Align sequencing reads to long reference sequences using HISAT2.
This App aligns the sequencing reads from a read library or a sample set of reads to long reference sequences of an assembly or a genome using HISAT2 and outputs a corresponding alignment (set) in BAM format.
In addition, it outputs the Qualimap-generated BAM QC report for the alignment (set) which includes a global and individual sample-wise summary of number of mapped reads, coverage, GC-content, mapping quality, etc. in tabular format, and various plots such as PCA and coverage histograms to visualize the tabular data.
HISAT2 is essentially a successor of TopHat2, and it is relatively faster and more sensitive while still maintaining low memory requirements. The HISAT2 index is based on the FM Index of Ferragina and Manzini, which in turn is based on the Burrows-Wheeler transform. The algorithm used to build the index is based on the blockwise algorithm of Karkkainen.
Team members who implemented algorithm in KBase: Srividya Ramakrishnan, Sunita Kumari, Shinjae Yoo, Priya Ranjan, Jim Thomason, and Vivek Kumar. For questions, please contact us.
- Kim D, Langmead B, Salzberg SL. HISAT: a fast spliced aligner with low memory requirements. Nature Methods. 2015;12: 357 360. doi:10.1038/nmeth.3317 , https://www.nature.com/articles/nmeth.3317
- Kim D, Pertea G, Trapnell C, Pimentel H, Kelley R, Salzberg SL. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biology. 2013;14: R36. doi:10.1186/gb-2013-14-4-r36 , https://genomebiology.biomedcentral.com/articles/10.1186/gb-2013-14-4-r36
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