R Code for Bioinformatics Analysis of Acute Pancreatitis-Associated Lung Injury

Lingfeng Chen published R code for bioinformatics analysis on 2026-05-22. The code analyzes three Gene Expression Omnibus (GEO) datasets to identify key genes and pathways in acute pancreatitis-associated acute lung injury (AP-ALI). The 2.5 KB text file contains scripts for differential expression analysis, pathway enrichment, and protein-protein interaction network construction.

Use Cases

• Identify differentially expressed genes (DEGs) based on analysis of mouse and human datasets described in the study
• Perform Gene Ontology (GO) and KEGG pathway enrichment analysis based on the common DEGs identified
• Construct protein-protein interaction (PPI) networks and screen for hub genes like IL-1β and CXCL2 mentioned in the results
• Conduct cross-species comparison of inflammatory pathways between mouse lung tissue and human peripheral blood data

Strengths

• Analysis is based on three publicly available GEO datasets (GSE244335, GSE216943, GSE194331) with specific gene counts provided
• Includes cross-species validation, comparing mouse lung tissue findings with human peripheral blood data
• Released under a permissive CC-BY-4.0 license, facilitating reuse and modification

Limitations

• Row count and column-level documentation for the underlying data are unknown; data quality requires manual inspection after download
• The dataset is a 2.5 KB text file of R code, not the primary expression data itself, which must be sourced separately

Provenance

Source

Gene Expression Omnibus (GEO) database

Collection Method

Bioinformatics analysis of publicly deposited microarray or RNA-seq datasets

Time Range

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Freshness

Last updated 2026-05-22 17:41:25; freshness should be verified.

Geography

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