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Data on Bioinformatics Described by Researchers at University of California (RNA-Skim: a rapid method for RNA-Seq quantification at transcript level)

August 5, 2014

By a News Reporter-Staff News Editor at Information Technology Newsweekly -- Research findings on Bioinformatics are discussed in a new report. According to news reporting out of Los Angeles, California, by VerticalNews editors, research stated, "RNA-Seq technique has been demonstrated as a revolutionary means for exploring transcriptome because it provides deep coverage and base pair-level resolution. RNA-Seq quantification is proven to be an efficient alternative to Microarray technique in gene expression study, and it is a critical component in RNA-Seq differential expression analysis."

Our news journalists obtained a quote from the research from the University of California, "Most existing RNA-Seq quantification tools require the alignments of fragments to either a genome or a transcriptome, entailing a time-consuming and intricate alignment step. To improve the performance of RNA-Seq quantification, an alignment- free method, Sailfish, has been recently proposed to quantify transcript abundances using all k-mers in the transcriptome, demonstrating the feasibility of designing an efficient alignment-free method for transcriptome quantification. Even though Sailfish is substantially faster than alternative alignment-dependent methods such as Cufflinks, using all k-mers in the transcriptome quantification impedes the scalability of the method. We propose a novel RNA-Seq quantification method, RNA-Skim, which partitions the transcriptome into disjoint transcript clusters based on sequence similarity, and introduces the notion of sig-mers, which are a special type of k-mers uniquely associated with each cluster. We demonstrate that the sig-mer counts within a cluster are sufficient for estimating transcript abundances with accuracy comparable with any state-of-the-art method. This enables RNA-Skim to perform transcript quantification on each cluster independently, reducing a complex optimization problem into smaller optimization tasks that can be run in parallel. As a result, RNA-Skim uses

According to the news editors, the research concluded: "It is able to finish transcriptome quantification in 100 speedup over the state-of-the-art alignment-based methods, while delivering comparable or higher accuracy."

For more information on this research see: RNA-Skim: a rapid method for RNA-Seq quantification at transcript level. Bioinformatics, 2014;30(12):283-292. Bioinformatics can be contacted at: Oxford Univ Press, Great Clarendon St, Oxford OX2 6DP, England. (Oxford University Press -; Bioinformatics -

Our news journalists report that additional information may be obtained by contacting Z.J. Zhang, University of California, Dept. of Comp Sci, Los Angeles, CA 90024, United States.

Keywords for this news article include: California, Los Angeles, United States, Bioinformatics, North and Central America

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Source: Information Technology Newsweekly

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