Package: ANCOMBC 2.15.0

Huang Lin

ANCOMBC: Microbiome differential abudance and correlation analyses with bias correction

ANCOMBC is a package containing differential abundance (DA) and correlation analyses for microbiome data. Specifically, the package includes Analysis of Compositions of Microbiomes with Bias Correction 2 (ANCOM-BC2), Analysis of Compositions of Microbiomes with Bias Correction (ANCOM-BC), and Analysis of Composition of Microbiomes (ANCOM) for DA analysis, and Sparse Estimation of Correlations among Microbiomes (SECOM) for correlation analysis. Microbiome data are typically subject to two sources of biases: unequal sampling fractions (sample-specific biases) and differential sequencing efficiencies (taxon-specific biases). Methodologies included in the ANCOMBC package are designed to correct these biases and construct statistically consistent estimators.

Authors:Huang Lin [cre, aut]

ANCOMBC_2.15.0.tar.gz
ANCOMBC_2.15.0.zip(r-4.7)ANCOMBC_2.15.0.zip(r-4.6)ANCOMBC_2.15.0.zip(r-4.5)
ANCOMBC_2.15.0.tgz(r-4.6-any)ANCOMBC_2.15.0.tgz(r-4.5-any)
ANCOMBC_2.15.0.tar.gz(r-4.7-any)ANCOMBC_2.15.0.tar.gz(r-4.6-any)
ANCOMBC_2.15.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
ANCOMBC/json (API)

# Install 'ANCOMBC' in R:
install.packages('ANCOMBC', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/frederickhuanglin/ancombc/issues

Datasets:
  • QMP - Quantitative Microbiome Project data

On BioConductor:ANCOMBC-2.15.0(bioc 3.24)ANCOMBC-2.14.0(bioc 3.23)

differentialexpressionmicrobiomenormalizationsequencingsoftwareancomancombcancombc2correlationdifferential-abundance-analysissecom

10.76 score 138 stars 1 packages 918 scripts 2 mentions 7 exports 120 dependencies

Last updated from:d823bf01e6. Checks:1 WARNING, 9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksWARNING228
linux-devel-x86_64OK372
source / vignettesOK1026
linux-release-x86_64OK407
macos-release-arm64OK188
macos-oldrel-arm64OK176
windows-develOK282
windows-releaseOK259
windows-oldrelOK256
wasm-releaseOK243

Exports:ancomancombcancombc2data_sanity_checksecom_distsecom_linearsim_plnm

Dependencies:askpassbackportsbase64encbitbit64bootbslibcachemcellrangercheckmateclassclicliprclustercodetoolscolorspacecpp11crayoncurldata.tableDescToolsdigestdoParalleldoRNGe1071energyevaluateExactexpmfarverfastmapfontawesomeforcatsforeachforeignFormulafsggplot2gldgluegridExtragslgtablegtoolshavenhighrHmischmshtmlTablehtmltoolshtmlwidgetshttrisobanditeratorsjquerylibjsonliteknitrlabelinglatticelifecyclelme4lmerTestlmommagrittrMASSMatrixmemoisemimeminqamultcompmvtnormnlmenloptrnnetnumDerivopensslpillarpkgconfigprettyunitsprogressproxyquadprogR6rappdirsrbibutilsRColorBrewerRcppRcppEigenRdpackreadrreadxlreformulasrematchrlangrmarkdownrngtoolsrootSolverpartrstudioapiS7sandwichsassscalesstringistringrsurvivalsysTH.datatibbletidyselecttinytextzdbutf8vctrsviridisLitevroomwithrxfunyamlzoo

