From Geuvadis MediaWiki
Aims of the analyses
- Catalogue genetic variants that associate to different transcriptome phenotypes (gene expression levels, splicing ratios, etc)
- Understand how genetic control of various parts of transcriptome works together: e.g are eQTLs and sQTLs often overlapping, do they interact with each other, do variants that affect miRNA-target interaction also end up affecting the target gene expression…
- Do SNPs, indels and SVs have different effects?
- Describe population sharing of tQTLs
- Understand the cellular mechanisms that drive the genetic associations by functional annotation of the variants
- Basic methodology
- Input data processing and filtering: genotypes, transcriptome phenotypes, normalization
- Statistical approaches for eQTL mapping
- expression quantitative trait locus results
- Splicing QTL discovery using transcript quantifications
- Splicing QTL discovery: exon inclusion statistics
Pending: other transcriptome phenotypes, SNP/indel/SV effects, functional annotation, population sharing...