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2 hours ago by

Hello everyone
I have bigwig files of normalized Tn5 insertions . I also have atac seq peaks of the same samples. I was wondering if it is possible to get coverages for atac seq peaks in R using only bigwigs and peaks.

bigwig sample:

"seqnames"  "start" "end"   "width" "strand"    "score"
"1" "chr1"  1   9999    9999    "*" 0
"2" "chr1"  10000   10099   100 "*" 17.7165222167969
"3" "chr1"  10100   10199   100 "*" 30.6012668609619
"4" "chr1"  10200   10299   100 "*" 9.66355800628662
"5" "chr1"  10300   10399   100 "*" 4.83177900314331
"6" "chr1"  10400   10499   100 "*" 8.05296516418457
"7" "chr1"  10500   10699   200 "*" 3.22118592262268
"8" "chr1"  10700   13199   2500    "*" 0

atac seq peaks :

seqnames    start   end name    score   annotation  percentGC   percentAT
chr1    975451  975952  BRCA_39 1.87842575038562    3' UTR  0.6187624750499 0.3812375249501
chr1    1014228 1014729 BRCA_55 4.07469686212787    3' UTR  0.62874251497006    0.37125748502994
chr1    1290080 1290581 BRCA_123    2.44358820293876    3' UTR  0.678642714570858   0.321357285429142
chr1    1291099 1291600 BRCA_124    3.18019908767794    3' UTR  0.702594810379242   0.297405189620758
chr1    1291742 1292243 BRCA_125    8.26783029566134    3' UTR  0.640718562874252   0.359281437125749
chr1    1327977 1328478 BRCA_143    1.08246502080444    3' UTR  0.676646706586826   0.323353293413174
chr1    1334423 1334924 BRCA_151    3.70277788120318    3' UTR  0.634730538922156   0.365269461077844
chr1    1335198 1335699 BRCA_152    2.60759091543721    3' UTR  0.588822355289421   0.411177644710579
chr1    1352725 1353226 BRCA_166    12.7576509548536    3' UTR  0.612774451097804   0.387225548902196

here is how bigwigs were constructed :

we constructed bigwigs based on the Tn5 offset-corrected insertion sites. To do this, the genome was
binned into 100-bp intervals using “tile” in GenomicRanges of the
chromosome sizes in R. The insertion sites (GenomicRanges) were then
converted into a coverage run-length encoding using “coverage”. Then,
to determine the number of Tn5 insertions within each bin we
constructed a “Views” object and calculated the sum in each bin with
“ViewSums”. We then normalized the total number of reads by a scale
factor that converted all samples to a constant 30 million reads
within peaks. This approach simultaneously normalizes samples by their
quality and read depth, analogous to the reads in peaks normalization
within a counts matrix. This was then converted into a bigwig using
rtracklayer “export.bw” in R.

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modified 51 minutes ago

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2 hours ago
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pt.taklifi60



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