Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

José Víctor Moreno-Mayar

dblp:152/3557 · DBLP profile ↗
← Back
2ranked-venue papers
1as first author
0since 2021 · last 2020
0000-0002-7712-4496ORCID · reported

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

Applied, interdisciplinary, general and emerging computing · 2 · 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
2 papers
Bioinformatics and computational biology · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › molecular evolution › evolutionary bioinformatics
ancient DNA analysis
0.522020
A likelihood method for estimating present-day human contamination in ancient male samples using low-depth X-chromosome data · Bioinform. 2020
bammds: a tool for assessing the ancestry of low-depth whole-genome data using multidimensional scaling (MDS) · Bioinform. 2014
Bioinformatics and computational biology › population genetics
ancestry inference
0.212014
bammds: a tool for assessing the ancestry of low-depth whole-genome data using multidimensional scaling (MDS) · Bioinform. 2014
Bioinformatics and computational biology
population genetics
0.212014
bammds: a tool for assessing the ancestry of low-depth whole-genome data using multidimensional scaling (MDS) · Bioinform. 2014

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

x-chromosome analysis · 0.4maximum likelihood · 0.4multidimensional scaling · 0.2
YearPublicationVenuePosition
2020 A likelihood method for estimating present-day human contamination in ancient male samples using low-depth X-chromosome data
abstract
MOTIVATION: The presence of present-day human contaminating DNA fragments is one of the challenges defining ancient DNA (aDNA) research. This is especially relevant to the ancient human DNA field where it is difficult to distinguish endogenous molecules from human contaminants due to their genetic similarity. Recently, with the advent of high-throughput sequencing and new aDNA protocols, hundreds of ancient human genomes have become available. Contamination in those genomes has been measured with computational methods often developed specifically for these empirical studies. Consequently, some of these methods have not been implemented and tested for general use while few are aimed at low-depth nuclear data, a common feature in aDNA datasets. RESULTS: We develop a new X-chromosome-based maximum likelihood method for estimating present-day human contamination in low-depth sequencing data from male individuals. We implement our method for general use, assess its performance under conditions typical of ancient human DNA research, and compare it to previous nuclear data-based methods through extensive simulations. For low-depth data, we show that existing methods can produce unusable estimates or substantially underestimate contamination. In contrast, our method provides accurate estimates for a depth of coverage as low as 0.5× on the X-chromosome when contamination is below 25%. Moreover, our method still yields meaningful estimates in very challenging situations, i.e. when the contaminant and the target come from closely related populations or with increased error rates. With a running time below 5 min, our method is applicable to large scale aDNA genomic studies. AVAILABILITY AND IMPLEMENTATION: The method is implemented in C++ and R and is available in github.com/sapfo/contaminationX and popgen.dk/angsd.
José Víctor Moreno-Mayar, Thorfinn Korneliussen, Jyoti Dalal, Gabriel Renaud, Anders Albrechtsen, Rasmus Nielsen, Anna-Sapfo Malaspinas
Bioinform.1
2014 bammds: a tool for assessing the ancestry of low-depth whole-genome data using multidimensional scaling (MDS)
abstract
SUMMARY: We present bammds, a practical tool that allows visualization of samples sequenced by second-generation sequencing when compared with a reference panel of individuals (usually genotypes) using a multidimensional scaling algorithm. Our tool is aimed at determining the ancestry of unknown samples-typical of ancient DNA data-particularly when only low amounts of data are available for those samples. AVAILABILITY AND IMPLEMENTATION: The software package is available under GNU General Public License v3 and is freely available together with test datasets https://savannah.nongnu.org/projects/bammds/. It is using R (http://www.r-project.org/), parallel (http://www.gnu.org/software/parallel/), samtools (https://github.com/samtools/samtools). CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Anna-Sapfo Malaspinas, Ole Tange, José Víctor Moreno-Mayar, Morten Rasmussen, Michael Degiorgio, Yong Wang 0075, Cristina E. Valdiosera, Gustavo Politis, Eske Willerslev, Rasmus Nielsen
Bioinform.3