Anthropogenic causes of jellyfish blooms and their direct consequences for humans: a review

  • Olafson R
  • McCubbin W
  • Kay C
 et al. 
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Abstract

Motivation: Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases.Results: To align our large (exceeding 80 billon reads) ENCODE Transcriptome RNA-seq dataset we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously un-described RNA-seq alignment algorithm which utilizes sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by more than a factor of 50 in mapping speed, aligning to the human genome 550 Million 2x76bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full length RNA sequences. Using Roche 454 sequencing of RT-PCR amplicons, we experimentally validated 1,960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy.Implementation and Availability: STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/Contact: dobin@cshl.edu

Author-supplied keywords

  • Nematostella vectensis
  • cnidaria
  • heavy metal
  • transcriptome

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Authors

  • Robert W Olafson

  • William D McCubbin

  • C M Kay

  • Ratna K Vadlamudi

  • Jaekyoon Shin

  • Rama Pal

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