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Laura J. Scott

dblp:38/1037 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2014
—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 › epigenomics
ChIP-seq analysis
0.212014
Broad-Enrich: functional interpretation of large sets of broad genomic regions · Bioinform. 2014
Bioinformatics and computational biology › functional genomics
functional enrichment analysis
0.212014
Broad-Enrich: functional interpretation of large sets of broad genomic regions · Bioinform. 2014

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

gene locus coverage · 0.2false-positive rate calibration · 0.2
YearPublicationVenuePosition
2014 Broad-Enrich: functional interpretation of large sets of broad genomic regions
abstract
MOTIVATION: Functional enrichment testing facilitates the interpretation of Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) data in terms of pathways and other biological contexts. Previous methods developed and used to test for key gene sets affected in ChIP-seq experiments treat peaks as points, and are based on the number of peaks associated with a gene or a binary score for each gene. These approaches work well for transcription factors, but histone modifications often occur over broad domains, and across multiple genes. RESULTS: To incorporate the unique properties of broad domains into functional enrichment testing, we developed Broad-Enrich, a method that uses the proportion of each gene's locus covered by a peak. We show that our method has a well-calibrated false-positive rate, performing well with ChIP-seq data having broad domains compared with alternative approaches. We illustrate Broad-Enrich with 55 ENCODE ChIP-seq datasets using different methods to define gene loci. Broad-Enrich can also be applied to other datasets consisting of broad genomic domains such as copy number variations. AVAILABILITY AND IMPLEMENTATION: http://broad-enrich.med.umich.edu for Web version and R package. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Raymond G. Cavalcante, Chee Lee, Ryan P. Welch, Snehal Patil, Terry E. Weymouth, Laura J. Scott, Maureen A. Sartor
Bioinform.6