Biomedical Engineering Reference
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track type=wiggle_0 name='densities' color=0,0,150
variableStep chrom=chr1 span=25
4775325 20
4775375 22
4775400 22
4775425 26
4775450 26
4775475 28
4775500 28
. . .
Example of window-based read densities in
wiggle format
Figure 8.7
8.5.4 Identifying window-based peaks
GenomicTools can also be used to identify window-based peaks and to
display them as a BED track in the UCSC Genome Browser. This is achieved
using the operation 'peaks' of the genomic_scans tool. As in the 'counts'
operation in the example above, the user needs to determine the window
size and distance as well as the minimum number of reads in the window.
For each window, p-values are computed using the binomial probability. A
p-value cutoff can be enforced using the '-pval' option. The user can specify
a fi le containing control reads ('control.bed' in our example below). If no
control reads are specifi ed, the computed p-values are based on a random
background. Finally, the 'bed' operation of the genomic_regions tool is
used to convert the output to the BED format for visualization in the UCSC
Genome browser (Figure 8.8, upper track):
$ genomic_scans peaks -v -cmp -w $win_size -d $win_dist -min $min_reads
-pval 1e-05 -g genome.bed chipseq.bed control.bed | genomic_regions -bed
-t 'peaks' -c '0,150,0' > peaks.bed
$ genomic_scans peaks -v -cmp -w $win_size -d $win_dist -min $min_reads
-pval 1e-05 -g genome.bed chipseq.bed control.bed | genomic_regions -bed
-t 'peaks' -c '0,150,0' > peaks.bed
$ head peaks.bed
track name='peaks' itemRgb=On visibility=1
chr1 4775075 4775575 2.27e-09 1000 + 4775075 4775575 0,150,0
chr1 4775125 4775625 6.90e-11 1000 + 4775125 4775625 0,150,0
chr1 4775150 4775650 6.90e-11 1000 + 4775150 4775650 0,150,0
...
$ head peaks.bed
track name='peaks' itemRgb=On visibility=1
chr1 4775075 4775575 2.27e-09 1000 + 4775075 4775575 0,150,0
chr1 4775125 4775625 6.90e-11 1000 + 4775125 4775625 0,150,0
chr1 4775150 4775650 6.90e-11 1000 + 4775150 4775650 0,150,0
. . .
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