Published April 14, 2023 | Version v1
Dataset Open

Data to reproduce analysis in "Systematic analysis of transcriptional and epigenetic effects of genetic variation in Kupffer cells enables discrimination of cell intrinsic and environment-dependent mechanisms"

  • 1. University of California, San Diego
  • 2. Cincinnati Children's Hospital Medical Center

Description

Here you can find the datasets necessary to reproduce all analyses described in the Glass lab paper by Bennett et al. The python and R code for reproducing analysis and figures can be found on our linked github repository.

Briefly, this paper explores the effect of natural genetic variation in vivo, using Kupffer cells as a model cell type. We collect and analyze transcriptional and epigenetic data (ATAC-seq, H3K27Ac ChIP-seq) to identify putative trans regulators driving differential gene expression across inbred strains of mice. Additionally, we provide evidence that trans effects control a majority of strain differential genes at homeostasis while cis effects dominate the transcriptional response to an external signal (lipopolysaccharide).

References:

Hunter Bennett, Ty D. Troutman, Enchen Zhou, Nathanael J. Spann, Verena M. Link, Jason S. Seidman, Christian K. Nickl, Yohei Abe, Mashito Sakai, Martina P. Pasillas, Justin M. Marlman, Carlos Guzman, Mojgan Hosseini, Bernd Schnabl, Christopher K. Glass bioRxiv 2022.09.22.509046; doi: https://doi.org/10.1101/2022.09.22.509046

 

Files

all_liver_cells_rna_tpm.txt

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Additional details

Related works

Is supplement to
Preprint: 10.1101/2022.09.22.509046 (DOI)