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67 results for “VCF file”
Genomic vcf file for D.melanogaster, Sussex LHM population
<p>Data, logs and code for genomic vcf genotypes file for the Morrow lab, D.melanogaster LHM sequencing and genotyping project.</p>
Simulated Ancient Genomic Kinship Dataset: VCF and BAM (1x) Files for Related (including inbred) Pairs
<p>Simulated Ancient Genomic Kinship Dataset: VCF and BAM (1x and 5x) Files for Related (including inbred) Pairs</p><p><strong>Description:</strong></p><p>This dataset comprises simulated pedigrees (VCF files containing 8,677,101 autosomal biallelic and 298,625 X chromosomal SNP positions) generated using Ped-sim (v1.3) and comprising pairs of diverse familial relationship types up to third-degree. The first-degree relationships are parent-offspring and siblings; the second-degree relationships are half-siblings, grandparent-grandchild, and avuncular pairs; and third-degree relationships are first cousins, great-grandparent-great-grandchild, and grand avuncular pairs. For each of these 8 relationship types, our dataset includes 48 pairs of individuals. It also contains unrelated pairs. Additionally, the dataset includes first- and second-degree relatives, with inbreeding (parent-offspring pairs where the parents of the offspring are the first cousins and grandparent-grandchild pairs where the grandchild is the offspring of first cousins). Our simulations encompass all combinations of kinship types regarding sex. The dataset was further enriched by simulating ancient DNA-like sequencing data (5x and 1x BAM files) of Ped-sim simulated individuals using the gargammel tool, employing procedures akin to standard paleogenomic sequencing libraries. Note that the BAM files contain only randomly chosen 200K autosomal SNP positions. Positions can be found in the "200K_positions" file. Details can be found in Aktürk, Mapelli and Güler et al. 2023.</p><p><strong>Data Sources and Generation:</strong></p><p>Founder genotypes for pedigree simulation were created from the Tuscany (TSI) population SNPs within the 1000 Genomes Dataset v3. Notably, the founder genotypes lack background relatedness or runs of homozygosity (ROH).</p><p><strong>Description of File Naming Conventions:</strong></p><p>The naming conventions of the BAM files in this dataset are designed to convey key information regarding the specifics of each file.</p><p><strong>cov1x or cov5x:</strong> This segment denotes the coverage level of the BAM files, indicating whether the sequencing coverage for the individuals in the files is 1x or 5x.</p><p><strong>run_*:</strong> Signifies the particular batch from which the pedigree and individuals are derived. This name segment also applies to VCF files.</p><p><strong>parent-offspring_* or similar identifiers:</strong> Reflects the origin of the individual from the corresponding VCF file. For instance, "parent-offspring_1" corresponds to the individuals present in the "run_*_parent-offspring_1.vcf" file.</p><p><strong>parent-offspring* or similar identifiers:</strong></p><p> Indicates the origin of the individual from the sets within the VCF files. For example, "parent-offspring1" signifies the first set of parent-offspring pedigrees within the VCF file. Note that parent-offspring, grandparent-grandchild, and great-grandparent-great-grandchild and the inbreeding VCFs contain only one set, so this identifier is always 1. This convention can be 1 or 2 for the rest of the pedigrees, as the VCF files contain two sets of related pairs.</p><p><strong>_g*-b*-: </strong>Provides information about the individual's generational level within the VCF. This follows the Ped-sim syntax. For example, for parent-offspring type, "_g1-b1-" indicates the first parent (generation 1) within a specific pedigree, and "_g1-b2-" indicates the second parent (generation 1) while "_g2-b1-" represents the offspring (generation 2).</p><p><strong>Example Naming Structure:</strong></p><p>For instance, the file "cov1x_run1_parent-offspring_1_parent-offspring1_g1-b1-i1.all.hs37d5.cons.90perc.trimBAM.bam" signifies a BAM file with 1x coverage, originating from "run1," containing individuals from the "run_*_parent-offspring_1.vcf" file (first set of parent-offspring pairs) where "_g1-b1-" designates the first parent in the first generation. The latter half of the name "hs37d5.cons.90perc.trimBAM.bam" is the same across all files. </p><p><strong>Note1:</strong> Segments such as <strong>parent-offspring*_g*-b*- </strong>can also be tracked in the naming of the genotype columns in the VCF.