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14 results for “Plink”
Drosophila simulans LD results from PLINK for Chromosome X
<p><strong>Abstract</strong>: Heritable phenotypic variation in natural populations exceeds the levels predicted under mutation-selection balance where purifying selection removes variation. Balancing selection, inefficient or weak selection, polygenic adaptation, and non-equilibrium populations are all possible explanations for excess variation. Yet, available genomic data indicate an abundance of directional selection. One potential explanation is that fleeting directional selection drives beneficial mutations to high frequency in rapid waves resulting in many intermediate frequency haplotypes. This hypothesis is supported by the genomic data from a panel of 170 D. simulans genotypes established from a single stable population which show evidence for an abundance of incomplete soft sweeps. Demography, admixture, and balancing selection cannot entirely explain the patterns in these data, while transient selective sweeps can account for all the patterns of variation observed in this population. One interpretation is that constant environmental shifts rapidly change the optimal phenotype within Drosophila populations, leaving a signature of adaptive responses.</p> <p><strong>Material type</strong>: Text files of pairwise linkage disequilibrium (LD) calculations from Plink (v). </p> <p><strong>Larger Body of Work</strong>: Pervasive incomplete selective sweeps in D. simulans account for excess variation.</p> <p><strong>Related publications and dataset</strong>s: Drosophila simulans VCF, LD results from chromosomes 2L, 2R, 3R, 3L, and 4.</p>
Drosophila simulans LD results from PLINK for Chromosome 3R
<p><strong>Abstract</strong>: Heritable phenotypic variation in natural populations exceeds the levels predicted under mutation-selection balance where purifying selection removes variation. Balancing selection, inefficient or weak selection, polygenic adaptation, and non-equilibrium populations are all possible explanations for excess variation. Yet, available genomic data indicate an abundance of directional selection. One potential explanation is that fleeting directional selection drives beneficial mutations to high frequency in rapid waves resulting in many intermediate frequency haplotypes. This hypothesis is supported by the genomic data from a panel of 170 D. simulans genotypes established from a single stable population which show evidence for an abundance of incomplete soft sweeps. Demography, admixture, and balancing selection cannot entirely explain the patterns in these data, while transient selective sweeps can account for all the patterns of variation observed in this population. One interpretation is that constant environmental shifts rapidly change the optimal phenotype within Drosophila populations, leaving a signature of adaptive responses.</p> <p><strong>Material type</strong>: Text files of pairwise linkage disequilibrium (LD) calculations from Plink (v). </p> <p><strong>Larger Body of Work</strong>: Pervasive incomplete selective sweeps in D. simulans account for excess variation.</p> <p><strong>Related publications and datasets</strong>: Drosophila simulans VCF, LD results from chromosomes 2L, 2R, 3L, 4, and X.</p>
Drosophila simulans LD results from PLINK for Chromosome 4
<p><strong>Abstract</strong>: Heritable phenotypic variation in natural populations exceeds the levels predicted under mutation-selection balance where purifying selection removes variation. Balancing selection, inefficient or weak selection, polygenic adaptation, and non-equilibrium populations are all possible explanations for excess variation. Yet, available genomic data indicate an abundance of directional selection. One potential explanation is that fleeting directional selection drives beneficial mutations to high frequency in rapid waves resulting in many intermediate frequency haplotypes. This hypothesis is supported by the genomic data from a panel of 170 D. simulans genotypes established from a single stable population which show evidence for an abundance of incomplete soft sweeps. Demography, admixture, and balancing selection cannot entirely explain the patterns in these data, while transient selective sweeps can account for all the patterns of variation observed in this population. One interpretation is that constant environmental shifts rapidly change the optimal phenotype within Drosophila populations, leaving a signature of adaptive responses.</p> <p><strong>Material type</strong>: Text files of pairwise linkage disequilibrium (LD) calculations from Plink (v). </p> <p><strong>Larger Body of Wor</strong>k: Pervasive incomplete selective sweeps in D. simulans account for excess variation.</p> <p><strong>Related publications and datasets</strong>: Drosophila simulans VCF, LD results from chromosomes 2L, 2R, 3R, 3L, and X.</p>
Drosophila simulans LD results from PLINK for Chromosome 2R
