def extract_phastcons(bedfile, phas_chrnames, width):
"""Extract phastcons scores from a bed file.
Return the average scores
"""
info("read bed file...")
bfhd = open(bedfile)
bed = BedIO.parse_BED(bfhd)
# calculate the middle point of bed regions then extend left and right by 1/2 width
bchrs = bed.peaks.keys()
bchrs.sort()
chrs = []
for c in phas_chrnames:
if c in bchrs:
chrs.append(c)
sumscores = [0] * width
n = 0
tmpfname = tempfile.mkstemp(prefix="consplotscore")[1]
tmpbedfname = tempfile.mkstemp(prefix="consplotbed")[1]
# fix regions in bed file
for chrom in chrs:
pchrom = bed.peaks[chrom]
for i in range(len(pchrom)):
mid = int((pchrom[i][0] + pchrom[i][1]) / 2)
left = int(mid - width / 2)
right = int(mid + width / 2)
if left < 0:
pchrom[i] = (0, width, 1, 1, 1, 1, 1, 1)
else:
pchrom[i] = (left, right, 1, 1, 1, 1, 1, 1)
bedfhd = open(tmpbedfname, 'w')
bedfhd.write(bed.tobed())
bedfhd.close()
for chrom in chrs:
tmpf = open(tmpfname, 'w')
info("extract chromosome %s" % (chrom))
p = subprocess.Popen(
[hgWiggle, '-bedFile=%s' % tmpbedfname, chrom], stdout=tmpf)
p.communicate()
tmpf.close()
wio = WiggleIO.WiggleIO(open(tmpfname))
wtrack = wio.build_wigtrack()
wtrack.sort()
scores = bed.extract_wiggle_pv(wtrack)
add_scores(sumscores, scores)
n += len(scores)
os.unlink(tmpfname)
os.unlink(tmpbedfname)
# calculate average score
return map(lambda x: float(x) / n, sumscores)
def extract_phastcons ( bedfile, phas_chrnames, width ):
"""Extract phastcons scores from a bed file.
Return the average scores
"""
info("read bed file...")
bfhd = open(bedfile)
bed = BedIO.parse_BED(bfhd)
# calculate the middle point of bed regions then extend left and right by 1/2 width
bchrs = bed.peaks.keys()
bchrs.sort()
chrs = []
for c in phas_chrnames:
if c in bchrs:
chrs.append(c)
sumscores = [0]*width
n = 0
tmpfname = tempfile.mkstemp(prefix="consplotscore")[1]
tmpbedfname = tempfile.mkstemp(prefix="consplotbed")[1]
# fix regions in bed file
for chrom in chrs:
pchrom = bed.peaks[chrom]
for i in range(len(pchrom)):
mid = int((pchrom[i][0]+pchrom[i][1])/2)
left = int(mid - width/2)
right = int(mid + width/2)
if left < 0:
pchrom[i] = (0,width,1,1,1,1,1,1)
else:
pchrom[i] = (left,right,1,1,1,1,1,1)
bedfhd = open (tmpbedfname,'w')
bedfhd.write(bed.tobed())
bedfhd.close()
for chrom in chrs:
tmpf = open(tmpfname,'w')
info ("extract chromosome %s" % (chrom))
p = subprocess.Popen([hgWiggle,'-bedFile=%s' % tmpbedfname,chrom],stdout=tmpf)
p.communicate()
tmpf.close()
wio = WiggleIO.WiggleIO(open(tmpfname))
wtrack = wio.build_wigtrack()
wtrack.sort()
scores = bed.extract_wiggle_pv(wtrack)
add_scores ( sumscores, scores )
n += len(scores)
os.unlink(tmpfname)
os.unlink(tmpbedfname)
# calculate average score
return map(lambda x:float(x)/n, sumscores)
def main():
usage = "usage: %prog [options] <-r rfile> <-b bed file> <-w wiggle file>(>=2)"
description = """Draw correlation plot for many wiggle files at regions by a bed file.
Method: It will calculate a value for each region defined in a bed
file based on each wiggle files. The method can be chosen from -m
option.
