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RNASeqAnalyzer.py
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RNASeqAnalyzer.py
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#!/usr/bin/python
"""
RNAseq analysis for Cortez Lab
Authors: Lisa Poole and James Pino
Requirements for this experiment - sequencing data files must be in a folder
entitled "fasta" within a folder corresponding to the experiment name;
modify general information in the first part of the script
(starting with sample base).
"""
import time
import os
import subprocess
import warnings
# General information - modify appropriately for each experiment
# Number of sequencing samples
number_of_samples = '4'
# Valid options: mouse or human
species = 'human'
# Valid options: "SE" or "PE"
read_type = 'PE'
read_length = 150
sample_suffix = 'fastq'
compression_suffix = 'gz'
n_cpus = 8
source_config = dict(flexbar=None, hisat2=None, samtools=None,
featurecounts=None, samstat=None, )
reference_config = dict(adaptors=None, transcripts=None, hisat2_index=None,
reference_genome=None, )
goku_config = dict(flexbar='/usr/bin/flexbar',
hisat2='/home/pinojc/RNASeq_sources/Software/hisat2-2.0.4/hisat2',
samtools='/home/pinojc/RNASeq_sources/Software/samtools-1.3.1/samtools',
samstat='/usr/local/bin/samstat',
featurecounts='/home/pinojc/RNASeq_sources/Software/subread-1.5.1-source/bin/featureCounts',
fasta_directory="/home/pinojc/LisaData/E65_rna_fasta",
gatk='/home/pinojc/RNASeq_sources/Software/GATK/GenomeAnalysisTK.jar',
bwa='/home/pinojc/RNASeq_sources/Software/bwa.kit/bwa',
picard='/home/pinojc/RNASeq_sources/Software/picard.jar', )
class RNASeqAnalyzer(object):
def __init__(self, sample_base, output_directory, n_cpu, ref_config,
executables_config, write_bash=False):
self.sample_base = sample_base
self.n_cpu = n_cpu
if not os.path.exists(output_directory):
os.mkdir(output_directory)
self.fasta_dir = os.path.join(output_directory, 'fasta')
if not os.path.exists(self.fasta_dir):
warnings.warn("Must have directory within provided output "
"directory {} named 'fasta' that contains "
"fasta(or fastq) files with sample base name")
os.chdir(output_directory)
self.all_output = ''
for i in reference_config:
if i not in ref_config:
print("Please provide path to {} in ref_config")
for i in ref_config:
if not os.path.exists(ref_config[i]):
err = "{} path of {} does not exist".format(i, ref_config[i])
warnings.warn(err)
self.adaptors = ref_config['adaptors']
self.transcripts = ref_config['transcripts']
self.hisat2_index = ref_config['hisat2_index']
self.reference_genome = ref_config['reference_genome']
self.write_bash = write_bash
self._bash_file = ''
for i in source_config:
if i not in executables_config:
print("Please provide path to {} in executables_config".format(
i))
for i in executables_config:
which(executables_config[i])
self._exe = executables_config
self.flexbar = self._exe['flexbar']
self.hisat2 = self._exe['hisat2']
self.samstat = self._exe['samstat']
self.samtools = self._exe['samtools']
self.featurecounts = self._exe['featurecounts']
def setup(self):
"""
Create directory of all outputs
Returns
-------
"""
def flexbar_trim(self):
"""
Removed adapters for better and quicker alignment
input :
zipped fasta(fastq) file
If single-ended, only 1, if paired-end there will be 2
Labeled with sample_base_1, sample_base_2
Returns
-------
"""
# Flexbar options
# '-a' = adaptor sequences (fasta format)
# '-n' = number of threads
# '-u' = max uncalled bases for each read to pass filtering
# '-m' = min read length to remain after filtering/trimming
# '-t' = prefix for output file names
# '-ao' = adapter min overlap
# '-ae' = adapter trim end
print("Start trimming {}".format(self.sample_base))
warnings.warn("Assuming the use of Illumina sequence adapters!\n"
"Please verify")
path_to_executable = self._exe['flexbar']
suffix_for_output = '-t {}/{}-trimmed'.format(self.fasta_dir,
self.sample_base)
adaptor_trim_end = '-ae ANY'
adaptor_overlap = '-ao 5'
path_to_adaptors = "-a {}".format(self.adaptors)
number_max_uncalled_bases_pass = '-u {}'.format(read_length)
main_read_length_to_remain = '-m 18'
threads = '-n {}'.format(self.n_cpu)
if read_type not in ('SE', 'PE'):
print("Error. Invalid read type. Valid options are "
"SE or PE Aborting.")
