Hello all -- my bioinformatics experience is mostly with mapping Illumina reads (to mammalian transcriptomes) using STAR. But lately my group is starting to do more work with long-read sequencing, on both PacBio and Nanopore platforms, and I'm gradually getting familiar with how to map such data. So far I've been using either the GMAP or minimap2 aligners.
My question is about setting an alignment threshold, in terms of a rate of errors (mismatches and/or indels) with respect to the genome reference. That is, I'd like to be able to limit the alignments I get to only those that have, say, a 95% exact match between the read and the reference, or only those reads with less than, say, 20 total mismatches.
With STAR, this can be controlled via the Output Filter options, such as "--outFilterMismatchNoverLmax" or "--outFilterMatchNminOverLread". But I can't figure out if there is any equivalent or similar command-line parameter that can be used in GMAP or minimap2. Can anyone advise me on this?
Thanks very much!
STAR -- https://github.com/alexdobin/STAR/bl...STARmanual.pdf
GMAP -- https://github.com/juliangehring/GMA.../master/README
minimap2 -- https://github.com/lh3/minimap2
Header Leaderboard Ad
Collapse
error/mismatch rate threshold for long-read alignment with GMAP or minimap2
Collapse
Announcement
Collapse
No announcement yet.
X
Latest Articles
Collapse
-
by seqadmin
The introduction of single-cell sequencing has advanced the ability to study cell-to-cell heterogeneity. Its use has improved our understanding of somatic mutations1, cell lineages2, cellular diversity and regulation3, and development in multicellular organisms4. Single-cell sequencing encompasses hundreds of techniques with different approaches to studying the genomes, transcriptomes, epigenomes, and other omics of individual cells. The analysis of single-cell sequencing data i
...-
Channel: Articles
01-24-2023, 01:19 PM -
-
by seqadminSingle-cell sequencing is a technique used to investigate the genome, transcriptome, epigenome, and other omics of individual cells using high-throughput sequencing. This technology has provided many scientific breakthroughs and continues to be applied across many fields, including microbiology, oncology, immunology, neurobiology, precision medicine, and stem cell research.
The advancement of single-cell sequencing began in 2009 when Tang et al. investigated the single-cell transcriptomes...-
Channel: Articles
01-09-2023, 03:10 PM -
ad_right_rmr
Collapse