</p><p><strong>Note2: </strong>Sexual information within the VCF files is discernible from the genetic data present at X chromosome positions. Individuals carrying two genotypes on the X chromosome are female, while those with a single genotype are male.</p><p><strong>Note3: Some of the individuals from distinct pedigrees may</strong>,<strong> in fact</strong>,<strong> be related due to shared ancestry through common founders. To suit specific research objectives, researchers may need to identify and exclude such relatives if the full dataset is used for kinship estimation.</strong></p><p>For more details about the dataset's generation process, unique characteristics, or any specific inquiries, our team is available for further information. We welcome and encourage inquiries, aiming to provide comprehensive support and additional details that might aid researchers in utilizing this dataset effectively. Please don't hesitate to contact us for any specific information you may need.</p><p>This repository contains only VCFs and cov1x BAM and 200K_positions files. The rest of the files can be found at <strong>10.5281/zenodo.10079625 </strong>and<strong> 10.5281/zenodo.10079685.</strong></p><p> </p>
Identification of grapevine clones via high-throughput amplicon sequencing: a proof-of-concept study VCF files
<p>VCF files used and cited in the article: Identification of grapevine clones via high-throughput amplicon sequencing: a proof-of-concept study</p>
Dsuite - fast D-statistics and related admixture evidence from VCF files
<p>Patterson's D, also known as the ABBA-BABA statistic, and related statistics such as the f4-ratio, are commonly used to assess evidence of gene flow between populations or closely related species. Currently available implementations often require custom file formats, implement only small subsets of the available statistics, and are impractical to evaluate all gene flow hypotheses across datasets with many populations or species due to computational inefficiencies. Here we present a new software package Dsuite, an efficient implementation allowing genome scale calculations of the D and f4-ratio statistics across all combinations of tens or hundreds of populations or species directly from a variant call format (VCF) file. Our program also implements statistics suited for application to genomic windows, providing evidence of whether introgression is confined to specific loci and it can also aid in interpretation of a system of f4-ratio results with the use of the 'f-branch' method. Dsuite is available at https://github.com/millanek/Dsuite, is straightforward to use, substantially more computationally efficient than comparable programs, and provides a convenient suite of tools and statistics, including some not previously available in any software package. Thus, Dsuite facilitates the assessment of evidence for gene flow, especially across larger genomic datasets.</p>
VCF file of Variants in a wide onion cross segregating for bolting
<p>VCF (variant call format) file of variants from bulked segregant RNA PoolSeq (BSR-seq) of F2 progeny pools of a wide onion cross segregating for bolting (precocious flowering). The reference assembly is GBGJ00000000.1 http://www.ncbi.nlm.nih.gov/nuccore/656904698</p> <p>The pools were taken from materials sampled for validation of the <em>AcBlt1</em> locus as described in http://www.ncbi.nlm.nih.gov/pubmed/24247236</p> <p>Pools were from bolting or non-bolting plants homozygous at the most closely linked marker to <em>AcBlt1 </em>either for the bolt-associated genotype (AA) or the non-bolt genotype (BB). </p>
VCF, pileup, and other files for Betula analyses using ebg & GATK
<p>These are the VCF, pileup, and input files files produced by the Genome Analysis ToolKit, SAMtools, and our own scripts, respectively, used for comparing the genotypes estimated by the GATK UnifiedGenotyper and the new model for allopolyploids that we introduced in our paper. Additional processing of the files was conducting using Python and R for filtering and extracting error values and read counts (scripts available on GitHub: https://github.com/pblischak/polyploid-genotyping).</p> <p><strong>Main files:</strong></p> <ul> <li>pendula-ug-filtered30.vcf: VCF file from GATK with all called variants for <em>Betula</em> <em>pendula</em> (diploid).