In compbiomed/BatchQC: Batch Effects Quality Control Software

Example 1: Protein Data

This data set is from protein expression data captured for 39 proteins. It has two batches and two conditions corresponding to case and control.

library(BatchQC)
data(protein_data)
data(protein_sample_info)
se_object <- BatchQC::summarized_experiment(protein_data, protein_sample_info)

Example 2: Signature Data

This data set is from signature data captured when activating different growth pathway genes in human mammary epithelial cells (GEO accession: GSE73628). This data consists of three batches and ten different conditions corresponding to control and nine different pathways

data(signature_data)
data(batch_indicator)
se_object <- BatchQC::summarized_experiment(signature_data, batch_indicator)

Example 3: Bladderbatch Data

This data set is from bladder cancer data. This dataset has 57 bladder samples with 5 batches and 3 covariate levels (cancer, biopsy, control). Batch 1 contains only cancer, 2 has cancer and controls, 3 has only controls, 4 contains only biopsy, and 5 contains cancer and biopsy. This data set is from the bladderbatch package which must be installed to use this data example set (Leek JT (2023). bladderbatch: Bladder gene expression data illustrating batch effects. R package version 1.38.0).

if (!requireNamespace("bladderbatch", quietly = TRUE))
    BiocManager::install("bladderbatch")
se_object <- BatchQC::bladder_data_upload()

Session info {.unnumbered}

sessionInfo()

compbiomed/BatchQC documentation built on Nov. 16, 2024, 5:47 a.m.