1:-1]
if line[0] == '#' and line.count('reads') == 1:
if line.count('processed') == 1:
readCount = line.split(':')[1][1:-1]
readCount = round(float(readCount)/1000000,2)
if line.count('reported alignment') == 1:
alignedReads = line[-9:-1]
if line.count('failed') == 1:
failedReads = line[-9:-1]
if line.count('suppressed') == 1:
multiReads = line[-9:-1]
if readLength and readCount and alignedReads and failedReads and multiReads:
print('%s\t\t%s\t%s\t%s\t%s\t%s' % (name,readLength,readCount,alignedReads,failedReads,multiReads))
else:
print('%s\tNO DATA AVAILABLE' % (name))
#==========================================================================
#===================MERGE BAMS=============================================
#==========================================================================
def mergeBams(dataFile,mergedName,namesList,color='',background =''):
'''
merges a set of bams and adds an entry to the dataFile
'''
dataDict = loadDataTable(dataFile)
#make an .sh file to call the merging
bamFolder = dataDict[namesList[0]]['folder']
genome = string.lower(dataDict[namesList[0]]['genome'])
if color == '':
color = dataDict[namesList[0]]['color']
if background == '':
background = dataDict[namesList[0]]['background']
if bamFolder[-1] != '/':
bamFolder+='/'
mergedFullPath = bamFolder+mergedName +'.'+genome+'.bwt.sorted.bam'
mergeShFile = open(mergedFullPath+'.sh','w')
mergeShFile.write('cd %s\n' % (bamFolder))
cmd1 = '%s merge %s ' % (samtoolsString,mergedFullPath)
for name in namesList:
cmd1+= ' %s' % (dataDict[name]['bam'])
mergeShFile.write(cmd1+'\n')
cmd2 = '%s sort %s %s' % (samtoolsString,mergedFullPath,bamFolder+mergedName+'.'+genome+'.bwt.sorted')
mergeShFile.write(cmd2+'\n')
cmd3 = '%s index %s' % (samtoolsString,mergedFullPath)
mergeShFile.write(cmd3+'\n')
mergeShFile.close()
runCmd = " 'bash %s'" % (mergedFullPath+'.sh')
os.system(runCmd)
dataTable = parseTable(dataFile,'\t')
dataTable.append([bamFolder,mergedName,genome,mergedName,background,'','',color])
unParseTable(dataTable,dataFile,'\t')
formatDataTable(dataFile)
#==========================================================================
#===============================FILTERING BAMS=============================
#==========================================================================
def filterBams(dataFile,namesList = [],tempFolder = '/raider/BOWTIE_TEMP/',bamFolder='/grail/bam/filtered/'):
'''
for all datasets, will run the bam filtering, drop the filtered bam into the correct TONY folder
and symlink into the bamFolder
must run as admin to write to folder
'''
#check that the temp folder and bam folder exist
if not formatFolder(tempFolder,False):
print("ERROR: UNABLE TO FIND TEMPORARY FOLDER %s" % (tempFolder))
sys.exit()
else:
tempFolder = formatFolder(tempFolder,False)
if not formatFolder(bamFolder,False):
print("ERROR: UNABLE TO FIND BAM FOLDER %s" % (bamFolder))
sys.exit()
else:
bamFolder = formatFolder(bamFolder,False)
dataDict = loadDataTable(dataFile)
if len(namesList) == 0:
namesList = dataDict.keys()
for name in namesList:
uniqueID = dataDict[name]['uniqueID']
genome = string.lower(dataDict[name]['genome'])
#check to see if this has already been done
if dataDict[name]['folder'] == "%s%s/" % (bamFolder,genome):
continue
#change the bam Folder to the location of the filtered bam
dataDict[name]['folder'] = "%s%s/" % (bamFolder,genome)
#get the original bam
bamFile = getTONYInfo(uniqueID,column =47)
#get the parent folder
parentFolder = getParentFolder(bamFile)
#make a temp folder
tempOutFolder = tempFolder + uniqueID +'/'
tempOutFolder = formatFolder(tempOutFolder,True)
#set up a bashFile
bashFileName = '%s%s_filterBam.sh' % (tempOutFolder,uniqueID)
bashFile = open(bashFileName,'w')
bashFile.write('#!usr/bin/bash\n')
#cd into temp directory
bashFile.write('cd %s\n' % (tempOutFolder))
#set up the filter command
filterCmd = 'python /ark/home/cl512/src/scripts-for-project/2-mito-filter-sort-dedupe.py -t 4 -i %s -o %s' % (bamFile,tempOutFolder)
bashFile.write(filterCmd + '\n')
#set up the command to move and then sym link
#mv command
mvBamCommand = 'mv *noChrM.sort.rmdup.bam %s%s_%s.noChrM.fix.rmdup.sorted.bam' % (parentFolder,uniqueID,genome)
bashFile.write(mvBamCommand + '\n')
mvBaiCommand = 'mv *noChrM.sort.rmdup.bam.bai %s%s_%s.noChrM.fix.rmdup.sorted.bam.bai' % (parentFolder,uniqueID,genome)
bashFile.write(mvBaiCommand + '\n')
#now symlink
#check to make sure the genome folder exist
if not formatFolder(bamFolder+genome,False):
print("NO FOLDER EXISTS IN %s FOR BUILD %s" % (bamFolder,genome))
print("ATTEMPTING TO CREATE FOLDER %s%s/" % (bamFolder,genome))
symFolder = formatFolder(bamFolder+genome,True)