WebbIn addition to using one global GFM index that represents a population of human genomes, HISAT2 uses a large set of small GFM indexes that collectively cover the whole genome (each index representing a genomic region of 56 Kbp, with 55,000 indexes needed to cover the human population). WebbHISAT2 is a fast and sensitive alignment program for mapping next-generation sequencing reads (whole-genome, transcriptome, and exome sequencing data) against the general …
run_featurecounts : Count reads in bam files using featureCounts
Webb13 nov. 2013 · Reads were aligned with the hg38 human reference genome using HISAT2 (Kim et al., 2024), and those that mapped uniquely to GENCODE-annotated genes were summarized using featureCounts (Liao et al ... Webb17 aug. 2016 · Strikingly, the alignment-independent methods outperform the alignment-dependent methods for genes with <80% unique sequence (11 % of genes). At the extreme end of the scale, for genes with 1-2% unique sequence, median spearman’s rho values for the alignment-independent methods are 0.93-0.94, compared to 0.7-0.78 for … cnqmswcs
Differential gene expression analysis using DESeq2 …
Webb22 okt. 2024 · Subsequently, these clean data were mapped to the reference genome (human: GCF_000001405.39_GRCh38.p13; mouse: GCF_000001635.26_GRCm38.p6) by using HISAT2 (v2.2.1) to generate SAM files. After that, we used the featureCounts tool of subread (v2.0.1) ( 18 ) software to count the reads aligned to each gene. Webb13 nov. 2013 · We present featureCounts, a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments. … WebbHISAT2 alignment and featureCounts HISAT2 Fast and sensitive alignment program for mapping next-generation sequencing reads (both DNA and RNA) to a population of human genomes as well as to a single reference genome. Align trimmed reads to the genome sequence using HISAT2. featureCounts cnpx 150319 hopper car