Detect batch effect

Use ANOVA to detect if batch effect is present in the data. If group is provided, it will be used as a covariate in the ANOVA model.

Usage

detect_batch_effect(x, batch = "batch", group = NULL)

Arguments

x

A glyexp::GlycomicSE(), glyexp::GlycoproteomicSE(), or SummarizedExperiment::SummarizedExperiment() object.

batch

Either a factor/character vector specifying batch assignments for each sample, or a string specifying the column name in sample_info. Defaults to "batch".

group

Either a factor/character vector specifying group assignments for each sample, or a string specifying the column name in sample_info. If provided, it will be used as a covariate in the ANOVA model. This is useful when you have an unbalanced design. Default to NULL.

Value

A double vector of p-values for each variable, with the same length as nrow(x).

Examples

library(SummarizedExperiment)

# With a SummarizedExperiment and column names
exp <- glyexp::real_experiment
batch <- rep(c("A", "B"), length.out = ncol(exp))
group <- rep(c("Ctrl", "Ctrl", "Treat", "Treat"), length.out = ncol(exp))
colData(exp)$batch <- batch
colData(exp)$group <- group
p_values <- detect_batch_effect(exp, batch = "batch", group = "group")
#> ℹ Detecting batch effects using ANOVA for 4262 variables...
#> Warning: ANOVA F-tests on an essentially perfect fit are unreliable
#> Warning: ANOVA F-tests on an essentially perfect fit are unreliable
#> Warning: ANOVA F-tests on an essentially perfect fit are unreliable
#> Warning: ANOVA F-tests on an essentially perfect fit are unreliable
#> Warning: ANOVA F-tests on an essentially perfect fit are unreliable
#> Warning: ANOVA F-tests on an essentially perfect fit are unreliable
#> Warning: ANOVA F-tests on an essentially perfect fit are unreliable
#> Warning: ANOVA F-tests on an essentially perfect fit are unreliable
#> Warning: ANOVA F-tests on an essentially perfect fit are unreliable
#> Warning: ANOVA F-tests on an essentially perfect fit are unreliable
#> Warning: ANOVA F-tests on an essentially perfect fit are unreliable
#> Warning: ANOVA F-tests on an essentially perfect fit are unreliable
#> Warning: ANOVA F-tests on an essentially perfect fit are unreliable
#> Warning: ANOVA F-tests on an essentially perfect fit are unreliable
#> Warning: ANOVA F-tests on an essentially perfect fit are unreliable
#> Warning: ANOVA F-tests on an essentially perfect fit are unreliable
#> Warning: ANOVA F-tests on an essentially perfect fit are unreliable
#> Warning: ANOVA F-tests on an essentially perfect fit are unreliable
#> Warning: ANOVA F-tests on an essentially perfect fit are unreliable
#> Warning: ANOVA F-tests on an essentially perfect fit are unreliable
#> Warning: ANOVA F-tests on an essentially perfect fit are unreliable
#> Warning: ANOVA F-tests on an essentially perfect fit are unreliable
#> Warning: ANOVA F-tests on an essentially perfect fit are unreliable
#> Warning: ANOVA F-tests on an essentially perfect fit are unreliable
#> Warning: ANOVA F-tests on an essentially perfect fit are unreliable
#> Warning: ANOVA F-tests on an essentially perfect fit are unreliable
#> Warning: ANOVA F-tests on an essentially perfect fit are unreliable
#> Warning: ANOVA F-tests on an essentially perfect fit are unreliable
#> ✔ Batch effect detection completed. 65 out of 4262 variables show significant batch effects (p < 0.05).