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Jack Humphrey

dblp:280/6423 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · unresolved

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

Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021

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 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › statistical genetics › fine-mapping
causal variant identification
0.612022
echolocatoR: an automated end-to-end statistical and functional genomic fine-mapping pipeline · Bioinform. 2022
Bioinformatics and computational biology › statistical genetics
fine-mapping
0.612022
echolocatoR: an automated end-to-end statistical and functional genomic fine-mapping pipeline · Bioinform. 2022
Bioinformatics and computational biology
functional genomics
0.612022
echolocatoR: an automated end-to-end statistical and functional genomic fine-mapping pipeline · Bioinform. 2022
Bioinformatics and computational biology › biostatistics › statistical bioinformatics
statistical genomics
0.612022
echolocatoR: an automated end-to-end statistical and functional genomic fine-mapping pipeline · Bioinform. 2022

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

quantitative trait loci · 0.6linkage disequilibrium · 0.6epigenomics · 0.6
YearPublicationVenuePosition
2022 echolocatoR: an automated end-to-end statistical and functional genomic fine-mapping pipeline
abstract
SUMMARY: echolocatoR integrates a diverse suite of statistical and functional fine-mapping tools to identify, test enrichment in, and visualize high-confidence causal consensus variants in any phenotype. It requires minimal input from users (a summary statistics file), can be run in a single R function, and provides extensive access to relevant datasets (e.g. reference linkage disequilibrium panels, quantitative trait loci, genome-wide annotations, cell-type-specific epigenomics), thereby enabling rapid, robust and scalable end-to-end fine-mapping investigations. AVAILABILITY AND IMPLEMENTATION: echolocatoR is an open-source R package available through GitHub under the GNU General Public License (Version 3) license: https://github.com/RajLabMSSM/echolocatoR. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Brian M. Schilder, Jack Humphrey, Towfique Raj
Bioinform.2