Zobrazeno 1 - 10
of 170
pro vyhledávání: '"Genetics and Population Analysis"'
Publikováno v:
Bioinformatics
Motivation Polygenic scores (PGS) aim to genetically predict complex traits at an individual level. PGS are typically trained on genome-wide association summary statistics and require an independent test dataset to tune parameters. More recent method
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4ad312ed9b33211863cda45bc9abcc8d
https://doi.org/10.1093/bioinformatics/btab456
https://doi.org/10.1093/bioinformatics/btab456
Autor:
Kenneth Westerman, Magdalena del Rocío Sevilla-González, Duy T. Pham, Yun Ju Sung, Ye Chen, Liang Hong, Alisa K. Manning, Alanna C. Morrison, Yan V. Sun, Han Chen
Publikováno v:
Bioinformatics
Motivation Gene–environment interaction (GEI) studies are a general framework that can be used to identify genetic variants that modify the effects of environmental, physiological, lifestyle or treatment effects on complex traits. Moreover, account
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cc868598c24131677aa0a9249d89a533
https://doi.org/10.1093/bioinformatics/btab223
https://doi.org/10.1093/bioinformatics/btab223
Autor:
Peer Bork, Shinichi Sunagawa, Renato J. Alves, Roman Thielemann, Paul Igor Costea, Thea Van Rossum, Lucas Paoli
Publikováno v:
Bioinformatics
Bioinformatics, 38 (4)
Bioinformatics, 38 (4)
Taxonomic analysis of microbial communities is well supported at the level of species and strains. However, species can contain significant phenotypic diversity and strains are rarely widely shared across global populations. Stratifying the diversity
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3e0aba78392f0c09365f83adf841074d
https://doi.org/10.1093/bioinformatics/btab789
https://doi.org/10.1093/bioinformatics/btab789
Autor:
Michael DeGiorgio, Xiaoheng Cheng
Publikováno v:
Bioinformatics
Summary The growing availability of genomewide polymorphism data has fueled interest in detecting diverse selective processes affecting population diversity. However, no model-based approaches exist to jointly detect and distinguish the two complemen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4d8a0d490318968066a2feef374557bc
https://doi.org/10.1093/bioinformatics/btab720
https://doi.org/10.1093/bioinformatics/btab720
Detecting quantitative trait loci and exploring chromosomal pairing in autopolyploids using polyqtlR
Autor:
Chris Maliepaard, Richard G. F. Visser, Peter M. Bourke, Geert van Geest, Johan H. Willemsen, Roeland E. Voorrips, Marinus J. M. Smulders, Paul Arens, Christine A. Hackett
Publikováno v:
Bioinformatics (Oxford, England), 37(21), 3822-3829
Bioinformatics
Bioinformatics (Oxford, England) 37 (2021) 21
Bioinformatics
Bioinformatics (Oxford, England) 37 (2021) 21
MotivationThe investigation of quantitative trait loci (QTL) is an essential component in our understanding of how organisms vary phenotypically. However, many important crop species are polyploid (carrying more than two copies of each chromosome), r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bd6e694eb1bf742635ef28db69c0d40e
https://doi.org/10.1093/bioinformatics/btab574
https://doi.org/10.1093/bioinformatics/btab574
Publikováno v:
Bioinformatics
Motivation Expression quantitative trait loci (eQTL) harbor genetic variants modulating gene transcription. Fine mapping of regulatory variants at these loci is a daunting task due to the juxtaposition of causal and linked variants at a locus as well
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ed365776a249fba8278f6be258d45562
http://europepmc.org/articles/PMC8150140
http://europepmc.org/articles/PMC8150140
Autor:
Dacheng Tao, Frank C. Sciurba, Peng Liu, Kun Zhang, Mingming Gong, Kayhan Batmanghelich, George C. Tseng, Petar Stojanov
Publikováno v:
Bioinformatics
Motivation There is growing interest in the biomedical research community to incorporate retrospective data, available in healthcare systems, to shed light on associations between different biomarkers. Understanding the association between various ty
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9a7de34c51fcad91a0e5a957a6096a48
http://europepmc.org/articles/PMC8098021
http://europepmc.org/articles/PMC8098021
Publikováno v:
Bioinformatics
MotivationThe use of genome data for diagnosis and treatment is becoming increasingly common. Researchers need access to as many genomes as possible to interpret the patient genome, to obtain some statistical patterns and to reveal disease–gene rel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fdff9d361074514ddbe6b4f69ff92d71
http://europepmc.org/articles/PMC7850099
http://europepmc.org/articles/PMC7850099
Publikováno v:
Bioinformatics, 37 (1)
Bioinformatics
Bioinformatics
Motivation Correlating genetic loci with a disease phenotype is a common approach to improve our understanding of the genetics underlying complex diseases. Standard analyses mostly ignore two aspects, namely genetic heterogeneity and interactions bet
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d8df72b767f1b0d1926f8dc52e7fb2e4
https://doi.org/10.1093/bioinformatics/btaa581
https://doi.org/10.1093/bioinformatics/btaa581