This dataset contains DESeq2-normalized RNA-seq expression matrices generated from human colon tissues collected from patients with Hirschsprung’s disease and matched controls. Ganglionic and aganglionic regions were dissected, RNA was extracted, sequenced, and processed to obtain normalized gene-level expression counts. The data were generated to investigate transcriptomic alterations in HSCR. Files and variables HSCR_A_RNAseq_DESeq2_normalized_counts.csv Description: Normalized RNA-seq expression counts for aganglionic colon tissue samples, including HSCR patients and matched controls. Variables: * Ensembl_ID: gene identifier * C12, C25, …, H_A_61: individual sample columns, each representing a tissue sample; values are DESeq2-normalized counts HSCR_G_RNAseq_DESeq2_normalized_counts.csv Description: Normalized RNA-seq expression counts for ganglionic colon tissue samples, including HSCR patients and matched controls. Variables: * Ensembl_ID: gene identifier * C12, C25, …, H_G_61: individual sample columns, each representing a tissue sample; values are DESeq2-normalized counts HSCR_RNAseq_GEO_metadatas.xlsx Description: Sample-level metadata including sample IDs, tissue type (ganglionic or aganglionic), experimental condition (HSCR or control), and processing notes. Variables: * Sample_ID: unique identifier for each sample * Tissue: ganglionic or aganglionic * Condition: HSCR or control * Other columns: additional experimental metadata provided in the file Code/software RNA-seq reads were processed using standard bioinformatics pipelines. Gene-level counts were normalized using DESeq2. No custom code is required to use the count matrices. Analyses can be performed with common transcriptomic tools in R, Python, or other statistical software. Access information Other publicly accessible locations of the data: * Data was derived from the following sources: * Currently, this dataset is available under embargo and will be publicly released through Dryad. The dataset was generated from human colon tissue samples collected under institutional ethics approval with informed consent. All samples are fully de-identified and contain no personally identifiable information. The dataset complements the manuscript: “Extracellular Matrix Remodeling and RET Pathways Define the Molecular Landscape of Hirschsprung’s Disease” (submitted to JCI). No other publicly accessible sources were used to generate this data.