De novo mutations (DNMs) arise spontaneously in germline cells (de novo germline mutation) or shortly after fertilization (post-zygotic mutation). They represent the most extreme form of rare genetic mutations that have been proved as important contributors to sporadic genetic diseases, such as autism spectrum disorders, intellectual disability, epileptic encephalopathy, schizophrenia, congenital heart disease, type 1 diabetes, and hearing loss. However, not all DNMs are the causes of sporadic diseases. It is indicated that averagely 74 de novo SNVs and 3 de novo INDELs arise spontaneously in an individual's genome and only a very few of them are considered to be pathogenic. Therefore, it is a great challenge to accurately assess the causality of DNMs as well as identify disease-causative genes from the considerable number of DNMs occurred in proband. A common method to this problem is to identify genes that harbor significantly DNMs than expected by chance. However, this method requires expected background de novo mutation rates (DNMRs) of each individual gene or large normal samples as controls. If accurate background DNMRs for each gene were provided, we could identify candidate genes much easier with strong statistical support and not require normal samples as controls.

      Here we constructed a gene-centered database named mirDNMR for collection of background DNMRs and variant frequencies in human genetic variation databases including ExAC (r0.3.1), ESP6500 (ESP6500SI-V2), UK10K, the 1000 Genomes (Phase 3) and dbSNP (Build 147). Users can freely browse and search resources in this database. Meanwhile, mirDNMR provides two convenient tools for users to prioritize and filter candidate genes.

Data collection:

Source of background DNMRs:

Currently available human genetic variation databases:

The main functionalities of mirDNMR:

The mirDNMR process:



      This database is free and open to all users and there is no login requirement !

Cite us:

      Jiang, Y., Li, Z., Liu, Z., Chen, D., Wu, W., Du, Y., Ji, L., Jin, Z.B., Li, W. and Wu, J. (2017) mirDNMR: a gene-centered database of background de novo mutation rates in human. Nucleic acids research, 45, D796-D803.