Linking Genetic Risk to Disease-Relevant Cellular States via Metacell-Informed Modeling with ICePop

This dataset contains the processed data used in the analyses of the paper: “Linking Genetic Risk to Disease-Relevant Cellular States via Metacell-Informed Modeling with ICePop” (https://doi.org/10.64898/2026.04.01.715877).

Code and notebooks to reproduce the analyses are available at: https://github.com/krishnanlab/icepop_analysis

The ICePop Python package is available at: https://github.com/krishnanlab/icepop_public

This dataset includes the following components:

• simulation.tar.gz
  • Input data for causal and null simulation studies.
• magma.tar.gz
  • MAGMA-derived z-scores for all diseases/traits analyzed in this study.
  • Corresponding disease/trait metadata are provided in Supplementary Data 1.
• TM_FACS.tar.gz
  • Processed single-cell RNA-seq data from Tabula Muris (FACS).
  • Raw data were obtained from: https://doi.org/10.6084/m9.figshare.5829687.v7
• mouse_colon.tar.gz
  • Single-cell RNA-seq data of mouse colon enteric cells from Drokhlyansky et al. Cell 2020.
  • Raw data were obtained from the Single Cell Portal (SCP1038).
  • This archive also includes SFARI gene scores downloaded from https://gene.sfari.org/database/human-gene/