scholarly journals Single-marker and two-marker association tests for unphased case-control genotype data, with a power comparison

2009 ◽  
pp. n/a-n/a ◽  
Author(s):  
Sulgi Kim ◽  
Nathan J. Morris ◽  
Sungho Won ◽  
Robert C. Elston
Keyword(s):  
Case Control ◽  
Genotype Data ◽  
Power Comparison ◽  
Association Tests ◽  
Single Marker ◽  
Control Genotype

scholarly journals A Powerful Two-Stage Association Test Using Case-Control and Case-Parents Genotype Data

2009 ◽  
Vol 68 (4) ◽  
pp. 278-287
Author(s):  
K.F. Cheng ◽  
W.J. Lin ◽  
J.H. Chen ◽  
J.T. Horng
Keyword(s):  
Case Control ◽  
Association Test ◽  
Genotype Data ◽  
Two Stage

scholarly journals Genetic association tests: a method for the joint analysis of family and case-control data

2009 ◽  
Vol 4 (1) ◽  
pp. 2 ◽  
Author(s):  
Courtney Gray-McGuire ◽  
Murielle Bochud ◽  
Robert Goodloe ◽  
Robert C Elston
Keyword(s):  
Genetic Association ◽  
Case Control ◽  
Joint Analysis ◽  
Control Data ◽  
Association Tests ◽  
Genetic Association Tests

Combining Association Tests across Multiple Genetic Markers in Case-Control Studies

2008 ◽  
Vol 65 (3) ◽  
pp. 166-174 ◽  
Author(s):  
Huanyu Zhou ◽  
Lee-Jen Wei ◽  
Xiping Xu ◽  
Xin Xu
Keyword(s):  
Genetic Markers ◽  
Case Control ◽  
Case Control Studies ◽  
Association Tests

scholarly journals The Mega2R package: R tools for accessing and processing genetic data in common formats

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 1352 ◽  
Author(s):  
Robert V. Baron ◽  
Justin R. Stickel ◽  
Daniel E. Weeks
Keyword(s):  
Association Analysis ◽  
Genetic Data ◽  
R Package ◽  
Data Representation ◽  
Family Data ◽  
Genotype Data ◽  
Association Tests ◽  
Link Type ◽  
Data Formats ◽  
Linkage And Association Analysis

The standalone C++ Mega2 program has been facilitating data-reformatting for linkage and association analysis programs since 2000. Support for more analysis programs has been added over time. Currently, Mega2 converts data from several different genetic data formats (including PLINK, VCF, BCF, and IMPUTE2) into the specific data requirements for over 40 commonly-used linkage and association analysis programs (including Mendel, Merlin, Morgan, SHAPEIT, ROADTRIPS, MaCH/minimac3). Recently, Mega2 has been enhanced to use a SQLite database as an intermediate data representation. Additionally, Mega2 now stores bialleleic genotype data in a highly compressed form, like that of the GenABEL R package and the PLINK binary format. Our new Mega2R package now makes it easy to load Mega2 SQLite databases directly into R as data frames. In addition, Mega2R is memory efficient, keeping its genotype data in a compressed format, portions of which are only expanded when needed. Mega2R has functions that ease the process of applying gene-based tests by looping over genes, efficiently pulling out genotypes for variants within the desired boundaries. We have also created several more functions that illustrate how to use the data frames: these permit one to run the pedgene package to carry out gene-based association tests on family data, to run the SKAT package to carry out gene-based association tests, to output the Mega2R data as a VCF file and related files (for phenotype and family data), and to convert the data frames into GenABEL format. The Mega2R package enhances GenABEL since it supports additional input data formats (such as PLINK, VCF, and IMPUTE2) not currently supported by GenABEL. The Mega2 program and the Mega2R R package are both open source and are freely available, along with extensive documentation, from https://watson.hgen.pitt.edu/register for Mega2 and https://CRAN.R-project.org/package=Mega2R for Mega2R.

scholarly journals A Metagenome-Wide Association Study of Gut Microbiome in Patients With Multiple Sclerosis Revealed Novel Disease Pathology

2020 ◽  
Vol 10 ◽  
Author(s):  
Toshihiro Kishikawa ◽  
Kotaro Ogawa ◽  
Daisuke Motooka ◽  
Akiko Hosokawa ◽  
Makoto Kinoshita ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Association Study ◽  
Pathway Analysis ◽  
Gut Microbiome ◽  
Genome Wide Association Study ◽  
Case Control ◽  
Shotgun Sequencing ◽  
Host Genome ◽  
Association Tests ◽  
Significant Enrichment

While microbiome plays key roles in the etiology of multiple sclerosis (MS), its mechanism remains elusive. Here, we conducted a comprehensive metagenome-wide association study (MWAS) of the relapsing-remitting MS gut microbiome (ncase = 26, ncontrol = 77) in the Japanese population, by using whole-genome shotgun sequencing. Our MWAS consisted of three major bioinformatic analytic pipelines (phylogenetic analysis, functional gene analysis, and pathway analysis). Phylogenetic case-control association tests showed discrepancies of eight clades, most of which were related to the immune system (false discovery rate [FDR] < 0.10; e.g., Erysipelatoclostridium_sp. and Gemella morbillorum). Gene association tests found an increased abundance of one putative dehydrogenase gene (Clo1100_2356) and one ABC transporter related gene (Mahau_1952) in the MS metagenome compared with controls (FDR < 0.1). Molecular pathway analysis of the microbiome gene case-control comparisons identified enrichment of multiple Gene Ontology terms, with the most significant enrichment on cell outer membrane (P = 1.5 × 10−7). Interaction between the metagenome and host genome was identified by comparing biological pathway enrichment between the MS MWAS and the MS genome-wide association study (GWAS) results (i.e., MWAS-GWAS interaction). No apparent discrepancies in alpha or beta diversities of metagenome were found between MS cases and controls. Our shotgun sequencing-based MWAS highlights novel characteristics of the MS gut microbiome and its interaction with host genome, which contributes to our understanding of the microbiome’s role in MS pathophysiology.

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