Optimizing RNA-Seq Mapping with STAR

Sequencing of transcribed RNA molecules (RNA-seq) is an invaluable tool for studying cell transcriptomes at high resolution and depth. RNA-seq datasets typically consist of tens to hundreds of millions of relatively short (30–200 nt) sequence fragments of the original RNA transcripts. The very first step in a typical RNA-seq analysis pipeline is mapping (alignment) of the short reads to a reference genome. The large number of reads, as well as large genome sizes of many important species, makes this task very computationally intensive. The RNA transcripts are often spliced, requiring mapping to noncontiguous regions of the genome. This creates a unique challenge for the RNA-seq mapping, both in terms of speed and accuracy. The STAR RNA-seq mapper was developed to overcome these challenges and enable highly accurate spliced reads alignment at ultrafast speed. STAR is feature-rich software, capable of detecting annotated and novel splice junctions, as well as chimeric and circular RNA. Because of its ability to map spliced sequences of any length with moderate error rate, STAR provides scalability for emerging sequencing technologies. In addition to standard SAM/BAM output, STAR can generate various other data files useful for downstream analyses such as transcript/gene expression quantification, differential gene expression, novel isoform reconstruction, signal visualization , etc.

Availability – The latest release of STAR software can be downloaded from https://​github.​com/​alexdobin/​STAR/​releases. The releases include the pre-compiled STAR executables for Linux and Mac OS X, as well as instructions on how to compile STAR from the source code.

Question about STAR usage should be asked on the STAR user discussion group: https://groups.google.com/forum/#!forum/rna-starhttps://groups.google.com/forum/#!forum/rna-star.

Dobin A, Gingeras TR. (2016) Optimizing RNA-Seq Mapping with STAR. Methods Mol Biol 1415:245-62. [abstract]

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