ROSMAP meQTL Results for Bulk cells 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*¹, Min Woo Sun¹, Olivier Gevaert¹, Michael D. Greicius², Thomas J. Montine³, Daniel Nachun*&Dagger;³, Stephen B. Montgomery*&Dagger;^1,3</p> <p>&Dagger; 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>&nbsp;Author affiliations:</p> <p>1.&nbsp;&nbsp;&nbsp;&nbsp; Department of Biomedical Data Science, Stanford University, Stanford, CA</p> <p>2.&nbsp;&nbsp;&nbsp;&nbsp; Department of Neurology &amp; Neurological Sciences, Stanford University, Stanford, CA</p> <p>3.&nbsp;&nbsp;&nbsp;&nbsp; Department of Pathology, Stanford University, Stanford, CA</p> <p>&nbsp;</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>