I guess that this is custom code. Given that you have methylation calls for individual CpGs, you might bin the gene into fractions of, say 0.01 so 1%-wise, and then average the methylation status of the CpGs per bin (be it binary - met or unmet, or averaging the methylation percentage per CpG). I would probably implement this using the R GenomicRanges and use its intersection functions for the downstream. Keep in mind that genes have extreme differences in length, ranging from like 3kb (CEBPA) over like 38kb (UBXN11) or 101kb (VOPP1) to up to 2Mb (DMD), so the question is how informative a plot like this is, especially because no information about the variances are provided (the last sentence is just thinking aloud).
II need your advice I am analyzing by WBGS (whole genome bisulfite sequencing) the genome of my plant under two conditions with 3 biological replicates …
In my RNA sequencing fastqc report, I consistently notice an abnormally high A (green) peak in session "Per base sequence content". See images below. I …
Hi everyone. I'm analysing the H3K9me3 ChIP from the ChIP experiment I've conducted. However, the bioinformatic parts were did by a labmate who understand programming …
**We have encountered strange pattern in bam file that is generated from amplicon sequencing. (Nextera XT, illumina MiSeq).** As you can see at the middle …
https://github.com/shenlab-sinai/ngsplot
deepTools plot profile.
I guess that this is custom code. Given that you have methylation calls for individual CpGs, you might bin the gene into fractions of, say 0.01 so 1%-wise, and then average the methylation status of the CpGs per bin (be it binary - met or unmet, or averaging the methylation percentage per CpG). I would probably implement this using the R
GenomicRangesand use its intersection functions for the downstream. Keep in mind that genes have extreme differences in length, ranging from like 3kb (CEBPA) over like 38kb (UBXN11) or 101kb (VOPP1) to up to 2Mb (DMD), so the question is how informative a plot like this is, especially because no information about the variances are provided (the last sentence is just thinking aloud).