Package omicplotr. March 15, 2019
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1 Package omicplotr March 15, 2019 Title Visual Exploration of Omic Datasets Using a Shiny App Version Date biocviews ImmunoOncology, Software, DifferentialExpression, GeneExpression, GUI, RNASeq, DNASeq, Metagenomics, Transcriptomics, Bayesian, Microbiome, Visualization, Sequencing A Shiny app for visual exploration of omic datasets as compositions, and differential abundance analysis using ALDEx2. Useful for exploring RNA-seq, meta-rna-seq, 16s rrna gene sequencing with visualizations such as principal component analysis biplots (coloured using metadata for visualizing each variable), dendrograms and stacked bar plots, and effect plots (ALDEx2). Input is a table of counts and metadata file (if metadata exists), with options to filter data by count or by metadata to remove low counts, or to visualize select samples according to selected metadata. Imports ALDEx2 (>= 1.8.0), compositions, grdevices, knitr, matrixstats, rmarkdown, shiny, stats, vegan, zcompositions VignetteBuilder knitr Depends R (>= 3.5) License MIT + file LICENSE LazyData true Encoding UTF-8 RoxygenNote git_url git_branch RELEASE_3_8 git_last_commit 3e141f1 git_last_commit_date Date/Publication Author Daniel Giguere [aut, cre], Jean Macklaim [aut], Greg Gloor [aut] Maintainer Daniel Giguere <dgiguer@uwo.ca> 1
2 2 internal R topics documented: omicplotr-package internal metadata omicplotr.run otu_table Index 5 omicplotr-package omicplotr A Shiny app for visual exploration of omic datasets as compositions, and differential abundance analysis using ALDEx2. Useful for exploring RNA-seq, meta-rna-seq, 16s rrna gene sequencing and more with visualizations such as principal component analysis biplot (coloured using metadata for visualizing each variable), association plots (igraph), dendrograms and stacked bar plots, and effect plots (ALDEx2). Input is a table of counts and metadata file (if metadata exists), with options to filter data by count or by metadata to remove low counts, or to visualize select samples according to selected metadata. The Shiny app s graphical user interface facilitates visual exploration for new and experienced users of R alike. Details To launch the shiny app in your default browser, type omicplotr.run(). Daniel Giguere, Jean Macklaim, Greg Gloor See Also omicplotr.run. internal Internal omicplotr functions. Internal functions for the app which are not intended to be called by the user. Please refer to omicplotr.run. Daniel Giguere, Greg Gloor.
3 metadata 3 Examples # These functions are not meant to be called by the user. However, some # functions can be useful. # Filter out your OTU table to remove rows that sum to less than 10. d <- omicplotr.filter(otu_table, min.reads = 10) metadata Vaginal microbiome OTU table metadata Associated metadata to otu_table. data(metadata) Format A data frame with 297 rows and 35 columns, where rows are samples and columns are collected metadata. References Macklaim et al (2014). Microb Ecol Health Dis. doi: See Also otu_table omicplotr.run Run omicplotr Shiny app. Launches Shiny for omicplotr in default browser. This graphical user interface facilitates visual exploration of datasets for both new and experienced R users alike. omicplotr.run() Value There is no value!
4 4 otu_table Daniel Giguere Examples # To run omicplotr, use `omicplotr.run()` function. This will open the shiny # app in your default browser. # omicplotr.run() # After running omicplotr.run(), you can filter your data and make a PCA # biplot. Internal functions are not mean to be called by the user. d.filt <- omicplotr.filter(otu_table) otu_table Vaginal microbiome OTU table Format This dataset contains a count table of operational taxonomic units (OTUs) from a 16s rrna gene sequencing experiment characterising changes in bacterial microbiota from oral antimicrobial or probiotic treatments. Associated metadata is contained in metadata. A data frame with 77 rows and 298 columns. The last column contains taxonomic information for each OTU. Samples are columns, OTUs are rows. References Macklaim et al (2014). Microb Ecol Health Dis. doi:
5 Index internal, 2 metadata, 3, 4 omicplotr (omicplotr-package), 2 omicplotr-package, 2 omicplotr.anosim (internal), 2 omicplotr.clr (internal), 2 omicplotr.colouredpca (internal), 2 omicplotr.colvec (internal), 2 omicplotr.filter (internal), 2 omicplotr.getremovedfeatures (internal), 2 omicplotr.getremovedsamples (internal), 2 omicplotr.metadatafilter (internal), 2 omicplotr.permanova (internal), 2 omicplotr.report (internal), 2 omicplotr.run, 2, 3 otu_table, 3, 4 5
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Package ALDEx2. April 4, 2019
Type Package Package ALDEx2 April 4, 2019 Title Analysis Of Differential Abundance Taking Sample Variation Into Account Version 1.14.1 Date 2017-10-11 Author Greg Gloor, Ruth Grace Wong, Andrew Fernandes,
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ALDEx2: ANOVA-Like Differential Expression tool for compositional data
ALDEx2: ANOVA-Like Differential Expression tool for compositional data Greg Gloor October 30, 2017 Contents 1 Why the ALDEx2 package? 1 2 Introduction 1 3 Installation 3 4 Quick example with selex example
ALDEx2: ANOVA-Like Differential Expression tool for compositional data
ALDEx2: ANOVA-Like Differential Expression tool for compositional data Greg Gloor October 30, 2018 Contents 1 Why the ALDEx2 package? 1 2 Introduction 1 3 Installation 3 4 Quick example with selex example
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