By default, STAR outFilterMultimapNmax parameter (read alignments will be output only if the read maps fewer than this value) is set to 10. Should that just be set to 1 if you are going to process the data with htseq-count, which discards multi-mapped reads? Is there a benefit to leaving it at 10?
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Even if you keep multimappers in the SAM output, HTseq will not count them - it recognizes the unique mappers by NH:i:1 attribute.Originally posted by id0 View PostBy default, STAR outFilterMultimapNmax parameter (read alignments will be output only if the read maps fewer than this value) is set to 10. Should that just be set to 1 if you are going to process the data with htseq-count, which discards multi-mapped reads? Is there a benefit to leaving it at 10?
Whether multimappers are useful depends on your downstream analysis. I find it useful to generate wiggle tracks separately for unique and multi-mappers, sometimes you can miss expression if you only look at unique mappers. Also, other quantification software (e.g. Cufflinks) can "rescue" multi-mappers. Typically multimappers do not occupy a lot of space, and - if needed - can be easily filtered by NH flag or the MAPQ field.
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Tumors contain complex mixtures of cell populations that evolve in response to treatment and host-specific factors. Tissue biopsies provide only static snapshots of a tumor’s state. But what if we could follow that evolution over time using a minimally invasive technique?
Liquid biopsies can detect tumor-derived material circulating in the bloodstream, providing a way to study treatment response, detect emerging resistance, and discover new biomarkers. Circulating...-
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