Curated RNA-seq Expression Dataset and Reproducible Python Workflow Derived from GSE144153 for FAIR Transcriptomic Analysis of ZNF587-Silenced Human H1 Cells

This repository contains a curated and reproducible derived RNA-seq transcriptomic dataset generated from publicly available sequencing count data associated with ZNF587-silenced human H1 cells from GEO accession GSE144153. The repository distributes exclusively derived computational resources and reproducible analytical workflows generated from publicly accessible transcriptomic count matrices. Original raw sequencing repositories are not redistributed. The repository includes: raw count matrices CPM-normalized expression matrices filtered transcriptomic datasets exploratory fold-change summaries PCA coordinates transcriptomic clustering resources heatmaps and hierarchical clustering visualizations workflow figures validation scripts reproducible Python workflows Colab/Jupyter reproducibility notebooks metadata mappings and FAIR-oriented documentation The workflow supports reproducible transcriptomic preprocessing, exploratory RNA-seq analysis, dimensionality reduction studies, clustering benchmarking, computational genomics education, and FAIR bioinformatics workflow development. The repository was generated using reproducible Python-based workflows and includes modular scripts for automated download, preprocessing, normalization, visualization, validation, and packaging. Original source dataset: Turelli et al., Science Advances (2020)DOI: 10.1126/sciadv.aba3200 GitHub repository:https://github.com/jrhechavarriah/GSE144153_FAIR_RNAseq License: CC BY 4.0