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'))

Peer review:

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-1.31.0(bioc 3.20)PathoStat-1.30.0(bioc 3.19)

microbiomemetagenomicsgraphandnetworkmicroarraypatternlogicprincipalcomponentsequencingsoftwarevisualizationrnaseqimmunooncology

5.90 score 8 stars 7 scripts 366 downloads 32 exports 198 dependencies

Last updated 23 days agofrom:1f65914ec5. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 30 2024
R-4.5-winNOTEOct 31 2024
R-4.5-linuxNOTEOct 30 2024
R-4.4-winNOTEOct 31 2024
R-4.4-macNOTEOct 31 2024
R-4.3-winNOTEOct 31 2024
R-4.3-macNOTEOct 31 2024

Exports:Bootstrap_LOOCV_LR_AUCChisq_Test_PamfindRAfromCountfindTaxonMatfindTaxonomyfindTaxonomy300Fisher_Test_PamGET_PAMgetShinyInputgetShinyInputCombatgetShinyInputOriggetSignatureFromMultipleGlmnetgrepTidloadPathoscopeReportsloadPstatlog2CPMLOOAUC_simple_multiple_noplot_one_dfLOOAUC_simple_multiple_one_dfpathostat1percentphyloseq_to_edgeRplotPCAPlotlyplotPCoAPlotlyreadPathoscopeDatarunPathoStatsavePstatsetShinyInputsetShinyInputCombatsetShinyInputOrigsummarizeTableTranslateIdToTaxLevelWilcox_Test_df

Dependencies:abindade4apeaskpassbase64encBHBiobaseBiocGenericsBiocManagerBiocParallelBiocStylebiomformatBiostringsbitopsbookdownbrewbriobslibcachemcallrcaToolscirclizeclicliprclueclustercodetoolscolorspacecommonmarkComplexHeatmapcorpcorcpp11crayoncredentialscrosstalkcurldata.tableDelayedArraydescDESeq2devtoolsdiffobjdigestdoParalleldownlitdplyrDTedgeRellipsisevaluatefansifarverfastmapfontawesomeforeachformatRfsfutile.loggerfutile.optionsgdatagenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesgertGetoptLongggplot2ghgitcredsglmnetGlobalOptionsgluegmodelsgplotsgtablegtoolshighrhtmltoolshtmlwidgetshttpuvhttrhttr2igraphiniIRangesisobanditeratorsjquerylibjsonliteKernSmoothknitrlabelinglambda.rlaterlatticelazyevallifecyclelimmalocfitmagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemgcvmimeminiUImulttestmunsellnlmeopensslpermutephyloseqpillarpixmappkgbuildpkgconfigpkgdownpkgloadplotlyplyrpngpraiseprettyunitsprocessxprofvispromisespspurrrR6raggrappdirsrcmdcheckRColorBrewerRcppRcppArmadilloRcppEigenrematch2remotesrentrezreshape2rhdf5rhdf5filtersRhdf5librjsonrlangrmarkdownROCRroxygen2rprojrootrstudioapirversionsS4ArraysS4VectorssassscalessessioninfoshapeshinyshinyjssnowsourcetoolsspSparseArraystatmodstringistringrSummarizedExperimentsurvivalsyssystemfontstestthattextshapingtibbletidyrtidyselecttinytexUCSC.utilsurlcheckerusethisutf8vctrsveganviridisLitewaldowebshotwhiskerwithrxfunXMLxml2xopenxtableXVectoryamlzipzlibbioc

Run PathoStat

Rendered fromPathoStat-vignette.Rmdusingknitr::rmarkdownon Oct 30 2024.

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

Readme and manuals

Help Manual

Help pageTopics
Do bootstrap and LOOCVBootstrap_LOOCV_LR_AUC
Given PAM and disease/control annotation, do Chi-square test for each row of PAMChisq_Test_Pam
Return the Relative Abundance (RA) data for the given count OTU tablefindRAfromCount
Find the Taxonomy Information MatrixfindTaxonMat
Find the taxonomy for unlimited tidsfindTaxonomy
Find the taxonomy for maximum 300 tidsfindTaxonomy300
Given PAM and disease/control annotation, do Chi-square test for each row of PAMFisher_Test_Pam
Format taxonomy table for renderingformatTaxTable
transform cpm counts to presence-absence matrixGET_PAM
Getter function to get the shinyInput optiongetShinyInput
Getter function to get the shinyInputCombat optiongetShinyInputCombat
Getter function to get the shinyInputOrig optiongetShinyInputOrig
Use Lasso to do feature selectiongetSignatureFromMultipleGlmnet
Greps the tid from the given identifier stringgrepTid
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 objectloadPstat
Compute log2(counts per mil reads) and library size for each samplelog2CPM
LOOCVLOOAUC_simple_multiple_noplot_one_df
LOOCV with ROC curveLOOAUC_simple_multiple_one_df
PathoStat class to store PathoStat input data including phyloseq objectPathoStat-class pathostat1
Compute percentagepercent
Convert phyloseq OTU count data into DGEList for edgeR packagephyloseq_to_edgeR
Plot PCAplotPCAPlotly
Plot PCoAplotPCoAPlotly
pathostat object generated from example pathoscope report filespstat pstat_data
Reads the data from PathoScope reports and returns a list of final guess relative abundance and count datareadPathoscopeData
Statistical Microbiome Analysis on the pathostat input and generates a html report and produces interactive shiny app plotsrunPathoStat
Save the pathostat object to R data(.rda) filesavePstat
Setter function to set the shinyInput optionsetShinyInput
Setter function to set the shinyInputCombat optionsetShinyInputCombat
Setter function to set the shinyInputOrig optionsetShinyInputOrig
Summarize samplesummarizeTable
Find the taxonomy for the given taxon id nameTranslateIdToTaxLevel
Mann-whitney test for a dataframeWilcox_Test_df