Literature DB >> 33346083

mrMLM v4.0.2: An R Platform for Multi-locus Genome-wide Association Studies.

Ya-Wen Zhang1, Cox Lwaka Tamba2, Yang-Jun Wen3, Pei Li1, Wen-Long Ren4, Yuan-Li Ni3, Jun Gao5, Yuan-Ming Zhang6.   

Abstract

Previous studies have reported that some important loci are missed in single-locus genome-wide association studies (GWAS), especially because of the large phenotypic error in field experiments. To solve this issue, multi-locus GWAS methods have been recommended. However, only a few software packages for multi-locus GWAS are available. Therefore, we developed an R software named mrMLM v4.0.2. This software integrates mrMLM, FASTmrMLM, FASTmrEMMA, pLARmEB, pKWmEB, and ISIS EM-BLASSO methods developed by our lab. There are four components in mrMLM v4.0.2, including dataset input, parameter setting, software running, and result output. The fread function in data.table is used to quickly read datasets, especially big datasets, and the doParallel package is used to conduct parallel computation using multiple CPUs. In addition, the graphical user interface software mrMLM.GUI v4.0.2, built upon Shiny, is also available. To confirm the correctness of the aforementioned programs, all the methods in mrMLM v4.0.2 and three widely-used methods were used to analyze real and simulated datasets. The results confirm the superior performance of mrMLM v4.0.2 to other methods currently available. False positive rates are effectively controlled, albeit with a less stringent significance threshold. mrMLM v4.0.2 is publicly available at BioCode (https://bigd.big.ac.cn/biocode/tools/BT007077) or R (https://cran.r-project.org/web/packages/mrMLM.GUI/index.html) as an open-source software.
Copyright © 2020 Beijing Institute of Genomics, Chinese Academy of Sciences and Genetics Society of China. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Genome-wide association study; Linear mixed model; Multi-locus genetic model; R; mrMLM

Year:  2020        PMID: 33346083     DOI: 10.1016/j.gpb.2020.06.006

Source DB:  PubMed          Journal:  Genomics Proteomics Bioinformatics        ISSN: 1672-0229            Impact factor:   7.691


  21 in total

1.  A Practical Guide to Using Structural Variants for Genome-Wide Association Studies.

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2.  Identification of QTNs Associated With Flowering Time, Maturity, and Plant Height Traits in Linum usitatissimum L. Using Genome-Wide Association Study.

Authors:  Ankit Saroha; Deepa Pal; Sunil S Gomashe; Vikender Kaur; Shraddha Ujjainwal; S Rajkumar; J Aravind; J Radhamani; Rajesh Kumar; Dinesh Chand; Abhishek Sengupta; Dhammaprakash Pandhari Wankhede
Journal:  Front Genet       Date:  2022-06-14       Impact factor: 4.772

3.  Domestication and improvement genes reveal the differences of seed size- and oil-related traits in soybean domestication and improvement.

Authors:  Jian-Fang Zuo; Muhammad Ikram; Jin-Yang Liu; Chun-Yu Han; Yuan Niu; Jim M Dunwell; Yuan-Ming Zhang
Journal:  Comput Struct Biotechnol J       Date:  2022-06-13       Impact factor: 6.155

4.  Superior haplotypes towards development of low glycemic index rice with preferred grain and cooking quality.

Authors:  Ramchander Selvaraj; Arun Kumar Singh; Vikas Kumar Singh; Ragavendran Abbai; Sonali Vijay Habde; Uma Maheshwar Singh; Arvind Kumar
Journal:  Sci Rep       Date:  2021-05-12       Impact factor: 4.379

5.  Chromosome-level genome sequence assembly and genome-wide association study of Muscadinia rotundifolia reveal the genetics of 12 berry-related traits.

Authors:  Minkyu Park; Daniel Vera; Devaiah Kambrianda; Pranavkumar Gajjar; Lance Cadle-Davidson; Violeta Tsolova; Islam El-Sharkawy
Journal:  Hortic Res       Date:  2022-01-18       Impact factor: 6.793

6.  Multi-Locus Genome-Wide Association Studies Reveal Fruit Quality Hotspots in Peach Genome.

Authors:  Cassia da Silva Linge; Lichun Cai; Wanfang Fu; John Clark; Margaret Worthington; Zena Rawandoozi; David H Byrne; Ksenija Gasic
Journal:  Front Plant Sci       Date:  2021-02-25       Impact factor: 5.753

7.  Genome-Wide Association Study (GWAS) for Resistance to Sclerotinia sclerotiorum in Common Bean.

Authors:  Ana Campa; Carmen García-Fernández; Juan José Ferreira
Journal:  Genes (Basel)       Date:  2020-12-12       Impact factor: 4.096

8.  Genome-wide association studies for growth traits in broilers.

Authors:  Dachang Dou; Linyong Shen; Jiamei Zhou; Zhiping Cao; Peng Luan; Yumao Li; Fan Xiao; Huaishun Guo; Hui Li; Hui Zhang
Journal:  BMC Genom Data       Date:  2022-01-03

Review 9.  Suitability of GWAS as a Tool to Discover SNPs Associated with Tick Resistance in Cattle: A Review.

Authors:  Nelisiwe Mkize; Azwihangwisi Maiwashe; Kennedy Dzama; Bekezela Dube; Ntanganedzeni Mapholi
Journal:  Pathogens       Date:  2021-12-09

10.  Uncovering Novel Genomic Regions and Candidate Genes for Senescence-Related Traits by Genome-Wide Association Studies in Upland Cotton (Gossypium hirsutum L.).

Authors:  Qibao Liu; Libei Li; Zhen Feng; Shuxun Yu
Journal:  Front Plant Sci       Date:  2022-01-05       Impact factor: 5.753

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