tmpdir_mutants = tempfile.mkdtemp("dictymutants")
base_mutants = DictyMutants.download_mutants()
file_mutants = os.path.join(tmpdir_mutants, "tempMut")
fm = open(file_mutants, "wb")
fm.write(base_mutants)
fm.close()
fm_dom = DictyMutants.domain
fm_name = DictyMutants.pickle_file
print file_mutants
sf_server.upload(fm_dom,
fm_name,
file_mutants,
title="dictyBase mutant phenotypes",
tags=DictyMutants.tags)
sf_server.unprotect(fm_dom, fm_name)
shutil.rmtree(tmpdir_mutants)
"""
Orange server upload for Dicty mutant gene sets
"""
from orangecontrib.bio.geneset import dictyMutantSets, update_server_list, register
mutant_sets_split = dictyMutantSets().split_by_hierarchy()
for mutant_sets in mutant_sets_split:
register(mutant_sets, sf_server)
import os, sys
path = os.path.join(environ.buffer_dir, "tmp_OMIM")
try:
os.mkdir(path)
except OSError:
pass
filename = os.path.join(path, "morbidmap")
obiOMIM.OMIM.download_from_NCBI(filename)
sf_server.upload("OMIM",
"morbidmap",
filename,
title="Online Mendelian Inheritance in Man (OMIM)",
tags=[
"genes", "diseases", "human",
"OMIM"
"#version:%i" % obiOMIM.OMIM.VERSION
])
sf_server.unprotect("OMIM", "morbidmap")
"""
Orange server upload for OMIM morbidmap gene sets
"""
from orangecontrib.bio.geneset import omimGeneSets, register
omim_sets_split = omimGeneSets().split_by_hierarchy()
for omim_sets in omim_sets_split:
register(omim_sets, sf_server)
##[email protected] from common import * from orangecontrib.bio import obiOMIM import os, sys path = os.path.join(environ.buffer_dir, "tmp_OMIM") try: os.mkdir(path) except OSError: pass filename = os.path.join(path, "morbidmap") obiOMIM.OMIM.download_from_NCBI(filename) sf_server.upload("OMIM", "morbidmap", filename, title="Online Mendelian Inheritance in Man (OMIM)", tags=["genes", "diseases", "human", "OMIM" "#version:%i" % obiOMIM.OMIM.VERSION]) sf_server.unprotect("OMIM", "morbidmap") """ Orange server upload for OMIM morbidmap gene sets """ from orangecontrib.bio.geneset import omimGeneSets, register omim_sets_split = omimGeneSets().split_by_hierarchy() for omim_sets in omim_sets_split: register(omim_sets, sf_server)
##interval:7
from common import *
"""
Orange server upload for Cytoband gene sets
"""
from orangecontrib.bio.geneset import reactomePathwaysGeneSets, register
reactome_sets_split = reactomePathwaysGeneSets().split_by_hierarchy()
for pathway_sets in reactome_sets_split:
register(pathway_sets, sf_server)
for exp in result["expressions"]:
diff_exp = [
e for e in exp["experiments"] if e["pvalue"] <= max_pvalue
] # Use only genes that are significantly diff. expressed
if diff_exp:
try:
sets[exp["ef"], exp["efv"]].append(
result["gene"]["name"]
) # The Gene Expression Atlas entries are not consistent.
except:
sets[exp["efoTerm"],
exp["efoId"]].append(result["gene"]["name"])
print time.time() - start
gene_sets = []
for (ef, efv), genes in sets.items():
ef_display = display_string(ef)
gs = GeneSet(genes, "Diff. expressed in %s=%s." % (ef_display, efv), id=ef + ":" + efv,
description="Diff. expressed in %s=%s." % (ef_display, efv),
link="http://www.ebi.ac.uk/gxa/qrs?specie_0={organism}&gprop_0=&gnot_0=&gval_0=&fact_1=&fexp_1=UPDOWN&fmex_1=&fval_1=%22{efv}%22+&view=hm".format( \
organism = "+".join(organism.lower().split()), efv = "+".join(efv.lower().split())), organism=org_code, hierarchy=("Gene Expression Atlas", display_string(condition)))
gene_sets.append(gs)
final_set = GeneSets(gene_sets)
set_split = final_set.split_by_hierarchy()
for s in set_split:
register(s, sf_server)
print "Gene sets successfully registered..."
##interval:7
from common import *
"""
Orange server upload for Cytoband gene sets
"""
from orangecontrib.bio.geneset import cytobandGeneSets, register
cytoband_sets_split = cytobandGeneSets().split_by_hierarchy()
for band_sets in cytoband_sets_split:
register(band_sets, sf_server)
start = time.time()
query = run_simple_query(regulation=regulation, organism=organism, condition=condition, start=start*no_of_genes, rows=no_of_genes)
for result in query["results"]:
i += 1
print result["gene"]["name"] + "\t" + str(i) # For printing out gene names and the current number of genes during debugging
for exp in result["expressions"]:
diff_exp = [e for e in exp["experiments"] if e["pvalue"] <= max_pvalue] # Use only genes that are significantly diff. expressed
if diff_exp:
try:
sets[exp["ef"], exp["efv"]].append(result["gene"]["name"]) # The Gene Expression Atlas entries are not consistent.
except:
sets[exp["efoTerm"], exp["efoId"]].append(result["gene"]["name"])
print time.time() - start
gene_sets = []
for (ef, efv), genes in sets.items():
ef_display = display_string(ef)
gs = GeneSet(genes, "Diff. expressed in %s=%s." % (ef_display, efv), id=ef + ":" + efv,
description="Diff. expressed in %s=%s." % (ef_display, efv),
link="http://www.ebi.ac.uk/gxa/qrs?specie_0={organism}&gprop_0=&gnot_0=&gval_0=&fact_1=&fexp_1=UPDOWN&fmex_1=&fval_1=%22{efv}%22+&view=hm".format( \
organism = "+".join(organism.lower().split()), efv = "+".join(efv.lower().split())), organism=org_code, hierarchy=("Gene Expression Atlas", display_string(condition)))
gene_sets.append(gs)
final_set = GeneSets(gene_sets)
set_split = final_set.split_by_hierarchy()
for s in set_split:
register(s, sf_server)
print "Gene sets successfully registered..."
Orange server upload for DictyMutants
"""
tmpdir_mutants = tempfile.mkdtemp("dictymutants")
base_mutants = DictyMutants.download_mutants()
file_mutants = os.path.join(tmpdir_mutants, "tempMut")
fm = open(file_mutants, "wb")
fm.write(base_mutants)
fm.close()
fm_dom = DictyMutants.domain
fm_name = DictyMutants.pickle_file
print file_mutants
sf_server.upload(fm_dom, fm_name, file_mutants, title="dictyBase mutant phenotypes",
tags=DictyMutants.tags)
sf_server.unprotect(fm_dom, fm_name)
shutil.rmtree(tmpdir_mutants)
"""
Orange server upload for Dicty mutant gene sets
"""
from orangecontrib.bio.geneset import dictyMutantSets, update_server_list, register
mutant_sets_split = dictyMutantSets().split_by_hierarchy()
for mutant_sets in mutant_sets_split:
register(mutant_sets, sf_server)
##interval:7
from common import *
"""
Orange server upload for Cytoband gene sets
"""
from orangecontrib.bio.geneset import reactomePathwaysGeneSets, register
reactome_sets_split = reactomePathwaysGeneSets().split_by_hierarchy()
for pathway_sets in reactome_sets_split:
register(pathway_sets, sf_server)