</li> <li>filtered30-pendula.pileup: SAMtools pileup file for variant sites identified by GATK in <em>B</em>. <em>pendula</em>.</li> <li>pubescens-ug-filtered30.vcf: VCF file from GATK with all called variants for <em>Betula</em> <em>pubescens</em> (allotetraploid).</li> <li>filtered30-pubescens.pileup: SAMtools pileup file for variant sites identified by GATK in <em>B</em>. <em>pubescens</em>.</li> </ul> <p><strong>Processed files:</strong></p> <ul> <li>filtered30-variants.txt: tab delimited file of shared variants between B. pendula and B. pubescens.</li> <li>filtered30-vcf1.vcf: VCF file for B. pendula with variants extracted from filtered30-variants.txt.</li> <li>filtered30-vcf2.vcf: VCF file for B. pubescens with variants extracted from filtered30-variants.txt.</li> </ul> <p><strong>Input files</strong>:</p> <ul> <li>filtered30-pubescens-tot.txt, filtered30-pubescents-alt.txt, filtered30-pubescens-err.txt: input files for running the alloSNP model in ebg.</li> <li>filtered30-pubescens-alloSNP-freqs2.txt, filtered30-pubescens-alloSNP-g1.txt, filtered30-pubescens-alloSNP-g2.txt: output files from the alloSNP model.</li> <li>filtered30-pendula-tot.txt, filtered30-pendula-alt.txt, filtered30-pendula-err.txt: input files for running the hwe model in ebg.</li> <li>filtered30-pendula-hwe-freqs.txt, filtered30-pendula-hwe-genos.txt: output files from the hwe model. The allele frequency estimates here were also used as the reference panel for the alloSNP model.</li> </ul>
VCF files of common grassland plants from wild collected seeds of 19 common European grassland species with up to 4 consecutive generations grown in monoculture for seed production for restoration
<p>A growing number of restoration projects require large amounts of seeds. As harvesting natural populations cannot cover the demand, wild plants are often propagated in large-scale monocultures. There are concerns that this cultivation process may cause genetic drift and unintended selection, which would alter the genetic properties of the cultivated populations and reduce their genetic diversity. Such changes could reduce the pre-existing adaptation of restored populations, and limit their adaptability to environmental change.</p> <p>We used single nucleotide polymorphism (SNP) markers and a pool-sequencing approach to test for genetic differentiation and changes in gene diversity during cultivation in 19 wild grassland species, comparing the source populations and up to four consecutive cultivation generations. We then linked the magnitudes of genetic changes to the species' breeding systems and seed dormancy, to understand the roles of these traits in genetic change.</p> <p>The propagation changed the genetic composition of the cultivated generations only moderately. The genetic differentiation we observed as a consequence of cultivation was much lower than the natural genetic differentiation between different source regions. The propagated generations harbored even higher gene diversity than wild-collected seeds. Genetic change was stronger in self-compatible than in self-incompatible species, probably as a result of increased outcrossing in the monocultures.</p> <p><em>Synthesis and applications</em>: Our study indicates that large-scale seed production maintains the genetic integrity of natural populations. Increased genetic diversity may be indicative of increased adaptive potential of propagated seeds, which would make them especially suitable for ecological restoration. Yet, it remains to be tested whether these patterns observed on the level of molecular markers will be mirrored also in plant phenotypes. Further, we used seeds produced in Germany and Austria, where the seed production is regulated and certified. Whether other seed production systems perform equally well remains to be tested.</p>
Development of a high-density 665 K SNP array for rainbow trout genome-wide genotyping. Supplemental VCF file