"""
optparser = OptionParser(version="%prog 0.1",description=description,usage=usage,add_help_option=False)
optparser.add_option("-h","--help",action="help",help="Show this help message and exit.")
optparser.add_option("-d","--db",type="str",dest="dbname",help="UCSC db name for the assembly. Default: ce4",default="ce4")
optparser.add_option("-z","--imgsize",dest="imgsize",type="int",
help="image size. default: 10, minimal: 10",default=10)
optparser.add_option("-f","--format",dest="imgformat",type="string",
help="image format. PDF or PNG",default='PDF')
optparser.add_option("-m","--method",dest="method",type="string",default="median",
help="method to process the paired two sets of data in the sampling step. Choices are 'median', 'mean', and 'sample' (just take one point out of a data set). Default: median")
optparser.add_option("-r","--rfile",dest="rfile",
help="R output file. If not set, do not save R file.")
optparser.add_option("-b","--bed",dest="bed",type="string",
help="the bed file you want to include in the calculation.")
optparser.add_option("-w","--wig",dest="wig",type="string",action="append",
help="the wiggle file you want to include in the calculation. This option should be used for at least twice.")
optparser.add_option("-l","--wig-label",dest="wiglabel",type="string",action="append",
help="the wiggle file labels in the figure. No space is allowed. This option should be used same times as -w option, and please input them in the same order as -w option. default: will use the wiggle file filename as labels.")
optparser.add_option("--min-score",dest="minscore",type="float",default=0,
help="minimum score included in calculation. Points w/ score lower than this will be discarded.")
optparser.add_option("--max-score",dest="maxscore",type="float",default=10000,
help="maximum score included in calculation. Points w/ score larger than this will be discarded.")
optparser.add_option("-H","--heatmap",dest="heatmap",action="store_true",default=False,
help="If True, a heatmap image will be generated instead of paired scatterplot image.")
(options,args) = optparser.parse_args()
imgfmt = options.imgformat.upper()
if imgfmt != 'PDF' and imgfmt != 'PNG':
print "unrecognized format: %s" % imgfmt
sys.exit(1)
method = options.method.lower()
if method == 'median':
medfunc = median
elif method == 'mean':
medfunc = mean
elif method == 'sample':
medfunc = lambda u: u[-1]
else:
print "unrecognized method: %s" % (method)
sys.exit(1)
# must provide >=2 wiggle files
if not options.wig or len(options.wig) < 2 or not options.rfile or not options.bed:
optparser.print_help()
sys.exit(1)
# wig labels
if options.wiglabel and len(options.wiglabel) == len(options.wig):
wiglabel = options.wiglabel
else: # or use the filename
wiglabel = map(lambda x:os.path.basename(x),options.wig)
wigfilenum = len(options.wig)
# check the files
if not os.path.isfile(options.bed):
error("%s is not valid!" % options.bed)
sys.exit(1)
for f in options.wig:
if not os.path.isfile(f):
error("%s is not valid!" % f)
sys.exit(1)
wigfhds = map(open,options.wig) # file handlers for wiggle files
info("number of wiggle files: %d" % wigfilenum)
# get chromosome length info from UCSC
info("connect to UCSC to get chromosome length information")
try:
chrom_len = get_chrom_length(options.dbname)
except:
error("Error!")
sys.exit(1)
# get the common chromosome list:
chromsdict = {}
for wigfhd in wigfhds:
for l in wigfhd:
if l.find("chrom=") != -1:
c = re.search("chrom=(\w+)",l).group(1)
chromsdict[c] = chromsdict.setdefault(c,0)+1
chroms = []
for c in chromsdict.keys():
if chromsdict[c]==wigfilenum:
chroms.append(c)
info("common chromosomes are %s..." % ",".join(chroms))
# open the R script file handler
rfhd = open(options.rfile,"w")
rfhd.write('''
require("RColorBrewer") ## from CRAN
''')
info("read bed file %s" % os.path.basename(options.bed))
bedregion = BedIO.parse_BED(open(options.bed,'r'))