quit()
elif read_type == 'SE':
reads = '-r {}/{}.{}.{}'.format(self.fasta_dir, self.sample_base,
sample_suffix, compression_suffix)
elif read_type == 'PE':
reads = ' -r {0}/{1}_1.{2}.{3} -p {0}/{1}_2.{2}.{3}'.format(
self.fasta_dir, self.sample_base, sample_suffix,
compression_suffix)
command = [path_to_executable, reads, path_to_adaptors, threads,
suffix_for_output, adaptor_overlap, adaptor_trim_end,
number_max_uncalled_bases_pass, main_read_length_to_remain]
if self.write_bash:
self._bash_file += ' '.join(i for i in command)
self._bash_file += '\n'
else:
self._run(command)
print("Done trimming {}".format(self.sample_base))
# HISAT Alignment
def hisat2_alignment(self):
"""
Aligns trimmed fasta(fastq) to genome
#TODO check to see if genome fasta exists
#TODO make sure HISAT2 index exists for that genome
Can be done with HISAT2 index command
Returns
-------
outputs a SAM format
"""
print("Starting aligning {}".format(self.sample_base))
path_to_executable = self._exe['hisat2']
if not os.path.exists("BAM_files"):
print("Creating BAM_files directory")
os.mkdir("BAM_files")
output_name = '-S ./BAM_files/{}.sam'.format(self.sample_base)
threads = '-p {}'.format(self.n_cpu)
indices = '-x {}'.format(self.hisat2_index)
if read_type == 'SE':
reads = '-U {0}/{1}-trimmed.{2}'.format(self.fasta_dir,
self.sample_base,
sample_suffix)
elif read_type == 'PE':
reads = '-1 {0}/{1}-trimmed_1.{2} ' \
'-2 {0}/{1}-trimmed_2.{2}'.format(self.fasta_dir,
self.sample_base,
sample_suffix, )
command = [path_to_executable, threads, indices, reads, output_name]
if self.write_bash:
self._bash_file += ' '.join(i for i in command)
self._bash_file += '\n'
else:
self._run(command)
print("Done aligning {}".format(self.sample_base))
def sam_to_bam(self):
""" Conversion from SAM to BAM and sorting
Returns
-------
"""
print("Start sam to bam conversion {}".format(self.sample_base))
path_to_executable = '{} view'.format(self.samtools)
path_to_samples = '-S -b ./BAM_files/{}.sam'.format(self.sample_base)
output_filename = '-o ./BAM_files/{}.bam'.format(self.sample_base)
threads = '--threads {}'.format(self.n_cpu)
command = [path_to_executable, path_to_samples, threads,
output_filename]
if self.write_bash:
self._bash_file += ' '.join(i for i in command)
self._bash_file += '\n'
else:
self._run(command)
def bam_index(self):
""" Indexs SAM file to BAM
Returns
-------
"""
print("Start indexing {}".format(self.sample_base))
# samtools = '/home/pinojc/RNASeq_sources/Software/./sambamba_v0.6.5'
# TODO see why I chose to use SAMBA? Benchmark
path_to_executable = '{} index'.format(self.samtools)
path_to_samples = './BAM_files/{}.sorted.bam'.format(self.sample_base)
threads = '-p --nthreads={}'.format(self.n_cpu)
threads = ''
command = [path_to_executable, threads, path_to_samples]
if self.write_bash:
self._bash_file += ' '.join(i for i in command)
self._bash_file += '\n'
else:
self._run(command)
print("Done indexing {}".format(self.sample_base))
# SAMSTAT Quality Check
def samstat_analysis(self):
""" quality control check on alignment
Open file and see what is print what is good and bad
Returns
-------
"""
print("Start SAMSTAT check {}".format(self.sample_base))
if not os.path.exists('quality_control'):
os.mkdir('quality_control')
path_to_executable = self.samstat
path_to_samples = './BAM_files/{}.sorted.bam'.format(self.sample_base)
command = [path_to_executable, path_to_samples]
if self.write_bash:
self._bash_file += ' '.join(i for i in command)
self._bash_file += '\n'
else:
self._run(command)
os.rename('BAM_files/{}.sorted.bam.samstat.html'.format(
self.sample_base),
'quality_control/{}.hisat2.sorted.bam.samstat.html'.format(
self.sample_base))
print("Done SAMSTAT check {}".format(self.sample_base))
def bam_sort(self, directory):
""" sorts bam file and collapses duplicates
append .sorted to "sample_base_name.bam"
like "sample_base_name.sorted.bam"
Parameters
----------
directory : str
output directory
Returns
-------
"""
print("Start sorting {}".format(self.sample_base))
path_to_executable = '{} sort'.format(self.samtools)
path_to_samples = ' {}/{}.bam'.format(directory, self.sample_base)
output_filename = '-o {}/{}.sorted.bam'.format(directory,
self.sample_base)