<p>Single nucleotide polymorphism (SNP) arrays, also named « SNP chips », enable very large numbers of individuals to be genotyped at a targeted set of thousands of genome-wide identified markers. We used preexisting variant datasets from USDA, a French commercial line and 30X-coverage whole genome sequencing of INRAE isogenic lines to develop an Affymetrix 665 K SNP array (HD chip) for rainbow trout. In total, we identified 32,372,492 SNPs that were polymorphic in the USDA or INRAE databases. A subset of identified SNPs were selected for inclusion on the chip, prioritizing SNPs whose flanking sequence uniquely aligned to the Swanson reference genome, with homogenous repartition over the genome and the highest Minimum Allele Frequency in both USDA and French databases. Of the 664,531 SNPs which passed the Affymetrix quality filters and were manufactured on the HD chip, 65.3% and 60.9% passed filtering metrics and were polymorphic in two other distinct French commercial populations in which, respectively, 288 and 175 sampled fish were genotyped. Only 576,118 SNPs mapped uniquely on both Swanson and Arlee reference genomes, and 12,071 SNPs did not map at all on the Arlee reference genome. Among those 576,118 SNPs, 38,948 SNPs were kept from the commercially available medium-density 57K SNP chip. We demonstrate the utility of the HD chip by describing the high rates of linkage disequilibrium at 2 kb to 10 kb in the rainbow trout genome in comparison to the linkage disequilibrium observed at 50 kb to 100 kb which are usual distances between markers of the medium-density chip.</p> <p> </p> <p>File submitted correspond to the supplementary data 1 of the publication (under submission) : INRAE_USDA_MAF1.vcf.gz</p>
VCF File containing genotype calls for 136 Populus alba x Populus tremula hybrids obtained through both RAD-seq and GBS
<p>VCF file used to compare genotype calls obtained through RAD-seq and GBS for 126 common garden seedlings of Populus tremula and Populus alba hybrids. See Bresadola et al. (2019) for more details.</p>
somalier files for thousand genomes high-coverage VCF for 2504 samples
<p>somalier files extracted from the thousand genomes VCF to be used for ancestry prediction with somalier.</p>
VCF file from: Signatures of local adaptation to current and future climate in phenology-related genes in natural populations of Quercus robur
<p>Qrob_seqcap_87_18799.vcf - containing 18,799 single nucleotide variants (SNPs) in phenology-related genes in 87 individuals of Quercus robur from 6 populations, described in Meger et al.</p> <p> </p>
VCF files of ddRAD seq data of Bermuda petrel population
<p>Two VCF files resulted from two different filtering and analyses of ddRAD sequencing data of the endangered Bermuda petrel. The one_snp VCF contains only one snp per RAD locus, while the all_snps contained all SNPs in a RAD locus.</p>
VCF files of common grassland plants from wild collected seeds of 19 common European grassland species with up to 4 consecutive generations grown in monoculture for seed production for restoration
Open the record for dataset details and reuse information.
Dsuite - fast D-statistics and related admixture evidence from VCF files
Open the record for dataset details and reuse information.
Staphylococcus aureus VCF files: Risk Factors for Recurrent Staphylococcus aureus Bacteremia
<p>Background: To understand the clinical, bacterial, and host characteristics associated with recurrent Staphylococcus aureus bacteremia (R-SAB), patients with R-SAB were compared to contemporaneous patients with a single episode of SAB (S-SAB).<br> Methods: All SAB isolates underwent spa genotyping. All isolates from R-SAB patients underwent Pulsed-Field Gel Electrophoresis (PFGE). PFGE-indistinguishable pairs from 40 patients underwent whole genome sequencing (WGS). Acute phase plasma from R-SAB and S-SAB patients was matched 1:1 for age, race, gender, and bacterial genotype and underwent cytokine quantification using 25-analyte multiplex bead array. Results: R-SAB occurred in 69 (9.1%) of the 756 study patients. Of the 69 patients, 30 experienced relapse (43.5%) and 39 reinfection (56.5%). Age, race, hemodialysis dependence, presence of foreign body, MRSA, and persistent bacteremia were individually associated with likelihood of recurrence. Multivariate risk modeling revealed that African American (AA) hemodialysis patients were nearly two times more likely (OR = 9.652 [5.402 – 17.418]) than White hemodialysis patients (OR = 4.53 [1.696 – 10.879]) to experience R-SAB. WGS confirmed PFGE interpretations in all cases. Median RANTES levels in acute phase plasma from the initial episode of SAB were higher in R-SAB than in matched S-SAB controls ( P = 0.0053, False Discovery Rate < 0.10). <br> Conclusion: This study identified several risk factors for R-SAB. The largest risk for R-SAB is among AA hemodialysis patients. Higher RANTES levels in R-SAB compared to<br> matched controls warrants further study.</p>
Adaptation by copy number variation increases insecticide resistance in the fall armyworm (vcf files)
