Demo Data from VLDB 2026 / reviewers in the wild / expert
Alison E. Wright
dblp:250/0787
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2019
—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 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › statistical genetics › genotype calling
genotype likelihood estimation |
0.4 | 1 | 2019 | ngsLD: evaluating linkage disequilibrium using genotype likelihoods · Bioinform. 2019 |
Bioinformatics and computational biology › population genetics
linkage disequilibrium |
0.4 | 1 | 2019 | ngsLD: evaluating linkage disequilibrium using genotype likelihoods · Bioinform. 2019 |
Bioinformatics and computational biology
population genetics |
0.4 | 1 | 2019 | ngsLD: evaluating linkage disequilibrium using genotype likelihoods · Bioinform. 2019 |
Bioinformatics and computational biology
genomics |
0.1 | 1 | 2019 | ngsLD: evaluating linkage disequilibrium using genotype likelihoods · Bioinform. 2019 |
Bioinformatics and computational biology › sequence analysis › sequencing data analysis
low-coverage sequencing analysis |
0.1 | 1 | 2019 | ngsLD: evaluating linkage disequilibrium using genotype likelihoods · Bioinform. 2019 |
Methods — techniques the papers use, named apart from their topics
maximum likelihood estimation · 0.4genotype likelihood · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | ngsLD: evaluating linkage disequilibrium using genotype likelihoodsabstractMOTIVATION: Linkage disequilibrium (LD) measures the correlation between genetic loci and is highly informative for association mapping and population genetics. As many studies rely on called genotypes for estimating LD, their results can be affected by data uncertainty, especially when employing a low read depth sequencing strategy. Furthermore, there is a manifest lack of tools for the analysis of large-scale, low-depth and short-read sequencing data from non-model organisms with limited sample sizes. RESULTS: ngsLD addresses these issues by estimating LD directly from genotype likelihoods in a fast, reliable and user-friendly implementation. This method makes use of the full information available from sequencing data and provides accurate estimates of linkage disequilibrium patterns compared with approaches based on genotype calling. We conducted a case study to investigate how LD decays over physical distance in two avian species. AVAILABILITY AND IMPLEMENTATION: The methods presented in this work were implemented in C/C and are freely available for non-commercial use from https://github.com/fgvieira/ngsLD. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Emma A. Fox, Alison E. Wright, Matteo Fumagalli 0002, Filipe G. Vieira |
Bioinform. | 2 |