近乎最优的概率 RNA-seq 定量。
Near-optimal probabilistic RNA-seq quantification.
机构信息
Innovative Genomics Initiative, University of California, Berkeley, California, USA.
Department of Computer Science, University of California, Berkeley, California, USA.
出版信息
Nat Biotechnol. 2016 May;34(5):525-7. doi: 10.1038/nbt.3519. Epub 2016 Apr 4.
We present kallisto, an RNA-seq quantification program that is two orders of magnitude faster than previous approaches and achieves similar accuracy. Kallisto pseudoaligns reads to a reference, producing a list of transcripts that are compatible with each read while avoiding alignment of individual bases. We use kallisto to analyze 30 million unaligned paired-end RNA-seq reads in <10 min on a standard laptop computer. This removes a major computational bottleneck in RNA-seq analysis.
我们介绍 kallisto，这是一种 RNA-seq 定量程序，比以前的方法快两个数量级，并且具有相似的准确性。 kallisto 伪比对读取到参考基因组，生成与每个读取兼容的转录本列表，同时避免对个别碱基进行比对。我们使用 kallisto 在标准笔记本电脑上不到 10 分钟即可分析 3000 万未对齐的配对末端 RNA-seq 读取。这消除了 RNA-seq 分析中的主要计算瓶颈。
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