<p>Here, I deposite vcf files used for a paper, entitled 'Adaptation by copy number variation increases insecticide resistance in the fall armyworm'.</p> <p>genotype.vcf and SNP.filtered.vcf.gz have the information of CNVs and SNPs, respectively. </p>
VCF file for a population of Drosophila melanogaster
<p>This file is the set of single nucleotide polymorphisms and insertion/deletions in a population of Drosophila melanoagaster. The zipped file is in a simple text file. This VCF file is part of the following larger body of work: <strong>Patterns of genetic regulation of expression variation in a natural population of Drosophila melanogaster provide evidence for buffering and GRN robustness</strong></p>
QTL script and VCF files - GENETIC ARCHITECTURE OF FLOWERING-TIME VARIATION IN BRACHYPODIUM DISTACHYON
<p>Supplemental data for the article:</p> <p>GENETIC ARCHITECTURE OF FLOWERING-TIME VARIATION IN BRACHYPODIUM DISTACHYON (Woods et al., 2016).</p> <p>Supplemental data includes:</p> <ul> <li> <p>A folder named “Data”, which contains:</p> <ol> <li> <p><strong>Raw genotypic data</strong>. Data showing the parental genotype in a RIL population (F7; Bd21 X Bd1-1)</p> </li> <li> <p><strong>Raw phenotypic data</strong>. Flowering time (leaves and days to flowering) of the RIL population in different growth environments.</p> </li> <li> <p><strong>The genetic map </strong>(see material and methods section of Woods et al., 2016 for additional information).</p> </li> <li> <p><strong>Gene positions.</strong> A file containing the position of annotated genes on the Brachypodium distachyon genome V2.1. Data from Phytozome (https://phytozome.jgi.doe.gov/pz/portal.html).</p> </li> </ol> </li> <li> <p>The<strong> R script</strong> used for the QTL analysis (Final_script.R).</p> </li> <li> <p><strong>VCF files of the loci of interest</strong>. A folder called “VCF” includes the VCF files of the genes presented in Fig. 6 (VRN1, PHYC, VRN2, and FD). </p> </li> </ul> <p> </p>
VCF files and regression analyses for: Assessing fine-scale pondscape connectivity with amphibian eyes: an integrative approach using genomic and capture-mark-recapture data
<p><span>In the face of habitat loss, preserving functional connectivity is essential to maintain genetic diversity and the demographic dynamics required for the viability of biotic communities. This requires knowledge of the dispersal behavior of target species, which can be modeled as kernels, or probability density functions of dispersal distances at increasing geographic distances. We present an integrative approach to investigate the relationships between genetic connectivity and demographic parameters in organisms with low vagility focusing on five syntopic pond-breeding amphibians. We genotyped 1,056 individuals of two anuran and three urodele species (1,732–3,913 SNPs per species) from populations located in a landscape comprising 64 ponds to characterize fine-scale genetic structure in a comparative framework and combined this genetic data with information obtained in a previous two-year capture-mark-recapture (CMR) study. Specifically, we contrasted graphs reconstructed from genomic data with connectivity graphs based on dispersal kernels and demographic information obtained from CMR data from previous studies and assessed the effects of population size, population density, geographical distances, inverse movement probabilities and the presence of habitat patches potentially functioning as stepping stones on genetic differentiation. Our results suggest a significant influence of local population sizes on patterns of genetic connectivity at small spatial scales. In addition, m</span><span>ovement records and cluster-derived kernels provide robust inferences on most likely dispersal paths that are consistent with </span><span>genomic inferences on genetic connectivity. The integration of genetic and CMR data holds great potential for understanding genetic connectivity at spatial scales relevant to individual organisms, with applications for the implementation of management actions at the landscape level. </span></p>
Mergus octosetaceus ddRAD data (vcf file)
<p>This VCF file contains SNPs derived from 46 individuals of the <i>Mergus octosetaceus </i>species. The data was obtained using the Double digest restriction-site associated sequencing (ddRAD-seq) methodology and processed through the Stacks <i>de novo</i> pipeline.</p>
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