isNotContaminant: Identify non-contaminant sequences.

In benjjneb/decontam: Identify Contaminants in Marker-gene and Metagenomics Sequencing Data

Description

The prevalence of each sequence (or OTU) in the input feature table across samples and negative controls is used to identify non-contaminant sequences. Note that the null hypothesis here is that sequences **are** contaminants. This function is intended for use on low-biomass samples in which a large proportion of the sequences are likely to be contaminants.

Usage

isNotContaminant(seqtab, ...)

## S4 method for signature 'ANY'
isNotContaminant(
  seqtab,
  neg = NULL,
  method = "prevalence",
  threshold = 0.5,
  normalize = TRUE,
  detailed = FALSE
)

Arguments

seqtab	(Required). Integer matrix. A feature table recording the observed abundances of each sequence (or OTU) in each sample. Rows should correspond to samples, and columns to sequences (or OTUs).
...	Not used currently
neg	(Required). logical The negative control samples. Extraction controls give the best results.
method	(Optional). Default "prevalence". The method used to test for contaminants. Currently the only method supported is prevalence. prevalence: Contaminants are identified by increased prevalence in negative controls.
threshold	(Optional). Default 0.5. The probability threshold below which (strictly less than) the null-hypothesis (a contaminant) should be rejected in favor of the alternate hypothesis (not a contaminant).
normalize	(Optional). Default TRUE. If TRUE, the input seqtab is normalized so that each row sums to 1 (converted to frequency). If FALSE, no normalization is performed (the data should already be frequencies or counts from equal-depth samples).
detailed	(Optional). Default FALSE. If TRUE, the return value is a data.frame containing diagnostic information on the non-contaminant decision. If FALSE, the return value is a logical vector containing the non-contaminant decisions.

Value

If detailed=FALSE a logical vector is returned, with TRUE indicating non-contaminants. If detailed=TRUE a data.frame is returned instead.

Examples

st <- readRDS(system.file("extdata", "st.rds", package="decontam"))
samdf <- readRDS(system.file("extdata", "samdf.rds", package="decontam"))
isNotContaminant(st, samdf$quant_reading, threshold=0.05)

benjjneb/decontam documentation built on July 3, 2021, 5:45 a.m.