bulk-rna-seq-batch-correction-with-combat

The 'bulk-rna-seq-batch-correction-with-combat' skill addresses the issue of batch effects in bulk RNA-seq or microarray datasets. When combining multiple expression matrices from different batches, it is common for the data to contain systematic variations unrelated to biological differences. This skill uses the pyComBat wrapper from omicverse to perform batch correction, aligning datasets for downstream analysis by removing these unwanted batch effects. By correcting these inconsistencies, it enables users to derive more reliable conclusions from merged datasets across different cohorts.

Main capabilities include the ability to load expression matrices from different batches, concatenate them on shared genes, and then apply ComBat batch correction. The skill generates corrected matrices while retaining the original data for comparison. Users can benchmark the effectiveness of the correction using visualizations such as PCA plots and boxplots before and after the correction. It also provides options to save both corrected and raw data in CSV format and as AnnData objects, allowing easy future access. The process is designed to be flexible, ensuring compatibility with various input formats and datasets.

This skill is particularly useful for bioinformaticians, data analysts, and researchers working with RNA sequencing data. It serves as an essential tool for harmonizing datasets that span multiple experimental conditions or cohorts, such as those found in large-scale genomic studies. Its ease of use and integration with other omicverse functionalities make it suitable for both new users and experienced researchers aiming to improve data quality before performing downstream analyses like differential expression analysis or pathway enrichment analysis.