Literature DB >> 17267431

Large scale genotype-phenotype correlation analysis based on phylogenetic trees.

Farhat Habib1, Andrew D Johnson, Ralf Bundschuh, Daniel Janies.   

Abstract

We provide two methods for identifying changes in genotype that are correlated with changes in a phenotype implied by phylogenetic trees. The first method, VENN, works when the number of branches over which the change occurred are modest. VENN looks for genetic changes that are completely penetrant with phenotype changes on a tree. The second method, CCTSWEEP, allows for a partial matching between changes in phenotypes and genotypes and provides a score for each change using Maddison's concentrated changes test. The mutations that are highly correlated with phenotypic change can be ranked by score. We use these methods to find SNPs correlated with resistance to Bacillus anthracis in inbred mouse strains. Our findings are consistent with the current biological literature, and also suggest potential novel candidate genes.

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Year:  2007        PMID: 17267431     DOI: 10.1093/bioinformatics/btm003

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  8 in total

1.  Cladograms with Path to Event (ClaPTE): a novel algorithm to detect associations between genotypes or phenotypes using phylogenies.

Authors:  Samuel K Handelman; Jacob M Aaronson; Michal Seweryn; Igor Voronkin; Jesse J Kwiek; Wolfgang Sadee; Joseph S Verducci; Daniel A Janies
Journal:  Comput Biol Med       Date:  2014-12-24       Impact factor: 4.589

2.  US and Scottish health professionals' attitudes toward DNA biobanking.

Authors:  David A Leiman; Nancy M Lorenzi; Jeremy C Wyatt; Alex S F Doney; S Trent Rosenbloom
Journal:  J Am Med Inform Assoc       Date:  2008-02-28       Impact factor: 4.497

3.  PhenoLink--a web-tool for linking phenotype to ~omics data for bacteria: application to gene-trait matching for Lactobacillus plantarum strains.

Authors:  Jumamurat R Bayjanov; Douwe Molenaar; Vesela Tzeneva; Roland J Siezen; Sacha A F T van Hijum
Journal:  BMC Genomics       Date:  2012-05-04       Impact factor: 3.969

Review 4.  Forest and Trees: Exploring Bacterial Virulence with Genome-wide Association Studies and Machine Learning.

Authors:  Jonathan P Allen; Evan Snitkin; Nathan B Pincus; Alan R Hauser
Journal:  Trends Microbiol       Date:  2021-01-14       Impact factor: 18.230

Review 5.  Explaining microbial phenotypes on a genomic scale: GWAS for microbes.

Authors:  Bas E Dutilh; Lennart Backus; Robert A Edwards; Michiel Wels; Jumamurat R Bayjanov; Sacha A F T van Hijum
Journal:  Brief Funct Genomics       Date:  2013-04-26       Impact factor: 4.241

6.  GWAMAR: genome-wide assessment of mutations associated with drug resistance in bacteria.

Authors:  Michal Wozniak; Jerzy Tiuryn; Limsoon Wong
Journal:  BMC Genomics       Date:  2014-12-12       Impact factor: 3.969

7.  An approach to identifying drug resistance associated mutations in bacterial strains.

Authors:  Michal Wozniak; Jerzy Tiuryn; Limsoon Wong
Journal:  BMC Genomics       Date:  2012-12-13       Impact factor: 3.969

Review 8.  Current Affairs of Microbial Genome-Wide Association Studies: Approaches, Bottlenecks and Analytical Pitfalls.

Authors:  James Emmanuel San; Shakuntala Baichoo; Aquillah Kanzi; Yumna Moosa; Richard Lessells; Vagner Fonseca; John Mogaka; Robert Power; Tulio de Oliveira
Journal:  Front Microbiol       Date:  2020-01-30       Impact factor: 5.640

  8 in total

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