#backBed=GenomicRegionSet("BACK")
#backBed.read_bed(backGroundPeaks)
for j, n in enumerate(range(randomize)):
backUP = GenomicRegionSet("BACKUP")
[
back_de_genes, back_de_peak_genes, back_mappedGenes,
back_totalPeaks, bla
] = backUP.filter_by_gene_association(str(j) + "random.bed",
g.genes,
geneFile,
genomeFile,
threshDist=distance)
randomRes.append(back_de_peak_genes)
#print str(j)+"random.bed"
randomRes = numpy.array(randomRes)
#print randomRes
a = de_peak_genes
m = numpy.mean(randomRes)
s = numpy.std(randomRes)
z = (a - m) / s
prop_de = de_peak_genes / float(degenes)
prop_back = m / float(degenes)
p = scipy.stats.norm.sf(z)
print region.name, g.name, a, m, z, degenes, mappedGenes, len(
allgenes), prop_de, prop_back, prop_de / prop_back, p, degenes
if len(outdir) > 0:
outGene.write(region.name + "\t" + g.name + "\t" +
("\t".join(bed.genes)) + "\n")
bed.write_bed(outdir + "/" + g.name + "_" + region.name + ".bed")
parser.add_argument('-organism', type=str, help="Define the organism")
args = parser.parse_args()
genome = GenomeData(args.organism)
if os.path.isfile(args.bed):
regionset = GenomicRegionSet("bed")
regionset.read_bed(args.bed)
gr = regionset.gene_association(organism=args.organism, promoterLength=1000,
threshDist=500000, show_dis=True)
regionset.replace_region_name(gr,combine=True)
regionset.write_bed(args.output)
elif os.path.isdir(args.bed):
if not os.path.exists(args.output):
os.makedirs(args.output)
for root, dirnames, filenames in os.walk(args.bed):
for filename in filenames:
if ".bed" in filename:
print(filename)
fnn = os.path.basename(filename)
fn = fnn.partition(".bed")[0]
try:
regionset = GenomicRegionSet("bed")
regionset.read_bed(os.path.join(args.bed,fnn))
gr = regionset.gene_association(organism=args.organism, promoterLength=1000,
br=region.random_regions('hg19',total_size=len(region),overlap_result=True, overlap_input=True)
br.write_bed(str(j)+"random.bed")
for g in genesets:
#print region,g
bed = GenomicRegionSet("")
[degenes,de_peak_genes, mappedGenes, totalPeaks,bla] = bed.filter_by_gene_association(region.fileName,g.genes,geneFile,genomeFile,threshDist=distance)
randomRes=[]
#backBed=GenomicRegionSet("BACK")
#backBed.read_bed(backGroundPeaks)
for j,n in enumerate(range(randomize)):
backUP=GenomicRegionSet("BACKUP")
[back_de_genes,back_de_peak_genes, back_mappedGenes, back_totalPeaks,bla] = backUP.filter_by_gene_association(str(j)+"random.bed",g.genes,geneFile,genomeFile,threshDist=distance)
randomRes.append(back_de_peak_genes)
#print str(j)+"random.bed"
randomRes=numpy.array(randomRes)
#print randomRes
a=de_peak_genes
m=numpy.mean(randomRes)
s=numpy.std(randomRes)
z=(a-m)/s
prop_de=de_peak_genes/float(degenes)
prop_back=m/float(degenes)
p= scipy.stats.norm.sf(z)
print region.name,g.name,a,m,z,degenes,mappedGenes,len(allgenes),prop_de,prop_back,prop_de/prop_back,p,degenes
if len(outdir)>0:
outGene.write(region.name+"\t"+g.name+"\t"+("\t".join(bed.genes))+"\n")
bed.write_bed(outdir+"/"+g.name+"_"+region.name+".bed")