{ "_id": "6a10403dacfb0bcc41c9d0a0", "Package": "Anaconda", "Type": "Package", "Title": "Targeted Differential and Global Enrichment Analysis of\nTaxonomic Rank by Shared Asvs", "Version": "0.1.5", "Authors@R": "person('Pierre-Louis', 'Stenger', role = c('cre','aut'), email = 'Pierrelouis.stenger@gmail.com')", "Author": "Pierre-Louis Stenger [cre, aut]", "Maintainer": "Pierre-Louis Stenger ", "Description": "Targeted differential and global enrichment analysis of\ntaxonomic rank by shared ASVs (Amplicon Sequence Variant), for\nhigh-throughput eDNA sequencing of fungi, bacteria, and\nmetazoan. Actually works in two steps: I) Targeted differential\nanalysis from QIIME2 data and II) Global analysis by Taxon\nMann-Whitney U test analysis from targeted analysis (I) (I)\nEstimate variance-mean dependence in count/abundance ASVs data\nfrom high-throughput sequencing assays and test for\ndifferential represented ASVs based on a model using the\nnegative binomial distribution. (II) NCBITaxon_MWU uses\ncontinuous measure of significance (such as fold-change or\n-log(p-value)) to identify NCBITaxon that are significantly\nenriches with either up- or down-represented ASVs. If the\nmeasure is binary (0 or 1) the script will perform a typical\n'NCBITaxon enrichment' analysis based Fisher's exact test: it\nwill show NCBITaxon over-represented among the ASVs that have 1\nas their measure. On the plot, different fonts are used to\nindicate significance and color indicates enrichment with\neither up (red) or down (blue) regulated ASVs. No colors are\nshown for binary measure analysis. The tree on the plot is\nhierarchical clustering of NCBITaxon based on shared ASVs.\nCategories with no branch length between them are subsets of\neach other. The fraction next to the category name indicates\nthe fraction of 'good' ASVs in it; 'good' ASVs are the ones\nexceeding the arbitrary absValue cutoff (option in\ntaxon_mwuPlot()). For Fisher's based test, specify\nabsValue=0.5. This value does not affect statistics and is used\nfor plotting only. The original idea was for genes differential\nexpression analysis from Wright et al (2015)\n; adapted here for taxonomic\nanalysis. The 'Anaconda' package makes it possible to carry out\nthese analyses by automatically creating several graphs and\ntables and storing them in specially created subfolders. You\nwill need your QIIME2 pipeline output for each kingdom (eg;\nFungi and/or Bacteria and/or Metazoan): i) taxonomy.tsv, ii)\ntaxonomy_RepSeq.tsv, iii) ASV.tsv and iv)\nSampleSheet_comparison.txt (the latter being created by you).", "License": "GPL (>= 2)", "URL": "https://github.com/PLStenger/Anaconda", "BugReports": "https://github.com/PLStenger/Anaconda/issues", "Encoding": "UTF-8", "RoxygenNote": "7.2.1", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-11 08:24:08 UTC", "User": "root" }, "Config/pak/sysreqs": "zlib1g-dev", "Repository": "https://plstenger.r-universe.dev", "Date/Publication": "2025-10-09 12:59:05 UTC", "RemoteUrl": "https://github.com/plstenger/anaconda", "RemoteRef": "HEAD", "RemoteSha": "022a0d34c8e61b7a7f55f8100e90ee58a9006e2d", "MD5sum": "2d02d285db6e7c8cfb7bf4e89e99f9ba", "_user": "plstenger", "_type": "src", "_file": "Anaconda_0.1.5.tar.gz", "_fileid": "0982592a1817ab6aa345ddd6f767d0fba45c671d14ab46f7ee8799c581b33ae1", "_filesize": 4109944, 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"title": "heatmap_data_dasva", "topics": [ "heatmap_data_dasva" ] }, { "page": "heatmap_samples_hclust", "title": "heatmap_samples_hclust", "topics": [ "heatmap_samples_hclust" ] }, { "page": "heatmap_samples_matrix", "title": "heatmap_samples_matrix", "topics": [ "heatmap_samples_matrix" ] }, { "page": "heatmap_taxo", "title": "heatmap_taxo", "topics": [ "heatmap_taxo" ] }, { "page": "input_global_analysis", "title": "input_global_analysis", "topics": [ "input_global_analysis" ] }, { "page": "Metazoan", "title": "Metazoan", "topics": [ "Metazoan" ] }, { "page": "move_files", "title": "move_files", "topics": [ "move_files" ] }, { "page": "mwuTest", "title": "mwuTest", "topics": [ "mwuTest" ] }, { "page": "PCA_data_dasva", "title": "PCA_data_dasva", "topics": [ "PCA_data_dasva" ] }, { "page": "plotDispASVs", "title": "plotDispASVs", "topics": [ "plotDispASVs" ] }, { "page": "plotMA.dasva", "title": "plotMA.dasva", "topics": [ "plotMA.dasva" ] }, { "page": "plotPCA.san", "title": 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