Package: PathoStat 1.33.0

Solaiappan Manimaran

PathoStat: PathoStat Statistical Microbiome Analysis Package

The purpose of this package is to perform Statistical Microbiome Analysis on metagenomics results from sequencing data samples. In particular, it supports analyses on the PathoScope generated report files. PathoStat provides various functionalities including Relative Abundance charts, Diversity estimates and plots, tests of Differential Abundance, Time Series visualization, and Core OTU analysis.

Authors:Solaiappan Manimaran <[email protected]>, Matthew Bendall <[email protected]>, Sandro Valenzuela Diaz <[email protected]>, Eduardo Castro <[email protected]>, Tyler Faits <[email protected]>, Yue Zhao <[email protected]>, Anthony Nicholas Federico <[email protected]>, W. Evan Johnson <[email protected]>

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PathoStat.pdf |PathoStat.html✨
PathoStat/json (API)
NEWS

# Install 'PathoStat' in R:

install.packages('PathoStat', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/mani2012/pathostat/issues

Datasets:

pstat - Pathostat object generated from example pathoscope report files
pstat - Pathostat object generated from example pathoscope report files
pstat - Pathostat object generated from example pathoscope report files
pstat - Pathostat object generated from example pathoscope report files

On BioConductor:PathoStat-1.33.0(bioc 3.21)PathoStat-1.32.0(bioc 3.20)

microbiome metagenomics graphandnetwork microarray patternlogic principalcomponent sequencing software visualization rnaseq immunooncology

5.90 score 8 stars 7 scripts 372 downloads 32 exports 197 dependencies

Last updated 2 months agofrom:1f65914ec5. Checks:OK: 1 NOTE: 6. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Nov 29 2024
R-4.5-win	NOTE	Nov 29 2024
R-4.5-linux	NOTE	Nov 29 2024
R-4.4-win	NOTE	Nov 29 2024
R-4.4-mac	NOTE	Nov 29 2024
R-4.3-win	NOTE	Nov 29 2024
R-4.3-mac	NOTE	Nov 29 2024

Exports:Bootstrap_LOOCV_LR_AUC Chisq_Test_Pam findRAfromCount findTaxonMat findTaxonomy findTaxonomy300 Fisher_Test_Pam GET_PAM getShinyInput getShinyInputCombat getShinyInputOrig getSignatureFromMultipleGlmnet grepTid loadPathoscopeReports loadPstat log2CPM LOOAUC_simple_multiple_noplot_one_df LOOAUC_simple_multiple_one_df pathostat1 percent phyloseq_to_edgeR plotPCAPlotly plotPCoAPlotly readPathoscopeData runPathoStat savePstat setShinyInput setShinyInputCombat setShinyInputOrig summarizeTable TranslateIdToTaxLevel Wilcox_Test_df

Dependencies:abind ade4 ape askpass base64enc BH Biobase BiocGenerics BiocManager BiocParallel BiocStyle biomformat Biostrings bitops bookdown brew brio bslib cachem callr caTools circlize cli clipr clue cluster codetools colorspace commonmark ComplexHeatmap corpcor cpp11 crayon credentials crosstalk curl data.table DelayedArray desc DESeq2 devtools diffobj digest doParallel downlit dplyr DT edgeR ellipsis evaluate fansi farver fastmap fontawesome foreach formatR fs futile.logger futile.options gdata generics GenomeInfoDb GenomeInfoDbData GenomicRanges gert GetoptLong ggplot2 gh gitcreds glmnet GlobalOptions glue gmodels gplots gtable gtools highr htmltools htmlwidgets httpuv httr httr2 igraph ini IRanges isoband iterators jquerylib jsonlite KernSmooth knitr labeling lambda.r later lattice lazyeval lifecycle limma locfit magrittr MASS Matrix MatrixGenerics matrixStats memoise mgcv mime miniUI multtest munsell nlme openssl permute phyloseq pillar pixmap pkgbuild pkgconfig pkgdown pkgload plotly plyr png praise prettyunits processx profvis promises ps purrr R6 ragg rappdirs rcmdcheck RColorBrewer Rcpp RcppArmadillo RcppEigen remotes rentrez reshape2 rhdf5 rhdf5filters Rhdf5lib rjson rlang rmarkdown ROCR roxygen2 rprojroot rstudioapi rversions S4Arrays S4Vectors sass scales sessioninfo shape shiny shinyjs snow sourcetools sp SparseArray statmod stringi stringr SummarizedExperiment survival sys systemfonts testthat textshaping tibble tidyr tidyselect tinytex UCSC.utils urlchecker usethis utf8 vctrs vegan viridisLite waldo webshot whisker withr xfun XML xml2 xopen xtable XVector yaml zip zlibbioc

Run PathoStat

Solaiappan Manimaran, Yue Zhao

Rendered fromPathoStat-vignette.Rmdusingknitr::rmarkdownon Nov 29 2024.

Last update: 2018-10-23
Started: 2018-04-02

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Do bootstrap and LOOCV	Bootstrap_LOOCV_LR_AUC
Given PAM and disease/control annotation, do Chi-square test for each row of PAM	Chisq_Test_Pam
Return the Relative Abundance (RA) data for the given count OTU table	findRAfromCount
Find the Taxonomy Information Matrix	findTaxonMat
Find the taxonomy for unlimited tids	findTaxonomy
Find the taxonomy for maximum 300 tids	findTaxonomy300
Given PAM and disease/control annotation, do Chi-square test for each row of PAM	Fisher_Test_Pam
Format taxonomy table for rendering	formatTaxTable
transform cpm counts to presence-absence matrix	GET_PAM
Getter function to get the shinyInput option	getShinyInput
Getter function to get the shinyInputCombat option	getShinyInputCombat
Getter function to get the shinyInputOrig option	getShinyInputOrig
Use Lasso to do feature selection	getSignatureFromMultipleGlmnet
Greps the tid from the given identifier string	grepTid
Loads all data from a set of PathoID reports. For each column in the PathoID report, construct a matrix where the rows are genomes and the columns are samples. Returns a list where each element is named according to the PathoID column. For example, ret[["Final.Best.Hit.Read.Numbers"]] on the result of this function will get you the final count matrix. Also includes elements "total_reads" and "total_genomes" from the first line of the PathoID report.	loadPathoscopeReports
Load the R data(.rda) file with pathostat object	loadPstat
Compute log2(counts per mil reads) and library size for each sample	log2CPM
LOOCV	LOOAUC_simple_multiple_noplot_one_df
LOOCV with ROC curve	LOOAUC_simple_multiple_one_df
PathoStat class to store PathoStat input data including phyloseq object	PathoStat-class pathostat1
Compute percentage	percent
Convert phyloseq OTU count data into DGEList for edgeR package	phyloseq_to_edgeR
Plot PCA	plotPCAPlotly
Plot PCoA	plotPCoAPlotly
pathostat object generated from example pathoscope report files	pstat pstat_data
Reads the data from PathoScope reports and returns a list of final guess relative abundance and count data	readPathoscopeData
Statistical Microbiome Analysis on the pathostat input and generates a html report and produces interactive shiny app plots	runPathoStat
Save the pathostat object to R data(.rda) file	savePstat
Setter function to set the shinyInput option	setShinyInput
Setter function to set the shinyInputCombat option	setShinyInputCombat
Setter function to set the shinyInputOrig option	setShinyInputOrig
Summarize sample	summarizeTable
Find the taxonomy for the given taxon id name	TranslateIdToTaxLevel
Mann-whitney test for a dataframe	Wilcox_Test_df