ANCOM-BC2 Tutorial
1. Introduction | 2. Installation | 3. Run ANCOM-BC2 on a simulated dataset | 3.1 Generate simulated data | 3.2 Run ancombc2 function | 3.3 Power and FDR | 4. Benchmark the performance of ANCOM-BC2 on a null dataset | 4.1 Import example data | 4.2 Permute the bmi label | 4.3 Run ancombc2 function | 4.4 Visualization | 5. Run ANCOM-BC2 on a real cross-sectional dataset | 5.1 Import example data | 5.2 Run ancombc2 function using the phyloseq object | 5.3 Structural zeros (taxon presence/absence) | 5.4 ANCOM-BC2 primary analysis | Results for age | Results for bmi | 5.5 ANCOM-BC2 global test | 5.6 ANCOM-BC2 multiple pairwise comparisons | 5.7 ANCOM-BC2 multiple pairwise comparisons against a pre-specified group (Dunnett's type of test) | 5.8 ANCOM-BC2 pattern analysis | 5.9 Run ancombc2 function using the tse object | 5.10 Run ancombc2 function by directly providing the abundance and metadata | 6. Run ANCOM-BC2 on a real longitudinal dataset | 6.1 Import example data | 6.2 Run ancombc2 function using the phyloseq object | 6.3 ANCOM-BC2 primary analysis | 6.4 ANCOM-BC2 global test | 6.5 ANCOM-BC2 multiple pairwise comparisons | 6.6 ANCOM-BC2 Dunnett's type of test | 6.7 ANCOM-BC2 pattern analysis | 6.8 Run ancombc2 function using the tse object | 6.9 Run ancombc2 function by directly providing the abundance and metadata | 7. Bias-corrected log abundances | Session information | References
Rendered fromANCOMBC2.Rmdusingknitr::rmarkdown

Last update: 2026-04-27
Started: 2022-10-11

Tutorial on Data Sanity and Integrity Checks
1. Introduction | 2. Installation | 3. Examples | 3.1 Import a phyloseq object | 3.2 Import a tse object | 3.3 Import a matrix or data.frame | Session information | References
Rendered fromdata_sanity_check.Rmdusingknitr::rmarkdown

Last update: 2025-03-16
Started: 2024-10-21

SECOM Tutorial
1. Introduction | 2. Installation | 3. Example Data | 4. Run SECOM on a Single Ecosystem | 4.1 Run secom functions using the phyloseq object | 4.2 Visualizations | Pearson correlation with thresholding | Pearson correlation with p-value filtering | Distance correlation with p-value filtering | 4.3 Run secom functions using the tse object | 4.4 Run secom functions by directly providing the abundance and metadata | 5. Run SECOM on Multiple Ecosystems | 5.1 Data manipulation | 5.2 Run secom functions using the phyloseq object | 5.3 Visualizations | 5.4 Run secom functions using the tse object | 5.5 Run secom functions by directly providing the abundance and metadata | Session information | References
Rendered fromSECOM.Rmdusingknitr::rmarkdown

Last update: 2025-01-07
Started: 2022-10-11

ANCOM Tutorial
1. Introduction | 2. Installation | 3. Run ANCOM on a real cross-sectional dataset | 3.1 Import example data | 3.2 Run ancom function using phyloseq data | 3.3 Scatter plot for W statistics | 3.4 Run ancom function using tse data | 3.5 Run ancom function by directly providing the abundance and metadata | 4. Run ANCOM on a real longitudinal dataset | 4.1 Import example data | 4.2 Run ancom function using phyloseq data | 4.3 Visualization for W statistics | 4.4 Run ancom function using tse data | 4.5 Run ancom function by directly providing the abundance and metadata | Session information | References
Rendered fromANCOM.Rmdusingknitr::rmarkdown

Last update: 2024-10-21
Started: 2022-10-11

ANCOM-BC Tutorial
1. Introduction | 2. Installation | 3. Example Data | 4 ANCOM-BC Implementation | 4.1 Run ancombc function using the phyloseq object | 4.2 ANCOMBC primary result | LFC | SE | Test statistic | P-values | Adjusted p-values | Differentially abundant taxa | Bias-corrected abundances | Visualization for age | Visualization for BMI | 4.3 ANCOMBC global test result | Test statistics | Visualization | 4.4 Run ancombc function using the tse object | 4.5 Run ancombc function by directly providing the abundance and metadata | Session information | References
Rendered fromANCOMBC.Rmdusingknitr::rmarkdown

Last update: 2024-10-21
Started: 2020-08-10