Dear deeptools developer,

Thanks for developing such a great tool! I recently ran a Cut & Tag experiment(2 X 150bp) and want to use the plots from deeptools to show the signal distribution of different histone markers on TSS regions. However, I got different results when I used "extendReads" or not in bamCoverage function with BPM normalization. Please see the plot shown below:

The plot showed that the male sample (the "m" in the sample name) has a higher reads intensity than female sample (the "f" in the sample name) when I used extendReads, but the direction is opposite when I deactivated extendReads. I thought it was possibly caused by the quantification issue that the mate reads in properly paired reads were quantified twice. So I included "--samFlagInclude 66" in bamCoverage to quantify the mate reads only once with extendReads activated. However, the result showed similar as the one activating extendReads without samFlagInclude parameter (see below):

I am wondering why "extendReads" caused so much different results? This is important since it would results in different interpretation for biology.

deeptools version: 3.5.1 python version: 3.9.13

Here are the codes:

###with extendReads activated
bamCoverage --bam <sample>.bam -o <sample>.extent.bw --ignoreDuplicates --normalizeUsing BPM --blackListFileName ../blacklist.merge.bed --binSize 10 --ignoreForNormalization chrX chrY chrM --extendReads

###with extendReads deactivated
bamCoverage --bam <sample>.bam -o <sample>.extent.bw --ignoreDuplicates --normalizeUsing BPM --blackListFileName ../blacklist.merge.bed --binSize 10 --ignoreForNormalization chrX chrY chrM

###with samFlagInclude 66
bamCoverage --bam <sample>.bam -o <sample>.extent_samflag66.bw --ignoreDuplicates --normalizeUsing BPM --blackListFileName ../blacklist.merge.bed --binSize 10 --ignoreForNormalization chrX chrY chrM

###computeMatrix codes
computeMatrix reference-point --referencePoint TSS -p 20 -b 2500 -a 2500 -R <region>.bed -S <sample>.bw --missingDataAsZero -o <output>.gz

I look forward to your reply! Many thanks in advance!!

Joe Wang