# for each wig file, sample...
for i in range(len(wigfhds)):
wigfhd = wigfhds[i]
wigfhd.seek(0) # reset
info("read wiggle track from wiggle file #%d" % (i+1))
bk = WiggleIO.WiggleIO(wigfhd).build_binKeeper(chromLenDict=chrom_len)
p = bedregion.extract_binkeepers(bk,func=medfunc)
info("write values to r file")
rfhd.write("p%d <- c(" % i )
if p[0]:
rfhd.write("%f" % p[0])
else:
rfhd.write("NA")
for v in p[1:]:
if v:
rfhd.write(",%f" % v)
else:
rfhd.write(",NA")
rfhd.write(")\n")
rfhd.write("c <- cbind(p0")
for i in range(wigfilenum-1):
rfhd.write(",p%d" % (i+1))
rfhd.write(")\n")
rfhd.write("c <- c[ c[,1]<=%f & c[,1]>=%f " % (options.maxscore,options.minscore))
for i in range(wigfilenum-1):
rfhd.write("& c[,%d]<=%f & c[,%d]>=%f " % (i+2,options.maxscore,i+2,options.minscore))
rfhd.write(",]\n")
if imgfmt == 'PDF':
rfhd.write("pdf(\"%s.pdf\",width=%d,height=%d)\n" % (options.rfile,options.imgsize,options.imgsize))
elif imgfmt == 'PNG':
rfhd.write("png(\"%s.png\",units=\"in\",res=150,width=%d,height=%d)\n" % (options.rfile,options.imgsize,options.imgsize))
if options.heatmap:
rfhd.write('library(gplots)\n')
rfhd.write('''
m <- cor(c, method="pearson", use="pairwise.complete.obs")
''')
labels = ",".join(map(lambda x:"\""+x+"\"",wiglabel))
rfhd.write("rownames(m) <- c(%s)\n" % labels)
rfhd.write("colnames(m) <- c(%s)\n" % labels)
rfhd.write('# draw the heatmap using gplots heatmap.2\n')
# rfhd.write('bitmap("%s.bmp",width=%d,height=%d)\n' % (options.rfile,options.imgsize,options.imgsize))
rfhd.write('mn <- -1\n')
rfhd.write('mx <- 1\n')
rfhd.write('n <- 98\n')
rfhd.write('bias <- 1\n')
rfhd.write('mc <- matrix(as.character(round(m, 2)), ncol=dim(m)[2])\n')
rfhd.write('breaks <- seq(mn, mx, (mx-mn)/(n))\n')
rfhd.write('cr <- colorRampPalette(colors = c("#2927FF","#FFFFFF","#DF5C5C"), bias=bias)\n')
rfhd.write('heatmap.2(m, col = cr(n), breaks=breaks, trace="none", cellnote=mc, notecol="black", notecex=1.8, keysize=0.5, density.info="histogram", margins=c(27.0,27.0), cexRow=2.20, cexCol=2.20, revC=T, symm=T)\n')
else:
rfhd.write('''
panel.plot <- function( x,y, ... )
{
par(new=TRUE)
m <- cbind(x,y)
plot(m,col=densCols(m),pch=20)
lines(lowess(m[!is.na(m[,1])&!is.na(m[,2]),]),col="red")
}
panel.cor <- function(x, y, digits=2, prefix="", cex.cor, ...)
{
usr <- par("usr"); on.exit(par(usr))
par(usr = c(0, 1, 0, 1))
r <- cor(x, y,use="complete.obs")
txt <- format(c(r, 0.123456789), digits=digits)[1]
txt <- paste(prefix, txt, sep="")
if(missing(cex.cor)) cex.cor <- 0.8/strwidth(txt)
text(0.5, 0.5, txt, cex = cex.cor * abs(r))
}
''')
# rfhd.write("bitmap(\"%s.bmp\",width=%d,height=%d)\n" % (options.rfile,options.imgsize,options.imgsize))
labels = ",".join(map(lambda x:"\""+x+"\"",wiglabel))
rfhd.write('''
pairs(c, lower.panel=panel.plot, upper.panel=panel.cor, labels=c(%s))
''' % (labels))
rfhd.write("dev.off()\n")
rfhd.close()
# try to call R
try:
subprocess.call(['Rscript',options.rfile])
except:
info("Please check %s" % options.rfile)
else:
info("Please check %s" % (options.rfile+'.bmp'))
def main():
usage = "usage: %prog [options] <-r rfile> <-b bed file> <-w wiggle file>(>=2)"
description = """Draw correlation plot for many wiggle files at regions by a bed file.
Method: It will calculate a value for each region defined in a bed
file based on each wiggle files. The method can be chosen from -m
option.