<p><strong>Abstract</strong>: Heritable phenotypic variation in natural populations exceeds the levels predicted under mutation-selection balance where purifying selection removes variation. Balancing selection, inefficient or weak selection, polygenic adaptation, and non-equilibrium populations are all possible explanations for excess variation. Yet, available genomic data indicate an abundance of directional selection. One potential explanation is that fleeting directional selection drives beneficial mutations to high frequency in rapid waves resulting in many intermediate frequency haplotypes. This hypothesis is supported by the genomic data from a panel of 170 D. simulans genotypes established from a single stable population which show evidence for an abundance of incomplete soft sweeps. Demography, admixture, and balancing selection cannot entirely explain the patterns in these data, while transient selective sweeps can account for all the patterns of variation observed in this population. One interpretation is that constant environmental shifts rapidly change the optimal phenotype within Drosophila populations, leaving a signature of adaptive responses.</p> <p><strong>Material type</strong>: Text files of pairwise linkage disequilibrium (LD) calculations from Plink (v). </p> <p><strong>Larger Body of Wor</strong>k: Pervasive incomplete selective sweeps in D. simulans account for excess variation.</p> <p><strong>Related publications and datasets</strong>: Drosophila simulans VCF, LD results from chromosomes 2L, 3L, 3R, 4, and X.</p>
Drosophila simulans LD results from PLINK for Chromosome 3L
<p><strong>Abstract</strong>: Heritable phenotypic variation in natural populations exceeds the levels predicted under mutation-selection balance where purifying selection removes variation. Balancing selection, inefficient or weak selection, polygenic adaptation, and non-equilibrium populations are all possible explanations for excess variation. Yet, available genomic data indicate an abundance of directional selection. One potential explanation is that fleeting directional selection drives beneficial mutations to high frequency in rapid waves resulting in many intermediate frequency haplotypes. This hypothesis is supported by the genomic data from a panel of 170 D. simulans genotypes established from a single stable population which show evidence for an abundance of incomplete soft sweeps. Demography, admixture, and balancing selection cannot entirely explain the patterns in these data, while transient selective sweeps can account for all the patterns of variation observed in this population. One interpretation is that constant environmental shifts rapidly change the optimal phenotype within Drosophila populations, leaving a signature of adaptive responses.</p> <p><strong>Material type</strong>: Text files of pairwise linkage disequilibrium (LD) calculations from Plink (v). </p> <p><strong>Larger Body of Work</strong>: Pervasive incomplete selective sweeps in D. simulans account for excess variation.</p> <p><strong>Related publications and datasets</strong>: Drosophila simulans VCF, LD results from chromosomes 2L, 2R, 3R, 4, and X</p>
Drosophila simulans LD results from PLINK for Chromosome 2L
<p><strong>Abstract</strong>: Heritable phenotypic variation in natural populations exceeds the levels predicted under mutation-selection balance where purifying selection removes variation. Balancing selection, inefficient or weak selection, polygenic adaptation, and non-equilibrium populations are all possible explanations for excess variation. Yet, available genomic data indicate an abundance of directional selection. One potential explanation is that fleeting directional selection drives beneficial mutations to high frequency in rapid waves resulting in many intermediate frequency haplotypes. This hypothesis is supported by the genomic data from a panel of 170 D. simulans genotypes established from a single stable population which show evidence for an abundance of incomplete soft sweeps. Demography, admixture, and balancing selection cannot entirely explain the patterns in these data, while transient selective sweeps can account for all the patterns of variation observed in this population. One interpretation is that constant environmental shifts rapidly change the optimal phenotype within Drosophila populations, leaving a signature of adaptive responses.</p> <p><strong>Material type</strong>: Text files of pairwise linkage disequilibrium (LD) calculations from Plink (v). </p> <p><strong>Larger Body of Work</strong>: Pervasive incomplete selective sweeps in D. simulans account for excess variation.</p> <p><strong>Related publications and datasets</strong>: Drosophila simulans VCF, LD results from chromosomes 2R, 3L, 3R, 4, and X.</p>
Effect of variable thresholds on calculating linkage disequilibrium and population structure, using Plink 1.9
