QTL.gCIMapping.GUI v2.0: An R software for detecting small-effect and linked QTLs for quantitative traits in bi-parental segregation populations
| Autor: | Jim M. Dunwell, Yuan-Ming Zhang, Ya-Wen Zhang, Yang-Jun Wen |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
lcsh:Biotechnology
Bayesian probability Small-effect QTL Biophysics Value (computer science) Quantitative trait locus computer.software_genre Biochemistry 03 medical and health sciences 0302 clinical medicine Software Structural Biology lcsh:TP248.13-248.65 Genetics 030304 developmental biology Mathematics 0303 health sciences business.industry Estimation theory Linked QTL Stepwise regression QTL.gCIMapping Computer Science Applications 030220 oncology & carcinogenesis Trait Doubled haploidy Data mining GCIM business QTL.gCIMapping.GUI computer Biotechnology Research Article |
| Zdroj: | Computational and Structural Biotechnology Journal Computational and Structural Biotechnology Journal, Vol 18, Iss, Pp 59-65 (2020) |
| ISSN: | 2001-0370 |
| Popis: | Highlights • Although QTL mapping methods are well established, it is difficult to detect small and linked QTLs. • An R software QTL.gCIMapping.GUI v2.0 has been developed to identify small and linked QTLs. • This software program can be used to identify all kinds of omics QTLs. The methodologies and software packages for mapping quantitative trait loci (QTLs) in bi-parental segregation populations are well established. However, it is still difficult to detect small-effect and linked QTLs. To address this issue, we proposed a genome-wide composite interval mapping (GCIM) in bi-parental segregation populations. To popularize this method, we developed an R package. This program with two versions (Graphical User Interface: QTL.gCIMapping.GUI v2.0 and code: QTL.gCIMapping v3.2) can be used to identify QTLs for quantitative traits in recombinant inbred lines, doubled haploid lines, backcross and F2 populations. To save running time, fread function was used to read the dataset, parallel operation was used in parameter estimation, and conditional probability calculation was implemented by C++. Once one input file with *.csv or *.txt formats is uploaded into the package, one or two output files and one figure can be obtained. The input file with the ICIM and win QTL cartographer formats is available as well. Real data analysis for 1000-grain weight in rice showed that the GCIM detects the maximum previously reported QTLs and genes, and has the minimum AIC value in the stepwise regression of all the identified QTLs for this trait; using stepwise regression and empirical Bayesian analyses, there are some false QTLs around the previously reported QTLs and genes from the CIM method. The above software packages on Windows, Mac and Linux can be downloaded from https://cran.r-project.org/web/packages/ or https://bigd.big.ac.cn/biocode/tools/7078/releases/27 in order to identify all kinds of omics QTLs. |
| Databáze: | OpenAIRE |
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