"""
optparser = OptionParser(version="%prog 0.1",
description=description,
usage=usage,
add_help_option=False)
optparser.add_option("-h",
"--help",
action="help",
help="Show this help message and exit.")
optparser.add_option("-d",
"--db",
type="str",
dest="dbname",
help="UCSC db name for the assembly. Default: ce4",
default="ce4")
optparser.add_option("-z",
"--imgsize",
dest="imgsize",
type="int",
help="image size. default: 10, minimal: 10",
default=10)
optparser.add_option("-f",
"--format",
dest="imgformat",
type="string",
help="image format. PDF or PNG",
default='PDF')
optparser.add_option(
"-m",
"--method",
dest="method",
type="string",
default="median",
help=
"method to process the paired two sets of data in the sampling step. Choices are 'median', 'mean', and 'sample' (just take one point out of a data set). Default: median"
)
optparser.add_option("-r",
"--rfile",
dest="rfile",
help="R output file. If not set, do not save R file.")
optparser.add_option(
"-b",
"--bed",
dest="bed",
type="string",
help="the bed file you want to include in the calculation.")
optparser.add_option(
"-w",
"--wig",
dest="wig",
type="string",
action="append",
help=
"the wiggle file you want to include in the calculation. This option should be used for at least twice."
)
optparser.add_option(
"-l",
"--wig-label",
dest="wiglabel",
type="string",
action="append",
help=
"the wiggle file labels in the figure. No space is allowed. This option should be used same times as -w option, and please input them in the same order as -w option. default: will use the wiggle file filename as labels."
)
optparser.add_option(
"--min-score",
dest="minscore",
type="float",
default=0,
help=
"minimum score included in calculation. Points w/ score lower than this will be discarded."
)
optparser.add_option(
"--max-score",
dest="maxscore",
type="float",
default=10000,
help=
"maximum score included in calculation. Points w/ score larger than this will be discarded."
)
optparser.add_option(
"-H",
"--heatmap",
dest="heatmap",
action="store_true",
default=False,
help=
"If True, a heatmap image will be generated instead of paired scatterplot image."
)
(options, args) = optparser.parse_args()
imgfmt = options.imgformat.upper()
if imgfmt != 'PDF' and imgfmt != 'PNG':
print "unrecognized format: %s" % imgfmt
sys.exit(1)
method = options.method.lower()
if method == 'median':
medfunc = median
elif method == 'mean':
medfunc = mean
elif method == 'sample':
medfunc = lambda u: u[-1]
else:
print "unrecognized method: %s" % (method)
sys.exit(1)
# must provide >=2 wiggle files
if not options.wig or len(
options.wig) < 2 or not options.rfile or not options.bed:
optparser.print_help()
sys.exit(1)
# wig labels
if options.wiglabel and len(options.wiglabel) == len(options.wig):
wiglabel = options.wiglabel
else: # or use the filename
wiglabel = map(lambda x: os.path.basename(x), options.wig)
wigfilenum = len(options.wig)
# check the files
if not os.path.isfile(options.bed):
error("%s is not valid!" % options.bed)
sys.exit(1)
for f in options.wig:
if not os.path.isfile(f):
error("%s is not valid!" % f)
sys.exit(1)
wigfhds = map(open, options.wig) # file handlers for wiggle files
info("number of wiggle files: %d" % wigfilenum)
# get chromosome length info from UCSC
info("connect to UCSC to get chromosome length information")
try:
chrom_len = get_chrom_length(options.dbname)
except:
error("Error!")
sys.exit(1)
# get the common chromosome list:
chromsdict = {}
for wigfhd in wigfhds:
for l in wigfhd:
if l.find("chrom=") != -1:
c = re.search("chrom=(\w+)", l).group(1)
chromsdict[c] = chromsdict.setdefault(c, 0) + 1
chroms = []
for c in chromsdict.keys():
if chromsdict[c] == wigfilenum:
chroms.append(c)
info("common chromosomes are %s..." % ",".join(chroms))
# open the R script file handler
rfhd = open(options.rfile, "w")
rfhd.write('''
require("RColorBrewer") ## from CRAN
''')
info("read bed file %s" % os.path.basename(options.bed))
bedregion = BedIO.parse_BED(open(options.bed, 'r'))
