Genome-wide association studies (GWAS) have emerged as a powerful tool to 
uncover the genetic basis of human common diseases, which often show a complex, 
polygenic and multi-factorial aetiology. These studies have revealed that 70-90% 
of all single nucleotide polymorphisms (SNPs) associated with common complex 
diseases do not occur within genes (i.e. they are non-coding), making the 
discovery of disease-causative genetic variants and the elucidation of the 
underlying pathological mechanisms far from straightforward. Based on emerging 
evidences suggesting that disease-associated SNPs are frequently found within 
cell type-specific regulatory sequences, here we present GARLIC (GWAS-based 
Prediction Toolkit for Connecting Diseases and Cell Types), a user-friendly, 
multi-purpose software with an associated database and online viewer that, using 
global maps of cis-regulatory elements, can aetiologically connect human 
diseases with relevant cell types. Additionally, GARLIC can be used to retrieve 
potential disease-causative genetic variants overlapping regulatory sequences of 
interest. Overall, GARLIC can satisfy several important needs within the field 
of medical genetics, thus potentially assisting in the ultimate goal of 
uncovering the elusive and complex genetic basis of common human disorders.