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Benjamin Rodriguez

dblp:53/5408 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2013
—ORCID · none

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 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › epigenomics › DNA methylation
DNA methylation analysis
0.212013
BSeQC: quality control of bisulfite sequencing experiments · Bioinform. 2013
Bioinformatics and computational biology › sequence analysis › sequencing data processing
next-generation sequencing quality control
0.012013
BSeQC: quality control of bisulfite sequencing experiments · Bioinform. 2013

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

bias trimming · 0.2SAM/BAM processing · 0.2
YearPublicationVenuePosition
2013 BSeQC: quality control of bisulfite sequencing experiments
abstract
MOTIVATION: Bisulfite sequencing (BS-seq) has emerged as the gold standard to study genome-wide DNA methylation at single-nucleotide resolution. Quality control (QC) is a critical step in the analysis pipeline to ensure that BS-seq data are of high quality and suitable for subsequent analysis. Although several QC tools are available for next-generation sequencing data, most of them were not designed to handle QC issues specific to BS-seq protocols. Therefore, there is a strong need for a dedicated QC tool to evaluate and remove potential technical biases in BS-seq experiments. RESULTS: We developed a package named BSeQC to comprehensively evaluate the quality of BS-seq experiments and automatically trim nucleotides with potential technical biases that may result in inaccurate methylation estimation. BSeQC takes standard SAM/BAM files as input and generates bias-free SAM/BAM files for downstream analysis. Evaluation based on real BS-seq data indicates that the use of the bias-free SAM/BAM file substantially improves the quantification of methylation level. AVAILABILITY AND IMPLEMENTATION: BSeQC is freely available at: http://code.google.com/p/bseqc/.
Xueqiu Lin, Deqiang Sun, Benjamin Rodriguez, Hanfei Sun, Yong Zhang 0006, Wei Li 0036
Bioinform.3