Updates

Release 2.0 (2023-6-23)

This release includes the following features described in detail in the [documentation]:

• Curated 10,342 GWASs and generated fine-mapping results;
• Added abf as an LD-free fine-mapping tool;
• Added SuSiE as an LD-based fine-mapping tool;
• Added results of PolyFun+FINEMAP and PolyFun+SuSiE to demonstrate annotation-informed fine-mapping;
• Used large reference panels to estimate LD, e.g., UKB, TOPMED, and SG10K;
• Conducted conditional analysis to identify independent signals;
• GWASs from UKB cohort were marked as UKB population;
• Search by variant: the PheWas plot shows the PP of the queried variant in each GWAS;
• LocusZoom-like plot: users can check the multiple independent signals by selecting lead SNPs;

Release 1.3 (2022-3-15)

• Added 1381 normalized data from GWAS summary statistics of the GWAS Catalog.

Release 1.2 (2021-9-24)

• Functional annotation has been replaced with our recently developed database vannoPortal (http://mulinlab.org/vportal), which provides more comprehensive variant annotations at different levels.

Release 1.1 (2019-09-29)

• Potential pleiotropy estimation: variant-level potential pleiotropy was calculated by gwas-pw for GWAS pairs. Traits were marked with “*” when associated variant has potential pleiotropy in phenome-wide-like plot.
• Query variant: variant can be searched in LD block viewer and jump to its causal block
• Annotation download: download the function annotation of selected variant
• SVG download: download the QQ plot or locus-zoom plot in SVG format
• Compare variants: select at most six credible variants and compare functional prediction scores from 14 base-wise tools (e.g., CADD or FATHMM-MKL) and the number of overlapped epigenomic features (e.g., open chromatin or transcription factor binding) across selected variants in popup bar plots.
• Fine-mapping combined score: combine the posterior probabilities calculated by the three tools by introducing the rank product value.
• Fine-mapping pipeline: our fine-mapping scripts were available on GitHub (https://github.com/mulinlab/CAUSALdb-finemapping-pip) so researchers who are familiar with command line can deploy the fine-mapping pipeline on their devices and reproduce CAUSALdb fine-mapping results easily, or even fine-map own GWAS data.

Release 1.0 (2019-06-27)

This release includes the following features described in details in the documentation:

• Curated GWAS: normalized meta information of 3,052 fine-mappable GWAS and their full summary statistics in a unified format.
• Search by variant: investigate the causality of interested variant by entering rsID
• Search by position and alleles: if the rsID of query variant was unknown, entering the combination of position and alleles (e.g. chr1-109817590-G-T)
• 'Only show P value' mode: switch to the phenomenon-wide scatter plot of significant signals of query variant
• Search by trait: retrieve all the studies of interested trait and statistics of their causal blocks
• Sort query results: sort the query results by date of publication, sample size, number of variants and number of causal blocks
• Filter query results: filter the query results by the main MeSH terms
• Search by gene: get the results of LD block which the query gene locates in
• Search by locus: search genomic region by chromosome, start and end of your interval
• Switch fine mapping tool: retrieve fine-mapping results from three different tools
• Clickable Manhattan plot: each highlighted strip represents a causal block and is clickable to show the details of causal block on the plot below
• LocusZoom like plot: we implemented a similar look as the LocusZoom plot for every causal block with additional signatures for credible set
• Make LD reference: change the proxy variant by clicking 'make LD reference' on the hover tip
• Annotation panel: retrieve the functional annotation by clicking the variant in LocusZoom like plot