SUMMARY: Distribution of fitness effects (DFE) of mutations can be inferred from site frequency spectrum (SFS) data. There is mounting interest to determine whether distinct genomic regions and/or species share a common DFE, or whether evidence exists for differences among them. polyDFEv2.0 fits multiple SFS datasets at once and provides likelihood ratio tests for DFE invariance across datasets. Simulations show that testing for DFE invariance across genomic regions within a species requires models accounting for distinct sources of heterogeneity (chance and genuine difference in DFE) underlying differences in SFS data in these regions. Not accounting for this will result in the spurious detection of DFE differences. AVAILABILITY AND IMPLEMENTATION: polyDFEv2.0 is implemented in C and is accompanied by a series of R functions that facilitate post-processing of the output. It is available as source code and compiled binaries under a GNU General Public License v3.0 from https://github.com/paula-tataru/polyDFE. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
SUMMARY: Distribution of fitness effects (DFE) of mutations can be inferred from site frequency spectrum (SFS) data. There is mounting interest to determine whether distinct genomic regions and/or species share a common DFE, or whether evidence exists for differences among them. polyDFEv2.0 fits multiple SFS datasets at once and provides likelihood ratio tests for DFE invariance across datasets. Simulations show that testing for DFE invariance across genomic regions within a species requires models accounting for distinct sources of heterogeneity (chance and genuine difference in DFE) underlying differences in SFS data in these regions. Not accounting for this will result in the spurious detection of DFE differences. AVAILABILITY AND IMPLEMENTATION: polyDFEv2.0 is implemented in C and is accompanied by a series of R functions that facilitate post-processing of the output. It is available as source code and compiled binaries under a GNU General Public License v3.0 from https://github.com/paula-tataru/polyDFE. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Authors: Parul Johri; Adam Eyre-Walker; Ryan N Gutenkunst; Kirk E Lohmueller; Jeffrey D Jensen Journal: Genome Biol Evol Date: 2022-07-02 Impact factor: 4.065
Authors: Robert Horvath; Emily B Josephs; Edouard Pesquet; John R Stinchcombe; Stephen I Wright; Douglas Scofield; Tanja Slotte Journal: Mol Biol Evol Date: 2021-12-09 Impact factor: 16.240
Authors: Xin Huang; Alyssa Lyn Fortier; Alec J Coffman; Travis J Struck; Megan N Irby; Jennifer E James; José E León-Burguete; Aaron P Ragsdale; Ryan N Gutenkunst Journal: Mol Biol Evol Date: 2021-09-27 Impact factor: 16.240