De novo alignments of mouse RNA-seq data to assess the VHL loss reported by Rathmell and colleagues (PMID 38618956)

The contents of this dataset were created de novo starting from RNA-seq data downloaded from Gene Expression Omnibus (GEO), with a pipeline specifically written to generate results starting with sequencing reads that were made available by the authors of a scientific article, in order to compare the results with claims in the article and the evidence for those claims. These results are otherwise available partially at best, and generally not from the authors, even though one type of result is the fundamental purpose of using RNA-seq (gene counts), and the article reported results derived from these standard output (differential expression).

In order to facilitate this comparison, this pipeline first and foremost retains a common but optional primary type of output, namely genomic alignments, so that these can be examined and shared. The comparison with the claims in the article would be indirect with gene counts, while the actual read sequences can be examined or extracted from the alignments. These files are normally in a format called BAM, and the files in this dataset are compressed versions of these; instructions and scripts are nearly ready, but anyone in bioinformatics would be able to use these files.

The scripts and metadata used to generate these files are also forthcoming but will follow this previous example: https://zenodo.org/records/17055095

The code that was used to generate those scripts is in this GitHub repo; the readme provides more context: https://github.com/a-dna-n/RNAseq_end_to_end/

The sequencing data was initially reported in this article:

VHL loss reprograms the immune landscape to promote an inflammatory myeloid microenvironment in renal tumorigenesis

J Clin Invest. 2024 Apr 15;134(8):e173934. doi: 10.1172/JCI173934 

Melissa M Wolf, Matthew Z Madden, Emily N Arner, Jackie E Bader, Xiang Ye, Logan Vlach, Megan L Tigue, Madelyn D Landis, Patrick B Jonker, Zaid Hatem, KayLee K Steiner, Dakim K Gaines, Bradley I Reinfeld, Emma S Hathaway, Fuxue Xin, M Noor Tantawy, Scott M Haake, Eric Jonasch, Alexander Muir, Vivian L Weiss, Kathryn E Beckermann, W Kimryn Rathmell, Jeffrey C Rathmell 

https://pubmed.ncbi.nlm.nih.gov/38618956/

The reads were obtained using the link in the article:  https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE239889