Pipelines for working with QTL results. Assumes QTLs were mapped using QTL-mapping-pipeline and both QTL and GWAS summary statistics have been placed into the Raj Lab GWAS/QTL Database.
Written by Jack Humphrey and Katia de Paiva Lopes Raj Lab 2020
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Scripts for wrangling GWAS summary stats (GWAS)
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Colocalisation with GWAS results (COLOC)
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Pairwise sharing between QTLs (qvalue_sharing, pisquared)
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Random-effects meta-analysis of multiple QTL datasets (METASOFT)
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Multivariate adaptive shrinkage for sharing of effect sizes between QTL datasets (MASHR)
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Building Transcriptome-wide Association Study models and applying them to GWAS (TWAS) - under construction
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Fine-mapping using the echolocatoR pipeline (Fine-mapping)