adjust_batch {MMUPHin} | R Documentation

## Zero-inflated empirical Bayes adjustment of batch effect in compositional feature abundance data

### Description

`adjust_batch` takes as input a feature-by-sample matrix of microbial abundances, and performs batch effect adjustment given provided batch and optional covariate variables. It returns the batch-adjusted abundance matrix. Additional options and parameters can be passed through the `control` parameter as a list (see details).

### Usage

    adjust_batch(feature_abd, batch, covariates = NULL, data, control)

### Arguments

`feature_abd` | feature-by-sample matrix of abundances (proportions or counts).
`batch` | name of the batch variable. This variable in data should be a factor variable and will be converted to so with a warning if otherwise.
`covariates` | name(s) of covariates to adjust for in the batch correction model.
`data` | data frame of metadata, columns must include batch and covariates (if specified).
`control` | a named list of additional control parameters. See details.

### Details

`control` should be provided as a named list of the following components (can be a subset).

zero_inflation

  logical. Indicates whether or not a zero-inflated model should be run. Default to TRUE (zero-inflated model). If set to FALSE then the correction will be similar to `ComBat` as provided in the `sva` package.

pseudo_count

  numeric. Pseudo count to add feature_abd before the methods' log transformation. Default to `NULL`, in which case `adjust_batch` will set the pseudo count automatically to half of minimal non-zero values in `feature_abd`.

diagnostic_plot

  character. Name for the generated diagnostic figure file. Default to `"adjust_batch_diagnostic.pdf"`. Can be set to `NULL` in which case no output will be generated.

conv

  numeric. Convergence threshold for the method's iterative algorithm for shrinking batch effect parameters. Default to 1e-4.

maxit

  integer. Maximum number of iterations allowed for the method's iterative algorithm. Default to 1000.

verbose

  logical. Indicates whether or not verbose information will be printed.

### Value

a list, with the following components:

feature_abd_adj

  feature-by-sample matrix of batch-adjusted abundances, normalized to the same per-sample total abundance as feature_abd.

control

  list of additional control parameters used in the function call.

### Author(s)

Siyuan Ma, siyuanma@g.harvard.edu

### Examples

    data("CRC_abd", "CRC_meta")
    CRC_abd_adj <- adjust_batch(feature_abd = CRC_abd,
                                batch = "studyID",
                                covariates = "study_condition",
                                data = CRC_meta)$feature_abd_adj

[Package MMUPHin version 1.0.0 Index]