Optional Step 0: | Step 1: read in vcf file as 'vcfR' object | Step 2: quality filtering | Note: | Step 3: set missing data per sample cutoff | Set arbitrary cutoff for missing data allowed per sample. | Step 4: set missing data per SNP cutoff | Set arbitrary cutoff for missing data allowed per SNP. | Step 5: quality unaware filters | Step 6: write out files for downstream analysis
Package: SNPfiltR 1.0.7
Devon DeRaad
SNPfiltR: Interactively Filter SNP Datasets
Is designed to interactively and reproducibly visualize and filter SNP (single-nucleotide polymorphism) datasets. This R-based implementation of SNP and genotype filters facilitates an interactive and iterative SNP filtering pipeline, which can be documented reproducibly via 'rmarkdown'. 'SNPfiltR' contains functions for visualizing various quality and missing data metrics for a SNP dataset, and then filtering the dataset based on user specified cutoffs. All functions take 'vcfR' objects as input, which can easily be generated by reading standard vcf (variant call format) files into R using the R package 'vcfR' authored by Knaus and Grünwald (2017) <doi:10.1111/1755-0998.12549>. Each 'SNPfiltR' function can return a newly filtered 'vcfR' object, which can then be written to a local directory in standard vcf format using the 'vcfR' package, for downstream population genetic and phylogenetic analyses.
Authors:
SNPfiltR_1.0.7.tar.gz
SNPfiltR_1.0.7.tar.gz(r-4.7-any)SNPfiltR_1.0.7.tar.gz(r-4.6-any)
SNPfiltR_1.0.7.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
SNPfiltR/json (API)
| # Install 'SNPfiltR' in R: |
| install.packages('SNPfiltR', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Datasets:
- popmap - Popmap for example scrub-jay vcfR file
- vcfR.example - Example scrub-jay vcfR file
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:93c0672fd3. Checks:4 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 150 | ||
| source / vignettes | OK | 224 | ||
| linux-release-x86_64 | OK | 198 | ||
| wasm-release | OK | 141 |
Exports:assess_missing_data_pcaassess_missing_data_tsnedistance_thinfilter_allele_balancefilter_biallelichard_filtermax_depthmin_macmissing_by_samplemissing_by_snp
Dependencies:ade4adegenetapebase64encbootbslibcachemcliclustercommonmarkcpp11digestdplyrfarverfastmapfontawesomefsgenericsggplot2ggridgesgluegridExtragtablehtmltoolshttpuvigraphisobandjquerylibjsonlitelabelinglaterlatticelifecyclemagrittrMASSMatrixmemoisememusemgcvmimenlmeotelpermutepillarpinfsc50pixmappkgconfigplyrpromisesR6rappdirsRColorBrewerRcppRcppArmadilloreshape2rlangRtsneS7sassscalessegmentedseqinrshinysourcetoolsspstringistringrtibbletidyselectutf8vcfRvctrsveganviridisLitewithrxtable
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Vizualise how missing data thresholds affect sample clustering | assess_missing_data_pca |
| Vizualise how missing data thresholds affect sample clustering | assess_missing_data_tsne |
| Filter a vcf file based on distance between SNPs on a given scaffold | distance_thin |
| Filter out heterozygous genotypes failing an allele balance check | filter_allele_balance |
| Remove SNPs with more than two alleles | filter_biallelic |
| Hard filter a vcf file by depth and genotype quality (gq) | hard_filter |
| Vizualise and filter based on mean depth across all called SNPs | max_depth |
| Vizualise, filter based on Minor Allele Count (MAC) | min_mac |
| Vizualise missing data per sample, remove samples above a missing data cutoff | missing_by_sample |
| Vizualise missing data per SNP, remove SNPs above a missing data cutoff | missing_by_snp |
| Popmap for example scrub-jay vcfR file | popmap |
| SNPfiltR: A package for interactively visualizing and filtering SNP datasets | SNPfiltR |
| Example scrub-jay vcfR file | vcfR.example |