기존 aligner의 error rates, speed, length limitation 및 biaes등의 한계를 개선하였다.
공인되어 많이 사용되어 지고 있는 타 RNAseq aligner에 비해 수십/수백배까지 빠른 속도로 mappging이 수행됨과 동시에 정확성, biases, canonical junction, chimeric, full-length RNA sequence에 대해 개선된 결과를 제공한다.
(input이 gzipped files (*.gz) 압축인 경우, --readFilesCommand zcat 또는 --readFilesCommand gzip -c 옵션사용)
The basic options to run a mapping job are as follows: #
--runThreadN NumberOfThreads
--genomeDir /path/to/genomeDir
--readFilesIn /path/to/read1 [/path/to/read2 ]
--runThreadN option defines the number of threads to be used for genome generation, it has to be set to the number of available cores on the server node.
--genomeDir specifies path to the genome directory where genome indices where generated
--readFilesIn name(s) (with path) of the files containing the sequences to be mapped (e.g.RNA-seq FASTQ files). If using Illumina paired-end reads, the read1 and read2 files have to be supplied. STAR can process both FASTA and FASTQ files. Multi-line (i.e. sequence split in multiple lines) FASTA file are supported. If the read files are compressed, use the
--readFilesCommand UncompressionCommand option, where UncompressionCommand is the un-compression command that takes the file name as input parameter, and sends the uncompressed output to stdout. For example, for gzipped files (*.gz) use --readFilesCommand zcat OR --readFilesCommand gzip -c. For bzip2-compressed files, use --readFilesCommand bzip2 -c.
