ROSMAP meQTL Results for Oligodendrocytes with regionalpcs and averages
<p>This dataset contains methylation quantitative trait loci (meQTL) results for the following study:</p> <p><strong><em>"regionalpcs improve discovery of DNA methylation associations with complex traits"</em></strong></p> <p>Tiffany Eulalio*<sup>1</sup>, Min Woo Sun<sup>1</sup>, Olivier Gevaert<sup>1</sup>, Michael D. Greicius<sup>2</sup>, Thomas J. Montine<sup>3</sup>, Daniel Nachun*‡<sup>3</sup>, Stephen B. Montgomery*‡<sup>1,3</sup></p> <p>‡ These authors contributed equally as senior authors</p> <p>* Corresponding authors: Tiffany Eulalio (<a href="mailto:eulalio@alumn.stanford.edu">eulalio@alumn.stanford.edu</a>), Daniel Nachun (<a href="mailto:dnachun@stanford.edu">dnachun@stanford.edu</a>), Stephen B. Montgomery (<a href="mailto:smontgom@stanford.edu">smontgom@stanford.edu</a>)</p> <p> Author affiliations:</p> <p>1. Department of Biomedical Data Science, Stanford University, Stanford, CA</p> <p>2. Department of Neurology & Neurological Sciences, Stanford University, Stanford, CA</p> <p>3. Department of Pathology, Stanford University, Stanford, CA</p> <p> </p> <p><strong>Dataset description</strong>:</p> <p>This dataset contains QTL results generated from FastQTL, organized by region type (full gene, gene body, preTSS, and promoters) and summary types (averages and regional principal components).</p> <p><strong>Contents:</strong></p> <ul> <li><strong>Parquet tar files</strong>: These compressed archives contain output files in Parquet format from FastQTL, split by chromosome. <code>parquet1</code> includes chromosomes 1-10, and <code>parquet2</code> includes chromosomes 11-22.</li> <li><strong>cis_qtl_summary_stats.csv</strong>: Provides summary statistics for each phenotype-variant pair, including effect sizes, p-values, TSS distances, and additional details.</li> <li><strong>cis_qtl.signif_pairs.csv</strong>: Contains the significant QTL results identified by FastQTL.</li> <li><strong>cis_qtls.time_to_run.txt</strong>: Reports the running time for FastQTL analysis.</li> <li><strong>cis_qtls.cis_qtl.txt.gz</strong>: Contains comprehensive results for all cis QTLs.</li> </ul> <p>This dataset is intended to support replication and further exploration of QTL associations across different genomic regions and summary methods.</p>
ShareScore
36/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 4
- Harmonization
- 4
- Access
- 20
- Reuse readiness
- 8
- Engagement
- 0