{ "_id": "6a5c5f849baadeef8ab4f2cd", "Package": "mbQTL", "Type": "Package", "Title": "mbQTL: A package for SNP-Taxa mGWAS analysis", "Version": "1.13.0", "Authors@R": "c(person(given = \"Mercedeh\",\nfamily = \"Movassagh\",\nrole = c(\"aut\", \"cre\"),\nemail = \"mercedeh.movassagh@yale.edu\",\ncomment = c(ORCID = \"0000-0001-7690-0230\")),\nperson(\"Steven\",\"Schiff\", role=\"aut\"),\nperson(\"Joseph N\", \"Paulson\", role=\"aut\"))", "Description": "mbQTL is a statistical R package for simultaneous\n16srRNA,16srDNA (microbial) and variant, SNP, SNV (host)\nrelationship, correlation, regression studies. We apply linear,\nlogistic and correlation based statistics to identify the\nrelationships of taxa, genus, species and variant, SNP, SNV in\nthe infected host. We produce various statistical significance\nmeasures such as P values, FDR, BC and probability estimation\nto show significance of these relationships. Further we provide\nvarious visualization function for ease and clarification of\nthe results of these analysis. The package is compatible with\ndataframe, MRexperiment and text formats.", "License": "MIT + file LICENSE", "Encoding": "UTF-8", "DeploySubPath": "mbQTL", "biocViews": "SNP, Microbiome, WholeGenome, Metagenomics,\nStatisticalMethod, Regression", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.2.1", "VignetteBuilder": "knitr", "URL": "\"https://github.com/Mercedeh66/mbQTL\"", "BugReport": "\"https://github.com/Mercedeh66/mbQTL/issues\"", "Config/pak/sysreqs": "libicu-dev", "Repository": "https://bioc.r-universe.dev", "Date/Publication": "2026-04-28 12:59:44 UTC", "RemoteUrl": "https://github.com/bioc/mbQTL", "RemoteRef": "HEAD", "RemoteSha": "dcb1e5a97f5133367a04b7d44713b4492bd950a7", "NeedsCompilation": "no", "Packaged": { "Date": "2026-07-19 05:19:46 UTC", "User": "root" }, "Author": "Mercedeh Movassagh [aut, cre] (ORCID:\n),\nSteven Schiff [aut],\nJoseph N Paulson [aut]", "Maintainer": "Mercedeh Movassagh ", "_user": "bioc", "_type": "src", "_file": "mbQTL_1.13.0.tar.gz", 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"Sample_2100" ], "rows": 2, "table": true, "tojson": true }, { "name": "metagenomeSeqObj", "title": "'mbQTL' \"metagenomeSeqObj\" \"MetagenomSeqObj\" is an 'MRexperiment' object format of the \"microbeAbund\" file.", "object": "metagenomeSeqObj", "file": "metagenomeSeqObj.rda", "class": [ "MRexperiment" ], "fields": [], "table": false, "tojson": false }, { "name": "microbeAbund", "title": "'mbQTL' \"microbiomeAbund\" File", "object": "microbeAbund", "file": "microbeAbund.rda", "class": [ "data.frame" ], "fields": [ "Acidovorax", "Acinetobacter", "Actinomyces", "Aggregatibacter", "Brevundimonas", "Corynebacterium", "Diaphorobacter", "Halomonas", "Hymenobacter", "Lactobacillus", "Leuconostoc", "Massilia", "Micromonospora", "Mycobacterium", "Porphyromonas", "Propionibacterium", "Pseudomonas", "Serinicoccus", "Staphylococcus", "Streptococcus", "Tepidimonas", "Veillonella", "Aerococcus", "Agrobacterium", "Alicyclobacillus", "Bacillus", "Buchnera", "Cloacibacterium", "Cytophagales", "Enhydrobacter", "Erwinia", "Haemophilus", "Hydrogenophaga", "Lactococcus", "Luteimonas", "Micrococcus", "Neisseria", "Nesterenkonia", "Oryza", "Paenibacillus", "Paracoccus", "Prevotella", "Providencia", "Roseomonas", "Salmonella", "Alishewanella", "Azospirillum", "Bifidobacterium", "Bosea", "Dialister", "Finegoldia", "Jeotgalicoccus", "Listeria", "Ralstonia", "Rubrobacter", "Actinomycetospora", "Anaerococcus", "Comamonas", "Granulicatella", "Rahnella", "Rheinheimera", "Sphingomonas", "Spirosoma", "Xanthobacter", "Actinobacillus", "Flavobacterium", "Rothia", "Terracoccus", "Prevotella.1", "Geobacillus", "Photobacterium", "Simplicispira", "Tepidiphilus", "Brevibacterium", "Hydrogenophilus", "Janibacter", "Leptolyngbya", "Microbispora", "Modestobacter", "Sphingobium", "Stenotrophomonas", "Citrobacter", "Lautropia", "Methylibium", "Methylobacterium", "Facklamia", "Pelomonas", "Thauera", "Psychrobacter", "Alcanivorax", "Blastomonas", "Chryseobacterium", "Enterococcus", "Flavihumibacter", "Kerstersia", "Petrobacter", "Sphingobacterium", "X02d06", "Deinococcus", "Kocuria", "Novispirillum", "Anoxybacillus", "Aquabacterium", "Demequina", "Roseateles", "Sanguibacter", "Treponema", "Xanthomonas", "Wautersiella", "Nevskia", "Phenylobacterium", "Arthrobacter", "Burkholderia", "Sphingopyxis", "Chroococcidiopsis", "Pantoea", "Alloiococcus", "Blastococcus", "Desulfotomaculum", "Microbacterium", "Lysobacter", "Azospira", "Desulfovibrio", "Rhodobacter", "Schlegelella", "Z.35", "Atopobium", "Kineococcus", "Nocardioides", "Oribacterium", "Perlucidibaca", "Solibacillus", "Bacteroides", "Curtobacterium", "Herbaspirillum", "Mesorhizobium", "Herminiimonas", "Acetonema", "Ewingella", "Pedobacter", "Aquicella", "Brochothrix", "Gordonia", "Paucisalibacillus", "Virgibacillus", "Blautia", "Leptotrichia", "Planomicrobium", "Rubellimicrobium", "Pseudoclavibacter", "Azomonas", "Hyphomicrobium", "Trachelomonas", "Devosia", "Pseudonocardia", "Dyadobacter", "Williamsia", "Capnocytophaga", "Anaerolinea", "Abiotrophia", "Fusibacter", "Fusobacterium", "Leptothrix", "Peptoniphilus", "Phormidium", "Thermus", "Brumimicrobium", "Carnobacterium", "Sneathia", "Methyloversatilis", "Pseudoxanthomonas", "Thermicanus", "WAL_1855D", "Catenibacterium", "Ramlibacter", "Eubacterium", "SMB53", "Rubrivivax", "Pinus", "Orientia", "Aeromicrobium", "Frigoribacterium", "Janthinobacterium", "Rhodococcus", "Escherichia", "Tessaracoccus", "Meiothermus", "Mucilaginibacter", "Streptomyces", "Moraxella", "Campylobacter", "Cardiobacterium", "Hylemonella", "Clostridium", "Aeromonas" ], "rows": 93, "table": true, "tojson": true }, { "name": "SnpFile", "title": "'mbQTL' \"SnpFile\"", "object": "SnpFile", "file": "SnpFile.rda", "class": [ "data.frame" ], "fields": [ "chr1.171282963_T", "chr2.215401061_A", "chr2.241072116_A", "chr3.6697902_T", "chr3.6699553_G", "chr7.138993603_C", "chr8.106149607_T", "chr9.135681285_A", "chr10.93532238_A", "chr12.32724664_T", "chr12.128184538_T", "chr13.37231354_G", "chr15.89411735_C", "chr15.89411741_T", "chr16.6827159_A", "chr19.16697358_G", "chr19.47571010_C", "chr20.51096383_C", "chr22.44156886_T", "chrX.24396162_C", "chrX.24396268_G", "chrX.24408658_G", "chrX.49752540_A", "chrX.49775416_G", "chrX.111951522_G", "chrX.111968160_T" ], "rows": 93, "table": true, "tojson": true } ], "_help": [ { "page": "mbQTL-package", "title": "title 'mbQTL' is a package for microbial QTL/GWAS Analysis", "topics": [ "mbQTL-package", "mbQTL" ] }, { "page": "allToAllProduct", "title": "'allToAllProduct' creates a dataframe of snp and taxa correlations", "topics": [ "allToAllProduct" ] }, { "page": "BinarizeMicrobe", "title": "'binarizeMicrobe' binarizes microbe abundace file based on user's cutoff", "topics": [ "binarizeMicrobe" ] }, { "page": "coringTaxa", "title": "'coringTaxa' creates correlation dataframe for taxa", "topics": [ "coringTaxa" ] }, { "page": "CovFile", "title": "'mbQTL' \"CovFile\"", "topics": [ "CovFile" ] }, { "page": "histPvalueLm", "title": "histPvalueLm a histogram of Taxa and SNP linear regression analysis. This function creates a histogram object of all SNPs with all taxa Linear regression analysis p values.", "topics": [ "histPvalueLm" ] }, { "page": "linearTaxaSnp", "title": "linearTaxaSnp Performs linear regression analysis between taxa and SNPs and returns concordance statistics", "topics": [ "linearTaxaSnp" ] }, { "page": "LogitPlotSnpTaxa", "title": "logitPlotSnpTaxa produces bar plots for counts of ref vs alt vs het allells for particular rsID taxa combinations", "topics": [ "logitPlotSnpTaxa" ] }, { "page": "LogRegSNPsTaxa", "title": "'logRegSnpsTaxa' Performs logistic regression analysis between taxa and SNPs and returns concordance statistics", "topics": [ "logRegSnpsTaxa" ] }, { "page": "mbQtlCorHeatmap", "title": "'mbQtlCorHeatmap' for making heatmap for snp, taxa rho values", "topics": [ "mbQtlCorHeatmap" ] }, { "page": "metagenomeSeqObj", "title": "'mbQTL' \"metagenomeSeqObj\" \"MetagenomSeqObj\" is an 'MRexperiment' object format of the \"microbeAbund\" file.", "topics": [ "metagenomeSeqObj" ] }, { "page": "metagenomeSeqToMbqtl", "title": "Written by Mercedeh Movassagh mercedeh@ds.dfci.harvard.edu, January 2023: metagenomeSeqToMbqtl Converts metagenomeSeq obj to compatible taxa dataframe", "topics": [ "metagenomeSeqToMbqtl" ] }, { "page": "microbeAbund", "title": "'mbQTL' \"microbiomeAbund\" File", "topics": [ "microbeAbund" ] }, { "page": "prepareCorData", "title": "'prepareCorData' prpares and joins snp-taxa and taxa-taxa correlation file.", "topics": [ "prepareCorData" ] }, { "page": "qqPlotLm", "title": "qqPlotLm creates QQ-Plot of all SNPs with all taxa Linear regression analysis This function creates QQ-Plot object of all SNPs with all taxa Linear regression analysis of expected versus observed P values", "topics": [ "qqPlotLm" ] }, { "page": "RegSNP", "title": "'RegSnp' creates a dataframe of parsed long snp files", "topics": [ "RegSnp" ] }, { "page": "SnpFile", "title": "'mbQTL' \"SnpFile\"", "topics": [ "SnpFile" ] }, { "page": "TaxaSnpCor", "title": "'taxaSnpCor' for estimation of the rho value between snp, taxa correlations across datasets", "topics": [ "taxaSnpCor" ] } ], "_readme": "https://github.com/bioc/mbQTL/raw/HEAD/README.md", "_rundeps": [ "backports", "Biobase", "BiocGenerics", "bitops", "broom", "caTools", "cellranger", "cli", "codetools", "cpp11", "crayon", "dplyr", "farver", "foreach", "generics", "ggplot2", "glmnet", "glue", "gplots", "gtable", "gtools", "hms", "isoband", "iterators", "KernSmooth", "labeling", "lattice", "lifecycle", "limma", "locfit", "magrittr", "Matrix", "MatrixEQTL", "matrixStats", "metagenomeSeq", "pheatmap", "pillar", "pkgconfig", "prettyunits", "progress", "purrr", "R6", "RColorBrewer", "Rcpp", "RcppEigen", "readxl", "rematch", "rlang", "S7", "scales", "shape", "statmod", "stringi", "stringr", "survival", "tibble", "tidyr", "tidyselect", "utf8", "vctrs", "viridisLite", "withr", "Wrench" ], "_vignettes": [ { "source": "mbQTL_Vignette.Rmd", "filename": "mbQTL_Vignette.html", "title": "mbQTL_Vignette", "author": "Mercedeh Movassagh", "engine": "knitr::rmarkdown", "headings": [ "Introduction", "Data upload.", "Import data", "Part A. Linear regression", "Part B. Correlation analysis (rho estimation)", "Part C. 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