threads = '--threads {}'.format(self.n_cpu)
command = [path_to_executable, threads, output_filename,
path_to_samples]
if self.write_bash:
self._bash_file += ' '.join(i for i in command)
self._bash_file += '\n'
else:
self._run(command)
print("Done sorting {}".format(self.sample_base))
# FeatureCounts - align reads to genes
def featurecounts_analysis(self, list_of_samples):
"""
Takes all sample sorted bam files and compares all genes across samples
Need GTF file for gene ids ( downloaded with genome)
#TODO check for GTF file
Parameters
-------
list_of_samples: list_like
list of all samples
Returns
-------
"""
# FeatureCounts options
# -a annotation file
# -o name of output file with read counts
# -p fragments counted instead of reads (paired end specific)
# -B count only read pairs that have both ends successfully aligned only
# -C don't count reads that have two ends mapping to different chromosomes or mapping to same chromosome but on different strands
# -Q minimum mapping quality score a read must satisfy in order to be counted
# -t feature type in GTF file, default is "exon"
# -g specify attribute in GTF file, default is gene_id
path_to_executable = self.featurecounts
annotation_file = "-a {}".format(self.transcripts)
output_name = "-o gene_counts.txt"
gtf_feature = '-t exon'
gtf_attibute = '-g gene_id'
quality_score = '-Q 30'
out_string = ''
if list_of_samples is None:
print("Need list of samples")
quit()
for i in list_of_samples:
input_files = ' ./BAM_files/{0}.sorted.bam'.format(i)
out_string += input_files
if read_type == 'SE':
important_options = "-T {}".format(n_cpus)
elif read_type == 'PE':
important_options = "-p -B -C -T {}".format(n_cpus)
command = [path_to_executable, important_options, gtf_feature,
gtf_attibute, quality_score, annotation_file, output_name,
out_string]
if self.write_bash:
self._bash_file += ' '.join(i for i in command)
self._bash_file += '\n'
else:
self._run(command)
print("Done running {}".format(self.sample_base))
def _run(self, command):
st = time.time()
call_code = ' '.join(command)
print("Running command {}".format(call_code))
process = subprocess.Popen([call_code], shell=True,
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT)
while True:
output = process.stdout.readline()
if output == '' and process.poll() is not None:
break
if output:
print(output.strip())
self.all_output += output.strip()
rc = process.poll()
print('Finished - time taken = {}'.format(time.time() - st))
def gene_exp(self):
""" Runs basic rna analysis
:param sample_base:
:return:
"""
self.flexbar_trim()
self.hisat2_alignment()
self.sam_to_bam()
self.bam_sort('BAM_files')
self.bam_index()
self.samstat_analysis()
def write_log_file(self, file_name):
with open(file_name, 'w') as f:
f.write(self.all_output)
def which(program):
import os
def _is_exe(filepath):
return os.path.isfile(filepath) and os.access(filepath, os.X_OK)
fpath, fname = os.path.split(program)
if fpath:
if _is_exe(program):
return program
else:
for path in os.environ["PATH"].split(os.pathsep):
path = path.strip('"')
exe_file = os.path.join(path, program)
if _is_exe(exe_file):
return exe_file
warnings.warn("{} isn't executable!\n"
"Make sure it is installed.".format(program))
return None
if __name__ == "__main__":
output_directory = "/media/pinojc/68f7ba6a-cdf6-4761-930d-9c1bb724e40d/home/LP_data",
goku_ref_config = dict(
adaptors='/Users/temporary/genomes/adapters/illumina_truseq.fasta',
transcripts='/media/pinojc/68f7ba6a-cdf6-4761-930d-9c1bb724e40d/home/Homo_sapiens/UCSC/hg38/Annotation/Genes/genes.gtf',
hisat2_index='/media/pinojc/68f7ba6a-cdf6-4761-930d-9c1bb724e40d/home/Homo_sapiens/UCSC/hg38/Sequence/HISAT2Index/genome',
reference_genome='/media/pinojc/68f7ba6a-cdf6-4761-930d-9c1bb724e40d/home/Homo_sapiens/UCSC/hg38/Sequence/BWAIndex/genome.fa', )
vegeta_config = dict(
featurecounts='/home/pinojc/Sources/subread-1.5.1-source/bin/featureCounts',
samstat='samstat', samtools='samtools',
hisat2='/home/pinojc/Sources/hisat2-2.0.5/hisat2',
flexbar='/home/pinojc/Sources/flexbar_v2.5_linux64/flexbar')
x = RNASeqAnalyzer('test', 'test', 1, ref_config=goku_ref_config,
executables_config=vegeta_config, write_bash=True)
x.gene_exp()
print(x._bash_file)