What is DAPPLE?
** We are still working on changes to improve the speed and performance of DAPPLE jobs. Thank you for your patience and please contact us if you have any concerns or suggestions. **
DAPPLE stands for Disease Association Protein-Protein Link Evaluator. DAPPLE looks for significant physical connectivity among proteins encoded for by genes in loci associated to disease according to protein-protein interactions reported in the literature. The hypothesis behind DAPPLE is that causal genetic variation affects a limited set of underlying mechanisms that are detectable by protein-protein interactions. Please refer to the DAPPLE publication for full details.
What kind of information does DAPPLE need?
DAPPLE takes as input a list of seed SNPs or genomic regions that are then converted into genes based on overlap. Alternatively, DAPPLE can also take genes of interest if the user would like to explicitly specify seed genes (either as gene-regions or just genes). Please follow the instructions below and on the FAQ page to ensure proper input format. Please note that DAPPLE is currently built for the hg18 build of the human genome; hg19 will be incorporated shortly. DAPPLE is a work in progress - refer to the Updates Page for a list of bug fixes and updates.
What does DAPPLE do with the input?
DAPPLE will build direct and indirect interaction networks from proteins encoded for by seed genes. It will then assess the statistical significance of a number of network connectivity parameters as well as of the connectivity of individual proteins to other seed proteins using a within-degree node-label permutation method. The individual protein scores are then used to propose candidate genes in large loci, and the user can decide whether to iterate until it can no longer propose any more new genes. It will then email the user a number of output files including figures, data summaries and resultant significance scores.
Test Run: Depending on the number of inputs and permutations, DAPPLE can take a little while to run. We suggest that you choose the option "Test Run" in the permutations pull-down to see a fast example result. Please note that at least 1000 permutations are needed to accurately estimate p-values.
Please fill out the following (click here for an explanation) :
QUESTIONS? Please refer to the FAQ page before emailing email@example.com with questions.
Rossin EJ, Lage K, Raychaudhuri S, Xavier RJ, Tartar D, IIBDGC, Cotsapas C, Daly MJ. 2011 Proteins Encoded in Genomic Regions Associated with Immune-Mediated Disease Physically Interact and Suggest Underlying Biology. PLoS Genetics 7(1): e1001273
DAPPLE was developed by Liz Rossin in the lab of Mark J Daly. We would like to offer enourmous thanks to Brett Thomas who took the lead in launching the website, Soumya Raychaudhuri who developed the published tool GRAIL off of which this site is modeled, The Broad Institute IT Team and Stephan Ripke for assistance in creating a web interface.