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7 results for “cis eQTL”
MTClass: Identification and annotation of multi-phenotype cis-eQTLs using machine learning
<p>This dataset contains the aggregated results from three iterations of MTClass. Brief descriptions of the file names are below:</p> <ul> <li><strong>multi-tissue.zip</strong>: Multi-tissue study containing the 9-tissue, 13 brain tissue, and 48-tissue results from MTClass, MultiPhen, and MANOVA</li> <li><strong>multi-exon.zip</strong>: Multi-exon study containing the multi-exon results from the 13 individual brain tissues (MTClass, MultiPhen, and MANOVA for each tissue)</li> <li><strong>2D_exon_tissue.zip</strong>: Multi-tissue/multi-exon combined eQTL study, done in 9 tissues using multi-layer perceptron. MTClass was only run once on this dataset due to the relatively higher computational burden.</li> <li><strong>PsychENCODE_isoQTL.zip</strong>: Multi-isoform eQTL study, done in human prefrontal cortex using PsychENCODE data.</li> <li><strong>OneK1K_scRNAseq.zip</strong>: Multi-cell-type eQTL study, done using scRNA-seq data from the OneK1K cohort.</li> </ul>
Summary statistics of cell-type specific cis-eQTLs in eight brain cell-types
<p>This dataset contains eQTL summary statistics for all SNPs-gene pairs in 8 major brain cell types (within 1MB window surrounding the TSS of each expressed gene). For each cell type, there is one file per chromosome.</p> <p>Column description:</p> <p>1. Gene_id</p> <p>2. SNP_id</p> <p>3. Distance to TSS</p> <p>4. Nominal p-value</p> <p>5. Beta</p> <p>In addition, a file contains the SNP positions (snp_pos.txt) and tested allele.</p> <p>Update February 2023: The summary statistics from our 'tissue-like' analysis were added (pb[1-22].gz). These file contain eQTL summary statistics after aggregating all reads from all nuclei for each individual (instead of per cell type).</p>
aFCn for independent cis-eQTLs across 49 tissues in the GTEx v8 release
<p>The aFC-n model is the multi-variant generalization of the aFC approach (<a href="https://github.com/secastel/aFC">https://github.com/secastel/aFC</a>), to estimate the <i>cis</i>-regulatory effect size in genes associated with multiple conditionally independent eQTLs. Notably, aFC-n is the first method that allows for predicting genetically regulated gene expression in a haplotype-specific fashion, paving the way for a future class of genome association studies that can systematically incorporate allele dosage effects.</p><p>This dataset is generated using aFC-n software package (<a href="https://doi.org/10.5281/zenodo.8412460">10.5281/zenodo.8412460</a>) to calculate effect sizes for ~half a million independent <i>cis</i>-eQTLs across 49 tissues in the GTEx v8 release as described in the <a href="https://www.biorxiv.org/content/10.1101/2022.01.28.478116v1">manuscript</a>.</p><p>GTEx_v8_aFCn contains:</p><ul><li>gene_id : Ensembl gene ID</li><li>variant_id : eQTL ID associated to the gene</li><li>log2_aFC : The log2 of eQTL effect sizes measured as allelic Fold Change (aFC).</li><li>log2_aFC_min_95_interv : Lower bound 95% confidence interval</li><li>log2_aFC_plus_95_interv: Upper bound 95% confidence interval</li></ul><p>GTEx_v8<i>_</i>aFCn<i>_</i>combined contains:</p><ul><li>gene_id : Ensembl gene ID</li><li>variant_id : eQTL ID associated to the gene</li><li>rest of the columns : The log2 of eQTL effect sizes measured as allelic Fold Change (aFC) in the tissue specified by the column label capped at ±log2(100) <ul><li>nan = The variant is not an eQTL for the tissue / the effect size is not calculated for variants on chrX</li></ul></li></ul><p> </p>
Cell-type-specific cis-eQTLs data in SMR format from https://doi.org/10.1038/s41593-022-01128-z
<p>Cell-type-specific cis-eQTLs data in SMR format from https://doi.org/10.1038/s41593-022-01128-z</p> <p>The hg38 version of the coordinates is used</p>
Data from: Mediation analysis demonstrates that trans-eQTLs are often explained by cis-mediation: a genome-wide analysis among 1,800 South Asians
A large fraction of human genes are regulated by genetic variation near the transcribed sequence (cis-eQTL, expression quantitative trait locus), and many cis-eQTLs have implications for human disease. Less is known regarding the effects of genetic variation on expression of distant genes (trans-eQTLs) and their biological mechanisms. In this work, we use genome-wide data on SNPs and array-based expression measures from mononuclear cells obtained from a population-based cohort of 1,799 Bangladeshi individuals to characterize cis- and trans-eQTLs and determine if observed trans-eQTL associations are mediated by expression of transcripts in cis with the SNPs showing trans-association, using Sobel tests of mediation. We observed 434 independent trans-eQTL associations at a false-discovery rate of 0.05, and 189 of these trans-eQTLs were also cis-eQTLs (enrichment P<0.0001). Among these 189 trans-eQTL associations, 39 were significantly attenuated after adjusting for a cis-mediator based on Sobel P<10-5. We attempted to replicate 21 of these mediation signals in two European cohorts, and while only 7 trans-eQTL associations were present in one or both cohorts, 6 showed evidence of cis-mediation. Analyses of simulated data show that complete mediation will be observed as partial mediation in the presence of mediator measurement error or imperfect LD between measured and causal variants. Our data demonstrates that trans-associations can become significantly stronger or switch directions after adjusting for a potential mediator. Using simulated data, we demonstrate that this phenomenon is expected in the presence of strong cis-trans confounding and when the measured cis-transcript is correlated with the true (unmeasured) mediator. In conclusion, by applying mediation analysis to eQTL data, we show that a substantial fraction of observed trans-eQTL associations can be explained by cis-mediation. Future studies should focus on understanding the mechanisms underlying widespread cis-mediation and their relevance to disease biology, as well as using mediation analysis to improve eQTL discovery.
Data from: Mediation analysis demonstrates that trans-eQTLs are often explained by cis-mediation: a genome-wide analysis among 1,800 South Asians
Open the record for dataset details and reuse information.
Lead Modulates trans- and cis-eQTLs in Drosophila melanogaster Heads
GEO Series GSE83141. Drosophila melanogaster. 158 samples. Type: Expression profiling by high throughput sequencing.
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