Prioritize candidate genes based on DNM burden

Step1: Input DNMs detected by your data

You can paste variants list in the following textbox

Input variant list in tab-delimited or space-delimited format which contains five fields: Chromosome, Start, End, Reference Allelel, Alternative Allele. The genomic coordinate is based on GRCH37/hg19. It is noted that the prefix of chromosome "chr" should not be omitted.
Click to paste an example

Or you can upload your input file

Input file
Download example file
The format of input file is the same as depicted above.

Step2: Set your parameters

Prioritize candidate genes by effectively combining the number of LoF and damaging missense mutations. P values are adjusted by FDR approach.
Maximun variant frequency in human genetic variation databases.
Average DNMR for the four background DNMRs
Number of trios for DNM burden analysis.
For each missense mutation, mirDNMR provides 14 methods to predict the effect, which mainly based on evolutionary conservation and function disruption. Only the selected methods will be used for damaging prediction.
Only the missense mutations being predicted as damaging by methods over the threshold will be identified as damaging.
A parameter for TADA which determines how much weight is assigned for LoF variants. γ = 1 + (λ - 1) / π, where λ denotes the burden of LoF variants and π denotes the fraction of risk genes.
A parameter for TADA which determines how much weight is assigned for missense variants. γ = 1 + (λ - 1) / π, where λ denotes the burden of missense variants and π denotes the fraction of risk genes.
Only the genes with q value less than the cutoff will be exhibited in the result.