i have an microRNA- seq data and I have applied a filter of >10 read counts in 90% of samples. I was wondering is it safe to say that 90 % of samples have sequencing depth of > 10 reads. Sequencing depth definition is little confusing Thanks
I have applied a filter of >10 read counts in 90% of samples.
This statement seems to have no meaning. Can you clarify?
From my interpretation this sentence is about the count table generated after performing feature counting, e.g. featurecounts, htseq-counts,... although the context in the first post is rather confusing. This filtering would say something about the read count per microRNA across and not about the samples an sich. If the entire sample would have <10 read counts that wouldn't really make sense. This looks like prefiltering (prior to differential expression analysis?).
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In which level of your analysis you are selecting ">10 read counts in 90%"? It looks to me that you are talking about filtering a gene expression matrix. Am i correct?
So The sequencing depth is another story. You can calculate the sequencing depth considering the reads aligned to the reference genome, the length of the reads of the sequencing machine (i.e. 101 for illumina) and the length of the genome of the organism you are using. Here the fromula:
original genome (G), the number of reads(N), and the average read length(L): (N*L)/G
But again, i do not think there is a link between sequencing depth and the filtering of the gene expression matrix (if that is what you are talking about).
I am working with RPM as length of microRNA is very small
Sequencing depth is rather pointless in RNA-seq since the expression profile is totally not uniform, it's more useful to talk about the total number of reads that were sequenced.
if you want to check the splicing junction, and then possible splicing events like exon skipping or intron retention, sequencing depth is quite important.
Yes, that's the local sequencing depth on that junction or for that exon and indeed that's important for discovery of the events you describe. But it's not "the sequencing depth" of the sample. Some genes will have far higher coverage than others so there is no uniform sequencing depth per samples. Just a total number of reads which is not uniformly distributed over the genome.