Demo Data from EDBT 2026 / reviewers in the wild / expert
Emil Jørsboe
dblp:209/7686
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2017
0000-0002-0593-7906ORCID · 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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › population genetics
admixture analysis |
0.3 | 1 | 2017 | fastNGSadmix: admixture proportions and principal component analysis of a single NGS sample · Bioinform. 2017 |
Bioinformatics and computational biology
population genetics |
0.3 | 1 | 2017 | fastNGSadmix: admixture proportions and principal component analysis of a single NGS sample · Bioinform. 2017 |
Methods — techniques the papers use, named apart from their topics
gibbs sampling · 0.3genotype likelihood · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | fastNGSadmix: admixture proportions and principal component analysis of a single NGS sampleabstractMOTIVATION: Estimation of admixture proportions and principal component analysis (PCA) are fundamental tools in populations genetics. However, applying these methods to low- or mid-depth sequencing data without taking genotype uncertainty into account can introduce biases. RESULTS: Here we present fastNGSadmix, a tool to fast and reliably estimate admixture proportions and perform PCA from next generation sequencing data of a single individual. The analyses are based on genotype likelihoods of the input sample and a set of predefined reference populations. The method has high accuracy, even at low sequencing depth and corrects for the biases introduced by small reference populations. AVAILABILITY AND IMPLEMENTATION: The admixture estimation method is implemented in C ++ and the PCA method is implemented in R. The code is freely available at http://www.popgen.dk/software/index.php/FastNGSadmix. CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Emil Jørsboe, Kristian Hanghøj, Anders Albrechtsen |
Bioinform. | 1 |