Commit fdce587a authored by Blaise Li's avatar Blaise Li
Browse files

Made libdeseq a submodule.

parent 08452c07
......@@ -10,3 +10,6 @@
[submodule "libhts"]
path = libhts
url = git@gitlab.pasteur.fr:bli/libhts.git
[submodule "libdeseq"]
path = libdeseq
url = git@gitlab.pasteur.fr:bli/libdeseq.git
Subproject commit 8df8009e005d16234b2b985f63e83ed25d0fa759
# Compiled python modules.
*.pyc
# Setuptools distribution folder.
/dist/
# Python egg metadata, regenerated from source files by setuptools.
/*.egg-info
# Backups
*~
#!/bin/sh
python3.6 setup.py build_ext
# .egg-link does not work with PYTHONPATH ?
python3.6 -m pip install -e .
python3.6 -m pip install --no-deps --ignore-installed .
from .libdeseq import (
do_deseq2)
import warnings
def formatwarning(message, category, filename, lineno, line):
"""Used to format warning messages."""
return "%s:%s: %s: %s\n" % (filename, lineno, category.__name__, message)
warnings.formatwarning = formatwarning
import pandas as pd
from rpy2.robjects import r, pandas2ri, Formula, StrVector
as_df = r("as.data.frame")
from rpy2.rinterface import RRuntimeError
from rpy2.robjects.packages import importr
deseq2 = importr("DESeq2")
#import gc
def do_deseq2(cond_names, conditions, counts_data,
formula=None, contrast=None, deseq2_args=None):
"""Runs a DESeq2 differential expression analysis."""
if formula is None:
formula = Formula("~ lib")
if contrast is None:
# FIXME: MUT and REF are not defined
# Maybe just make (formula and) contrast mandatory
contrast = StrVector(["lib", MUT, REF])
if deseq2_args is None:
deseq2_args = {"betaPrior" : True, "addMLE" : True, "independentFiltering" : True}
col_data = pd.DataFrame(conditions).assign(
cond_name=pd.Series(cond_names).values).set_index("cond_name")
# In case we want contrasts between factor combinations
if ("lib" in col_data.columns) and ("treat" in col_data.columns):
col_data = col_data.assign(
lib_treat = ["%s_%s" % (lib, treat) for (lib, treat) in zip(
col_data["lib"], col_data["treat"])])
col_data_rownames = list(col_data.index)
counts_data_colnames = list(counts_data.columns)
if col_data_rownames != counts_data_colnames:
warnings.warn(
"The lines in the sample description do not match "
"the columns in the counts table.\n"
"Expect failures while loading data in DESeq2.\n")
# http://stackoverflow.com/a/31206596/1878788
pandas2ri.activate() # makes some conversions automatic
# r_counts_data = pandas2ri.py2ri(counts_data)
# r_col_data = pandas2ri.py2ri(col_data)
# r.DESeqDataSetFromMatrix(countData=r_counts_data, colData=r_col_data, design=Formula("~lib"))
# dds = deseq2.DESeq(dds, betaPrior=deseq2_args["betaPrior"])
# Decompose into the 3 steps to have more control on the options
dds = deseq2.DESeqDataSetFromMatrix(
countData=counts_data,
colData=col_data,
design=formula)
# try:
# dds = deseq2.DESeqDataSetFromMatrix(
# countData=counts_data,
# colData=col_data,
# design=formula)
# except RRuntimeError as e:
# # TODO: remove this debugging thing, or use a unique path
# # and issue a warning that indicates the path to the debug file
# col_data.to_csv("/tmp/col_data_debug.txt", sep="\t")
# counts_data.to_csv("/tmp/counts_data_debug.txt", sep="\t")
# raise
try:
dds = deseq2.estimateSizeFactors_DESeqDataSet(dds, type="ratio")
#gc.collect()
except RRuntimeError as e:
if sum(counts_data.prod(axis=1)) == 0:
msg = "".join(["Error occurred in estimateSizeFactors:\n%s\n" % e,
"This is probably because every gene has at least one zero.\n",
"We will try to use the \"poscounts\" method instead."])
warnings.warn(msg)
try:
dds = deseq2.estimateSizeFactors_DESeqDataSet(dds, type="poscounts")
#gc.collect()
except RRuntimeError as e:
msg = "".join(["Error occurred in estimateSizeFactors:\n%s\n" % e,
"We give up."])
warnings.warn(msg)
#gc.collect()
raise
#print(counts_data.dtypes)
#print(counts_data.columns)
#print(len(counts_data))
#raise
else:
raise
size_factors = pandas2ri.ri2py(as_df(deseq2.sizeFactors_DESeqDataSet(dds)))
#for cond in cond_names:
# #s = size_factors.loc[cond][0]
# #(*_, s) = size_factors.loc[cond]
#pd.DataFrame({cond : size_factors.loc[cond][0] for cond in COND_NAMES}, index=('size_factor',))
try:
dds = deseq2.estimateDispersions_DESeqDataSet(dds, fitType="parametric")
#gc.collect()
except RRuntimeError as e:
msg = "".join(["Error occurred in estimateDispersions:\n%s\n" % e,
"We will try with fitType=\"local\"."])
warnings.warn(msg)
try:
dds = deseq2.estimateDispersions_DESeqDataSet(dds, fitType="local")
#gc.collect()
except RRuntimeError as e:
msg = "".join(["Error occurred in estimateDispersions:\n%s\n" % e,
"We will try with fitType=\"mean\"."])
warnings.warn(msg)
try:
dds = deseq2.estimateDispersions_DESeqDataSet(dds, fitType="mean")
#gc.collect()
except RRuntimeError as e:
msg = "".join(["Error occurred in estimateDispersions:\n%s\n" % e,
"We give up."])
warnings.warn(msg)
#gc.collect()
raise
dds = deseq2.nbinomWaldTest(dds, betaPrior=deseq2_args["betaPrior"])
#gc.collect()
res = pandas2ri.ri2py(as_df(deseq2.results(
dds,
contrast=contrast,
addMLE=deseq2_args["addMLE"],
independentFiltering=deseq2_args["independentFiltering"])))
res.index = counts_data.index
return res, {cond : size_factors.loc[cond][0] for cond in cond_names}
from setuptools import setup, find_packages
#from Cython.Build import cythonize
name = "libdeseq"
# Adapted from Biopython
__version__ = "Undefined"
for line in open("%s/__init__.py" % name):
if (line.startswith('__version__')):
exec(line.strip())
setup(
name=name,
version=__version__,
description="Interfacing the call to DESEq2 with python.",
author="Blaise Li",
author_email="blaise.li@normalesup.org",
license="MIT",
packages=find_packages())
#ext_modules = cythonize("libsmallrna/libsmallrna.pyx"),
#install_requires=["cytoolz"],
#zip_safe=False
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