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Saravana M. Dhanasekaran

dblp:173/1982 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2016
0000-0002-0489-2224ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › transcriptomics
RNA-seq analysis
0.212016
Two-pass alignment improves novel splice junction quantification · Bioinform. 2016
Bioinformatics and computational biology › transcriptomics › RNA-seq analysis
splice junction quantification
0.212016
Two-pass alignment improves novel splice junction quantification · Bioinform. 2016
Bioinformatics and computational biology
transcriptomics
0.212016
Two-pass alignment improves novel splice junction quantification · Bioinform. 2016

Methods — techniques the papers use, named apart from their topics

two-pass alignment · 0.2STAR aligner · 0.2
YearPublicationVenuePosition
2016 Two-pass alignment improves novel splice junction quantification
abstract
MOTIVATION: Discovery of novel splicing from RNA sequence data remains a critical and exciting focus of transcriptomics, but reduced alignment power impedes expression quantification of novel splice junctions. RESULTS: Here, we profile performance characteristics of two-pass alignment, which separates splice junction discovery from quantification. Per sample, across a variety of transcriptome sequencing datasets, two-pass alignment improved quantification of at least 94% of simulated novel splice junctions, and provided as much as 1.7-fold deeper median read depth over those splice junctions. We further demonstrate that two-pass alignment works by increasing alignment of reads to splice junctions by short lengths, and that potential alignment errors are readily identifiable by simple classification. Taken together, two-pass alignment promises to advance quantification and discovery of novel splicing events. CONTACT: [email protected], [email protected] AVAILABILITY AND IMPLEMENTATION: Two-pass alignment was implemented here as sequential alignment, genome indexing, and re-alignment steps with STAR. Full parameters are provided in Supplementary Table 2. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Brendan A. Veeneman, Sudhanshu Shukla, Saravana M. Dhanasekaran, Arul M. Chinnaiyan, Alexey I. Nesvizhskii
Bioinform.3