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Gabrielle Deschamps-Francoeur

dblp:255/6766 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2019
0000-0001-7129-960XORCID · verified

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

Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author

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 › sequence analysis › read mapping
multi-mapping read resolution
0.412019
CoCo: RNA-seq read assignment correction for nested genes and multimapped reads · Bioinform. 2019
Bioinformatics and computational biology › transcriptomics
RNA-seq analysis
0.412019
CoCo: RNA-seq read assignment correction for nested genes and multimapped reads · Bioinform. 2019
YearPublicationVenuePosition
2019 CoCo: RNA-seq read assignment correction for nested genes and multimapped reads
abstract
MOTIVATION: Next-generation sequencing techniques revolutionized the study of RNA expression by permitting whole transcriptome analysis. However, sequencing reads generated from nested and multi-copy genes are often either misassigned or discarded, which greatly reduces both quantification accuracy and gene coverage. RESULTS: Here we present count corrector (CoCo), a read assignment pipeline that takes into account the multitude of overlapping and repetitive genes in the transcriptome of higher eukaryotes. CoCo uses a modified annotation file that highlights nested genes and proportionally distributes multimapped reads between repeated sequences. CoCo salvages over 15% of discarded aligned RNA-seq reads and significantly changes the abundance estimates for both coding and non-coding RNA as validated by PCR and bedgraph comparisons. AVAILABILITY AND IMPLEMENTATION: The CoCo software is an open source package written in Python and available from http://gitlabscottgroup.med.usherbrooke.ca/scott-group/coco. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Gabrielle Deschamps-Francoeur, Vincent Boivin, Sherif Abou Elela, Michelle S. Scott
Bioinform.1