# for each wig file, sample...
for i in range(len(wigfhds)):
wigfhd = wigfhds[i]
wigfhd.seek(0) # reset
info("read wiggle track from wiggle file #%d" % (i + 1))
bk = WiggleIO.WiggleIO(wigfhd).build_binKeeper(chromLenDict=chrom_len)
p = bedregion.extract_binkeepers(bk, func=medfunc)
info("write values to r file")
rfhd.write("p%d <- c(" % i)
if p[0]:
rfhd.write("%f" % p[0])
else:
rfhd.write("NA")
for v in p[1:]:
if v:
rfhd.write(",%f" % v)
else:
rfhd.write(",NA")
rfhd.write(")\n")
rfhd.write("c <- cbind(p0")
for i in range(wigfilenum - 1):
rfhd.write(",p%d" % (i + 1))
rfhd.write(")\n")
rfhd.write("c <- c[ c[,1]<=%f & c[,1]>=%f " %
(options.maxscore, options.minscore))
for i in range(wigfilenum - 1):
rfhd.write("& c[,%d]<=%f & c[,%d]>=%f " %
(i + 2, options.maxscore, i + 2, options.minscore))
rfhd.write(",]\n")
if imgfmt == 'PDF':
rfhd.write("pdf(\"%s.pdf\",width=%d,height=%d)\n" %
(options.rfile, options.imgsize, options.imgsize))
elif imgfmt == 'PNG':
rfhd.write(
"png(\"%s.png\",units=\"in\",res=150,width=%d,height=%d)\n" %
(options.rfile, options.imgsize, options.imgsize))
if options.heatmap:
rfhd.write('library(gplots)\n')
rfhd.write('''
m <- cor(c, method="pearson", use="pairwise.complete.obs")
''')
labels = ",".join(map(lambda x: "\"" + x + "\"", wiglabel))
rfhd.write("rownames(m) <- c(%s)\n" % labels)
rfhd.write("colnames(m) <- c(%s)\n" % labels)
rfhd.write('# draw the heatmap using gplots heatmap.2\n')
# rfhd.write('bitmap("%s.bmp",width=%d,height=%d)\n' % (options.rfile,options.imgsize,options.imgsize))
rfhd.write('mn <- -1\n')
rfhd.write('mx <- 1\n')
rfhd.write('n <- 98\n')
rfhd.write('bias <- 1\n')
rfhd.write('mc <- matrix(as.character(round(m, 2)), ncol=dim(m)[2])\n')
rfhd.write('breaks <- seq(mn, mx, (mx-mn)/(n))\n')
rfhd.write(
'cr <- colorRampPalette(colors = c("#2927FF","#FFFFFF","#DF5C5C"), bias=bias)\n'
)
rfhd.write(
'heatmap.2(m, col = cr(n), breaks=breaks, trace="none", cellnote=mc, notecol="black", notecex=1.8, keysize=0.5, density.info="histogram", margins=c(27.0,27.0), cexRow=2.20, cexCol=2.20, revC=T, symm=T)\n'
)
else:
rfhd.write('''
panel.plot <- function( x,y, ... )
{
par(new=TRUE)
m <- cbind(x,y)
plot(m,col=densCols(m),pch=20)
lines(lowess(m[!is.na(m[,1])&!is.na(m[,2]),]),col="red")
}
panel.cor <- function(x, y, digits=2, prefix="", cex.cor, ...)
{
usr <- par("usr"); on.exit(par(usr))
par(usr = c(0, 1, 0, 1))
r <- cor(x, y,use="complete.obs")
txt <- format(c(r, 0.123456789), digits=digits)[1]
txt <- paste(prefix, txt, sep="")
if(missing(cex.cor)) cex.cor <- 0.8/strwidth(txt)
text(0.5, 0.5, txt, cex = cex.cor * abs(r))
}
''')
# rfhd.write("bitmap(\"%s.bmp\",width=%d,height=%d)\n" % (options.rfile,options.imgsize,options.imgsize))
labels = ",".join(map(lambda x: "\"" + x + "\"", wiglabel))
rfhd.write('''
pairs(c, lower.panel=panel.plot, upper.panel=panel.cor, labels=c(%s))
''' % (labels))
rfhd.write("dev.off()\n")
rfhd.close()
# try to call R
try:
subprocess.call(['Rscript', options.rfile])
except:
info("Please check %s" % options.rfile)
else:
info("Please check %s" % (options.rfile + '.bmp'))
