TY - JOUR
T1 - SNeP: A tool to estimate trends in recent effective population size trajectories using genome-wide SNP data
AU - Barbato, Mario
AU - Orozco-Terwengel, Pablo
AU - Tapio, Miika
AU - Bruford, Michael W.
PY - 2015
Y1 - 2015
N2 - Effective population size (Ne) is a key population genetic parameter that describes the amount of genetic drift in a population. Estimating Ne has been subject to much research over the last 80 years. Methods to estimate Ne from linkage disequilibrium (LD) were developed ~40 years ago but depend on the availability of large amounts of genetic marker data that only the most recent advances in DNA technology have made available. Here we introduce SNeP, a multithreaded tool to perform the estimate of Ne using LD using the standard PLINK input file format (.ped and.map files) or by using LD values calculated using other software. Through SNeP the user can apply several corrections to take account of sample size, mutation, phasing, and recombination rate. Each variable involved in the computation such as the binning parameters or the chromosomes to include in the analysis can be modified. When applied to published datasets, SNeP produced results closely comparable with those obtained in the original studies. The use of SNeP to estimate Ne trends can improve understanding of population demography in the recent past, provided a sufficient number of SNPs and their physical position in the genome are available. Binaries for the most common operating systems are available at https://sourceforge.net/projects/snepnetrends/.
AB - Effective population size (Ne) is a key population genetic parameter that describes the amount of genetic drift in a population. Estimating Ne has been subject to much research over the last 80 years. Methods to estimate Ne from linkage disequilibrium (LD) were developed ~40 years ago but depend on the availability of large amounts of genetic marker data that only the most recent advances in DNA technology have made available. Here we introduce SNeP, a multithreaded tool to perform the estimate of Ne using LD using the standard PLINK input file format (.ped and.map files) or by using LD values calculated using other software. Through SNeP the user can apply several corrections to take account of sample size, mutation, phasing, and recombination rate. Each variable involved in the computation such as the binning parameters or the chromosomes to include in the analysis can be modified. When applied to published datasets, SNeP produced results closely comparable with those obtained in the original studies. The use of SNeP to estimate Ne trends can improve understanding of population demography in the recent past, provided a sufficient number of SNPs and their physical position in the genome are available. Binaries for the most common operating systems are available at https://sourceforge.net/projects/snepnetrends/.
KW - Demography
KW - Effective population size
KW - Genetics
KW - Genetics (clinical)
KW - Large scale genotyping
KW - Linkage disequilibrium
KW - Molecular Medicine
KW - SNPChip
KW - Demography
KW - Effective population size
KW - Genetics
KW - Genetics (clinical)
KW - Large scale genotyping
KW - Linkage disequilibrium
KW - Molecular Medicine
KW - SNPChip
UR - http://hdl.handle.net/10807/127890
UR - http://journal.frontiersin.org/article/10.3389/fgene.2015.00109/full
U2 - 10.3389/fgene.2015.00109
DO - 10.3389/fgene.2015.00109
M3 - Article
SN - 1664-8021
VL - 6
SP - 1
EP - 6
JO - Frontiers in Genetics
JF - Frontiers in Genetics
ER -