DAPPLE Version 2.0

We have recently updated DAPPLE to include new features:

⋅Get results much faster
⋅Hg19 HapMap and 1KG SNPs can now be input
⋅Input list length can be up to 2000
⋅Combine input types (SNP, gene, region)
⋅Plot a specified sub-network

What is DAPPLE?


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) :

Genome Assembly:
Number of permutations:
Common Interactor binding degree cutoff:
Define gene regulatory region:
For SNP and region input only. Gene boundary definitions can include flanking regulatory DNA.
kb upstream of Tx Start
kb downstream of Tx End
Nearest Gene:
For SNP inputs only. Select the closest gene, rather than all genes in the wingspan.
Use Nearest Gene
Inputs:
Inputs can be genes, SNPs, regions or a combination. One line per input. Limit: 2000.
See example of Combination input
See example of SNP input
See example of Region input
See example of Gene-Region input
See example of Gene input

Genes to Specify:
Only for SNP and region input. Input any genes that you would like to fix as the causal gene for an input locus, such that all other genes in that region will not be included. Use gene symbol ID, 1 gene per line.
See example of genes to specify

Plot:
Return a picture of your network.
To add a picture of your network involving only a subset of genes, specify here using gene IDs.
PlotColor by DAPPLE p-valueSimplifyZoom to genes? (comma separated)
Your email address (required):
Description (required):
Warning: All non-alphanumeric characters and spaces will be removed

If you haven't yet, click here to receive email notification of any major changes in DAPPLE

QUESTIONS? Please refer to the FAQ page before emailing dapple@broadinstitute.org with questions.

Reference:

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

Acknowledgement:

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.

Downloads

You do not need to download anything to run DAPPLE. To download the raw InWeb data, click here. To convert InWeb IDs to Gene Symbol, click here.