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Ian T. Fiddes

dblp:213/7062 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · unresolved

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 › gene expression analysis › gene expression quantification
allele-specific expression		 0.412020
scHLAcount: allele-specific HLA expression from single-cell gene expression data · Bioinform. 2020
Bioinformatics and computational biology › single-cell analysis › single-cell RNA sequencing
single-cell RNA-seq analysis		 0.412020
scHLAcount: allele-specific HLA expression from single-cell gene expression data · Bioinform. 2020

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

personalized reference construction · 0.4molecule-level counting · 0.4
YearPublicationVenuePosition
2020 scHLAcount: allele-specific HLA expression from single-cell gene expression data
abstract
SUMMARY: Bulk RNA sequencing studies have demonstrated that human leukocyte antigen (HLA) genes may be expressed in a cell type-specific and allele-specific fashion. Single-cell gene expression assays have the potential to further resolve these expression patterns, but currently available methods do not perform allele-specific quantification at the molecule level. Here, we present scHLAcount, a post-processing workflow for single-cell RNA-seq data that computes allele-specific molecule counts of the HLA genes based on a personalized reference constructed from the sample's HLA genotypes. AVAILABILITY AND IMPLEMENTATION: scHLAcount is available under the MIT license at https://github.com/10XGenomics/scHLAcount. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Charlotte A. Darby, Michael J. T. Stubbington, Patrick J. Marks, Álvaro Martínez Barrio, Ian T. Fiddes
 Bioinform.5