<p>The figure presented here shows how the number of LD-independent SNPs and the apparent population structure can change drastically, depending on what input thresholds are used for the calculations. The population sample consists of 220 fruit-fly (Drosophila melanogaster). Most of the population structure plots indicate four subpopulations, which on further investigation using Fst indicate that this is caused by defined trans-centromeric regions, without evidence for genotyping error, and probably reflective of historic admixture. In the plots of population structure, the number in each box indicates the number of independent SNPs which were used in the IBD calculatations. Points are coloured by order in which each fly was sequenced, and some error is noticable for the beige points in the top-right plots.</p> <p>The Plink program provides a useful method for selecting single-nucleotide polymorphisms (SNPs) which are independent of linkage disequilibrium (LD), and also of visualising the genetic relatedness between individuals in a population sample, using identity-by-descent analysis (IBD). The selection of LD-independent SNPs requires three user-specfied paramaters, alongside the genotype data: i. Window-size, in kilobases (Kb) within which all pairwise comparisons between SNPs will be made, ii. Step-size, in number of SNPs, iii. r2 threshold between any two SNPs, below which they are considered to be independent (fixed here at 0.5).</p>
correctKin PLINK data sets
<p>The PLINK data set of archaic mediveal family and the public 1KG individuals used in our manuscript: An optimized method to infer relatedness up to the 4th degree from low coverage ancient human genomes (BMC Genome Biology).</p> <p>The public sample IDs are equivalent with the 1KG phase III IDs. For archaic data: FTH (Father - tooth sample - high coverage); FPM (father - pars petrosa - medium coverage); FPL (father - parse petrosa - low coverage); CPH (Son - pars petrosa - high coverage); FPL (Son - pars petrosa - low coverage).</p> <p> </p>
.bed / .bim / .fam files, for 1kg, converted from the raw data on the PLINK website
<div> <div># Download the hg38 genome reference files from the PLINK website</div> <div>RUN wget -L https://www.dropbox.com/s/j72j6uciq5zuzii/all_hg38.pgen.zst</div> <div>RUN wget -L https://www.dropbox.com/scl/fi/fn0bcm5oseyuawxfvkcpb/all_hg38_rs.pvar.zst?rlkey=przncwb78rhz4g4ukovocdxaz -O all_hg38.pvar.zst</div> <div>RUN wget -L https://www.dropbox.com/scl/fi/u5udzzaibgyvxzfnjcvjc/hg38_corrected.psam?rlkey=oecjnk4vmbhc8b1p202l0ih4x -O all_hg38.psam</div> <br> <div># Download the hg38 related samples file from the PLINK website</div> <div>RUN wget -L https://www.dropbox.com/s/4zhmxpk5oclfplp/deg2_hg38.king.cutoff.out.id</div> <br> <div># Decompress the genome reference files</div> <div>RUN /plink-ng-master/2.0/bin/plink2 --zst-decompress all_hg38.pgen.zst all_hg38.pgen</div> <div>RUN rm all_hg38.pgen.zst</div> <br> <div>RUN /plink-ng-master/2.0/bin/plink2 --pfile all_hg38 vzs --allow-extra-chr --chr 1-22 --max-alleles 2 --remove deg2_hg38.king.cutoff.out.id --memory 6000 --make-bed --out 1kg_hg38</div> <br> <div># Replace rsIDs with chr:pos:ref:alt</div> <div>RUN awk 'BEGIN{OFS="\t"} {print $1,$1":"$4":"$6":"$5,$4,$6,$5}' 1kg_hg38.bim > 1kg_hg38_clean.bim</div> <div>RUN mv 1kg_hg38_clean.bim 1kg_hg38.bim</div> <div> </div> <div># Apply PLINK filtering (mAF > 0.1%, HWE p-value <1e-12, keep SNPs only)</div> <div>/plink-ng-master/2.0/bin/plink2 --bfile 1kg_hg38 --maf 0.001 --hwe 1e-12 --snps-only --make-bed --out 1kg_hg38_filtered --memory 6000</div> <div> </div> <div># Compress output files</div> <div>gzip 1kg_hg38_filtered.* -v --force</div> <div> </div> </div>
PLINK association test statistics of UK Biobank blood traits
<p>PLINK association test statistics of UK Biobank blood traits generated for mvSuSiE fine-mapping analyses; see https://www.biorxiv.org/content/10.1101/2023.04.14.536893.</p>
PLINK breed data showing SLAMF1 is associated with canine atopic dermatitis
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Minimal dataset to run CAUSEWAY - 5 eQTLGen genes, PLINK european bfiles and 1 Depression MTAG sumstats
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Plink files from NYGC 1KG to be used for Cancer GWAS project QBIO475
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Dataset with SNP genotypes for local goat breeds of Mongolia (PLINK format)
<p>SNP genotyping was performed with Goat 50K BeadChip (Illumina Inc., USA) containing ~60 000 SNP. Quality control was performed by setting a cutoff of 0.5 for the GenCall and GenTrain scores. SNP dataset was filtered to remove poorly genotyped individuals, loci genotyped in <90% of individuals and rare alleles using PLINK 1.9 (Chang et al. 2015) with geno 0.1 --mind 0.1 --maf 0.05 plink parameters. To ensure that our analysis would not be affected by the presence of SNP in strong linkage disequilibrium we also filtered data with --indep-pairwaise 50 5 0.2 PLINK filter. </p>
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