batch_evaluation.microarray: Assessment of batch-correction methods

In madhulika-EBI/Batchevaluation: Toolkit for batch correction

Assessment of batch-correction methods

Description

The function performs various evaluations on batch-corrected microarray data and output performance list of each individual method. Since there are no. of ways batch-correction can be evaluated and each method has its own limitation, we have used a cocktail of methods to perform analysis.

Usage

batch_evaluation.microarray(result, batch.factors, experiment, N1, N2, filter)

Arguments

result	A list of wrapped batch-corrected experiments obtained from the last step ('batch_correction').
batch.factors	A list of factors to perform PVCA analysis. Along with the batch factor, one biological factor which can be used to assess over-fitting should be provided.
experiment	A merged experiment without batch correction obtained from step ('merge_experiments').
N1	is the number of randomly picked samples for the BatchEntropy function.
N2	is the number of nearest neighbors of a sample (from all batches) to check (for BatchEntropy function).
filter	A string. Should be one of following string- 'symbol', 'ensembl_gene_id', or 'entrezgene_id' depending on gene label for the given dataset.

Value

A list of the evaluation methods on the batch-corrected microarray experiment.

Examples

 batch_evaluation(result, batch.factors=c("batch","sex"),experiments,'ensembl_gene_id')

madhulika-EBI/Batchevaluation documentation built on Jan. 27, 2023, 5:27 p.m.