{ "_id": "6ae76ade818c9e3ef6dbc192", "Package": "mina", "Title": "Microbial community dIversity and Network Analysis", "Version": "1.21.0", "Authors@R": "c(person(\"Rui\", \"Guan\", email = \"guan@mpipz.mpg.de\", role = c(\"aut\", \"cre\")),\nperson(\"Ruben\", \"Garrido-Oter\", email = \"garridoo@mpipz.mpg.de\", role = \"ctb\"))", "Description": "An increasing number of microbiome datasets have been\ngenerated and analyzed with the help of rapidly developing\nsequencing technologies. At present, analysis of taxonomic\nprofiling data is mainly conducted using composition-based\nmethods, which ignores interactions between community members.\nBesides this, a lack of efficient ways to compare microbial\ninteraction networks limited the study of community dynamics.\nTo better understand how community diversity is affected by\ncomplex interactions between its members, we developed a\nframework (Microbial community dIversity and Network Analysis,\nmina), a comprehensive framework for microbial community\ndiversity analysis and network comparison. By defining and\nintegrating network-derived community features, we greatly\nreduce noise-to-signal ratio for diversity analyses. A\nbootstrap and permutation-based method was implemented to\nassess community network dissimilarities and extract\ndiscriminative features in a statistically principled way.", "License": "GPL", "Encoding": "UTF-8", "LazyData": "true", "VignetteBuilder": "knitr", "RoxygenNote": "7.1.1", "Collate": "'RcppChk.R' 'RcppExports.R' 'all_classes.R' 'all_generics.R'\n'adj.R' 'all_accessors.R' 'bs_pm.R' 'check.R' 'com_dis.R'\n'com_plot.R' 'com_r2.R' 'data.R' 'dmr.R' 'fit_tabs.R'\n'get_rep.R' 'net_cls.R' 'net_cls_tab.R' 'net_dis.R'\n'net_dis_indi.R' 'net_dis_pcoa.R' 'net_dis_plot.R'\n'net_grp_cmp.R' 'net_node_cmp.R' 'norm_tab.R'", "biocViews": "Software, WorkflowStep", "BugReports": "https://github.com/Guan06/mina", "Config/pak/sysreqs": "cmake make libicu-dev libuv1-dev", "Repository": "https://bioc.r-universe.dev", "Date/Publication": "2026-04-28 12:54:33 UTC", "RemoteUrl": "https://github.com/bioc/mina", "RemoteRef": "HEAD", "RemoteSha": "a79adb620856874ce9f258a7ddb55b5627793871", "NeedsCompilation": "yes", "Packaged": { "Date": "2026-11-01 13:58:59 UTC", "User": "root" }, "Author": "Rui Guan [aut, cre],\nRuben Garrido-Oter [ctb]", "Maintainer": "Rui Guan ", "_user": "bioc", "_type": "src", "_file": "mina_1.21.0.tar.gz", "_fileid": "https://r2.ropensci.org/15eef23c442154622133227399b26d64364bf0f02ec6f5aba3d9cff68cc25bc6", "_filesize": 4407550, "_sha256": "15eef23c442154622133227399b26d64364bf0f02ec6f5aba3d9cff68cc25bc6", "_expires": "2027-02-09T16:37:47.000Z", "_created": "2026-11-01T13:58:59.000Z", "_published": "2026-11-01T16:37:49.923Z", "_upstream": "https://github.com/bioc/mina", "_status": "success", "_maintainer": { "name": "Rui Guan", "email": "guan@mpipz.mpg.de" }, "_jobs": [ { "job": 124869876274, "time": 167, "config": "bioc-checks", "r": "4.6.2", "check": "WARNING", "artifact": "13087656471" }, { "job": 124869876264, "time": 274, "config": "linux-devel-arm64", "r": "4.7.0", "check": "WARNING", "artifact": "13085499754" }, { "job": 124869876312, 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Austral Ecology, 26: 32-46.", "topics": [ "com_r2,mina,ANY-method", "com_r2,mina,character-method" ] }, { "page": "cp_cor", "title": "Function for correlation coefficient calculation.", "topics": [ "cp_cor" ] }, { "page": "data-hmp", "title": "Internal testing data of HMP project, including quantitative table (hmp_otu) and descriptive table (hmp_des) for testing.", "topics": [ "data-hmp", "hmp" ] }, { "page": "data-maize", "title": "Internal testing data of maize project, vegetative stage samples only, including quantitative table (maize_asv.rds) and descriptive table (maize_des.txt) for testing.", "topics": [ "data-maize", "maize" ] }, { "page": "des_accessor", "title": "Setter and getter for the slot `des`, which is the description and meta data of rows in `tab`.", "topics": [ "des", "des,mina-method", "des<-", "des<-,mina-method" ] }, { "page": "dis_stat_accessor", "title": "Getter for the slots `dis_bs`, `dis_pm` and `dis_stat`.", "topics": [ "dis_bs", "dis_pm", "dis_stat" ] }, { "page": "dis_accessor", "title": "Setter and getter for the slot `dis`.", "topics": [ "dis", "dis,mina-method", "dis<-", "dis<-,mina-method" ] }, { "page": "dmr", "title": "Dimensionality reduction of community dissimilarity / distance for visulization.", "topics": [ "dmr" ] }, { "page": "dmr-matrix", "title": "Dimensionality reduction of the distance matrix.", "topics": [ "dmr,matrix-method" ] }, { "page": "dmr-mina", "title": "Dimensionality reduction of the `dis` included in mina.", "topics": [ "dmr,mina-method" ] }, { "page": "fit_tabs", "title": "Filter the quantitative and descriptive table to make them have the same samples, the intersect samples will be remained.", "topics": [ "fit_tabs" ] }, { "page": "fit_tabs-mina", "title": "Filter the quantitative and descriptive table to make them have the same samples, samples present in both tables are remained. If `norm` table exist in the `mina` object, descriptive table will be filtered again to only keep samples present in `norm`.", "topics": [ "fit_tabs,mina-method" ] }, { "page": "get_net_cls_tab", "title": "Get the cluster table `cls_tab` from quantitative table `norm` and network clustering results `cls`.", "topics": [ "get_net_cls_tab" ] }, { "page": "get_net_cls_tab-matrix-data.frame-method", "title": "Get the cluster table `cls_tab` from quantitative table `norm` and network clustering results `cls`.", "topics": [ "get_net_cls_tab,matrix,data.frame-method" ] }, { "page": "get_r2", "title": "Same function as `com_r2` with matrix and corresponding descriptive table as input.", "topics": [ "get_r2" ] }, { "page": "get_r2-mat", "title": "Function for unexplained variance ratio calculation indicated in Anderson, M.J. 2001. A new method for non-parametric multivariate analysis of variance. Austral Ecology, 26: 32-46.", "topics": [ "get_r2,matrix,ANY,ANY-method", "get_r2,matrix,data.frame,ANY-method", "get_r2,matrix,data.frame,character-method" ] }, { "page": "get_rep-matrix", "title": "Get the representative community members by extracting the most abundant and prevalent compositions.", "topics": [ "get_rep", "get_rep,matrix-method" ] }, { "page": "get_rep-mima", "title": "Get the representative community members.", "topics": [ "get_rep,mina-method" ] }, { "page": "hmp_des", "title": "Design file for HMP project, including 2711 samples in total.", "topics": [ "hmp_des" ] }, { "page": "hmp_otu", "title": "OTU table of HMP project, data downloaded from https://www.hmpdacc.org/hmp/HMQCP/", "topics": [ "hmp_otu" ] }, { "page": "maize_asv", "title": "ASV table of maize project, vegetative stage samples only.", "topics": [ "maize_asv" ] }, { "page": "maize_asv2", "title": "Subset of ASV table of maize project, ASVs appear in less than 100 samples were filtered for later analysis.", "topics": [ "maize_asv2" ] }, { "page": "maize_des", "title": "Design file of maize project, vegetative stage samples only, including 528 samples in total.", "topics": [ "maize_des" ] }, { "page": "maize_des2", "title": "Subset of design file of maize project, 313 samples are included.", "topics": [ "maize_des2" ] }, { "page": "mina-class", "title": "Class \"mina\" includes the quantitative table and descriptive table.", "topics": [ "mina-class" ] }, { "page": "net_cls", "title": "Network clustering of sparsed adjacacency matrix.", "topics": [ "net_cls" ] }, { "page": "net_cls_tab", "title": "Get the cluster table 'cls_tab' from `norm` and `cls`.", "topics": [ "net_cls_tab" ] }, { "page": "net_cls_tab-mina-method", "title": "Get the cluster table `cls_tab` from quantitative table `norm` and network clustering results `cls`.", "topics": [ "net_cls_tab,mina-method" ] }, { "page": "net_cls-matrix", "title": "Network clustering based on the sparsed adjacacency matrix.", "topics": [ "net_cls,matrix,ANY-method", "net_cls,matrix,character-method" ] }, { "page": "net_cls-mina", "title": "Network clustering based on the sparsed adjacacency matrix.", "topics": [ "net_cls,mina,ANY-method", "net_cls,mina,character-method" ] }, { "page": "net_dis", "title": "Calculate the network distance of `multi` and test the significance when `perm` is defined.", "topics": [ "net_dis" ] }, { "page": "net_dis_indi", "title": "Calculate the network distance of bootstrap and permutation when appliable.", "topics": [ "net_dis_indi", "net_dis_indi,character,ANY-method", "net_dis_indi,character,character-method" ] }, { "page": "net_dis_pcoa", "title": "Visulization of spectra network distance as PCoA.", "topics": [ "net_dis_pcoa", "net_dis_pcoa,character-method" ] }, { "page": "net_dis_plot", "title": "Visulization of network distance, average distances are used for tile plot.", "topics": [ "net_dis_plot", "net_dis_plot,mina-method" ] }, { "page": "net_dis-mina", "title": "Calculate the network distance of `multi` and test the significance when `perm` is defined.", "topics": [ "net_dis,mina,ANY-method", "net_dis,mina,character-method" ] }, { "page": "net_grp_cmp", "title": "Compare the group features between networks.", "topics": [ "net_grp_cmp", "net_grp_cmp,character-method" ] }, { "page": "net_node_cmp", "title": "Compare the node features between networks.", "topics": [ "net_node_cmp", "net_node_cmp,character,character-method" ] }, { "page": "norm_tab", "title": "Normalize the slot `tab` for later analysis.", "topics": [ "norm_tab" ] }, { "page": "norm_tab_method_list", "title": "List of normalization methods supported in 'norm_tab'", "topics": [ "norm_tab_method_list" ] }, { "page": "norm_tab-matrix", "title": "Normalize the quantitative matrix.", "topics": [ "norm_tab,matrix,character-method" ] }, { "page": "norm_tab-mina", "title": "Normalize the quantitative table with mina input.", "topics": [ "norm_tab,mina,ANY-method", "norm_tab,mina,character-method" ] }, { "page": "norm_accessor", "title": "Setter and getters for the slot `norm`, normalized `tab` matrix.", "topics": [ "norm", "norm,mina-method", "norm<-", "norm<-,mina-method" ] }, { "page": "pcoa_plot", "title": "Visulization of components distance / dissimilarity in k dimension.", "topics": [ "pcoa_plot", "pcoa_plot,list,data.frame,character-method" ] }, { "page": "tab_accessor", "title": "Setter and getter for the slot `tab`.", "topics": [ "tab", "tab,mina-method", "tab<-", "tab<-,mina-method" ] }, { "page": "tina", "title": "TINA community dissimilarity used in 'com_dis'. Function for `tina` dissimilarity/distance calculation. Modified from Schmidt et al., 2016.", "topics": [ "tina" ] }, { "page": "tina-matrix-method", "title": "Function for `tina` dissimilarity calculation. Modified from Schmidt et al., 2016. Person and Spearman could be used for correlation and weighted and unweighted Jaccard could be used for similarity calculation.", "topics": [ "tina,matrix-method" ] } ], "_readme": "https://github.com/bioc/mina/raw/HEAD/README.md", "_rundeps": [ "apcluster", "backports", "base64enc", "BH", "biganalytics", "biglm", "bigmemory", "bigmemory.sri", "bslib", "cachem", "checkmate", "cli", "cluster", "codetools", "colorspace", "cpp11", "data.table", "DBI", "digest", "evaluate", "expm", "farver", "fastmap", "fontawesome", "foreach", "foreign", "Formula", "fs", "ggplot2", "glue", "gridExtra", "gtable", "highr", "Hmisc", "htmlTable", "htmltools", "htmlwidgets", "isoband", "iterators", "jquerylib", "jsonlite", "knitr", "labeling", "lattice", "lifecycle", "magrittr", "Matrix", "MCL", "memoise", "mime", "nnet", "parallelDist", "plyr", "R6", "rappdirs", "RColorBrewer", "Rcpp", "RcppArmadillo", "RcppEigen", "RcppParallel", "reshape2", "rlang", "rmarkdown", "rpart", "RSpectra", "rstudioapi", "S7", "sass", "scales", "stringi", "stringr", "tinytex", "uuid", "vctrs", "viridisLite", "withr", "xfun", "yaml" ], "_sysdeps": [ { "shlib": "libstdc++", "package": "libstdc++6", "source": "gcc", "version": "16-20260322-1ubuntu1", "name": "c++", "homepage": "http://gcc.gnu.org/", "description": "GNU Standard C++ Library v3" } ], "_vignettes": [ { "source": "mina.Rmd", "filename": "mina.html", "title": "Microbial dIversity and Network Analysis with mina", "author": "Rui Guan", "engine": "knitr::rmarkdown", "headings": [ "Overview", "Input data", "Import data", "Check data format and tidy up", "Diversity analysis of the community", "Data normalization", "Community diversity", "Unexplained variance of community diversity", "Community beta-diversity visualization", "Network inference and clustering", "Correlation coefficient adjacency matrix", "Network clustering", "Higher-order feature based diversity analysis", "Higher-order quantitative table", "Community diversity analysis and comparison", 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