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Wanseon Lee

dblp:41/9423 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2018
0000-0002-2881-8184ORCID · reported

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 › gene expression analysis › gene expression quantification
allele-specific expression
0.312018
AltHapAlignR: improved accuracy of RNA-seq analyses through the use of alternative haplotypes · Bioinform. 2018
Bioinformatics and computational biology › transcriptomics
RNA-seq analysis
0.312018
AltHapAlignR: improved accuracy of RNA-seq analyses through the use of alternative haplotypes · Bioinform. 2018

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

alternative haplotype reference mapping · 0.3
YearPublicationVenuePosition
2018 AltHapAlignR: improved accuracy of RNA-seq analyses through the use of alternative haplotypes
abstract
Motivation: Reliance on mapping to a single reference haplotype currently limits accurate estimation of allele or haplotype-specific expression using RNA-sequencing, notably in highly polymorphic regions such as the major histocompatibility complex. Results: We present AltHapAlignR, a method incorporating alternate reference haplotypes to generate gene- and haplotype-level estimates of transcript abundance for any genomic region where such information is available. We validate using simulated and experimental data to quantify input allelic ratios for major histocompatibility complex haplotypes, demonstrating significantly improved correlation with ground truth estimates of gene counts compared to standard single reference mapping. We apply AltHapAlignR to RNA-seq data from 462 individuals, showing how significant underestimation of expression of the majority of classical human leukocyte antigen genes using conventional mapping can be corrected using AltHapAlignR to allow more accurate quantification of gene expression for individual alleles and haplotypes. Availability and implementation: Source code freely available at https://github.com/jknightlab/AltHapAlignR. Supplementary information: Supplementary data are available at Bioinformatics online.
Wanseon Lee, Katharine Plant, Peter Humburg, Julian C. Knight
Bioinform.1