bigwig-nim includes a command-line tool distributed as a static binary here. It supports converting bed to bigwig and bigwig to bed and extracting stats (mean, coverage, etc) for regions in a bigwig.
There are other tools to do this, including kentTools which has a more restrictive license and does not supported (b)gzipped input and bwtools which seems to provide similar functionality (but I am not able to build it).
To convert a bed with the value in the 4th column to bigwig, use:
bigwig view $bed_in --value-column 4 --chrom-sizes $fai -O bigwig -o $bigwig_out
bigwig
will automatically determine the best data format for each block (fixed span and step or per-base) most of the
CPU time is spent parsing the input bed file.
To get the mean value for a given region (in this case on chromosome 22)
bigwig stats --stat mean $bigwig 22:145000-155000
# or a bed file or regions
bigwig stats --stat mean $bigwig $bed
Output is tab-delimited chrom
, start
, stop
, stat
for each row in the bed (or just once for the region).
The supported stats are mean
, min
, max
, coverage
, sum
with a special-case for the stat of header
which
shows the chromosomes, lengths and mean coverages for each chromosome in the bigwig file.
var bw: BigWig
bw.open(path, fmRead)
# avoid allocating when possible
var values: seq[float32]
bw.values(values, "chr1", 0, 2222)
for iv in bw.intervals("chr2", 999, 88888): # iterator.
# tuple[start: int, stop: int, value: float32]
# for bigbed
for iv in bw.entries("chr2", 999, 88888): # iterator.
# tuple[start: int, stop: int, value: cstring]
# value contains "SQL" for bigbed entry.
# single value
var m: seq[float32] = bw.stats("chr2", 999, 9999, stat=Stat.mean)
# multiple bins:
var L: seq[float32] = bw.stats("chr2", 999, 9999, stat=Stat.min, nBins=10)
echo bw.header # @[(name: "1", length: 195471971, tid: 0'u32), (name: "10", length: 130694993, tid: 1'u32)]
bw.close
var wtr:BigWig
doAssert wtr.open("tests/writer.bw", fmWrite)
wtr.setHeader(@[(name:"chr1", length: 2000, tid: 0'u32)])
wtr.writeHeader
# add intervals with tuples
wtr.add("chr1", @[(start: 22, stop: 33, value: 0.01'f32), (start: 44, stop: 55, value: 155'f32)])
# or with, for example a span of 15 bases:
wtr.add("chr1", 15, @[(start: 20, value: 0.01'f32), (start: 30, value: 155'f32)])
# or an array of values with a given span and step:
var values = @[0.1'f32, 0.2, 0.3, 0.4]
wtr.add("chr1", 100, values, span=100, step=200) # 100-200 is 0.1, 300-400 is 0.2 ...
wtr.close()