MutationTaster2021

Here we present an update to MutationTaster, our DNA variant effect prediction tool. The new version uses a different prediction model and attains higher accuracy than its predecessor, especially for rare benign variants. In addition, we have integrated many sources of data that only became available after the last release (such as gnomAD and ExAC pLI scores) and changed the splice site prediction model. To more easily assess the relevance of detected known disease mutations to the clinical phenotype of the patient, MutationTaster now provides information on the diseases they cause. Further changes represent a major overhaul of the interfaces to increase user-friendliness whilst many changes under the hood have been designed to accelerate the processing of uploaded VCF files. We also offer an API for the rapid automated query of smaller numbers of variants from within other software. MutationTaster2021 integrates our disease mutation search engine, MutationDistiller, to prioritise variants from VCF files using the patient's clinical phenotype. The novel version is available at https://www.genecascade.org/MutationTaster2021/. This website is free and open to all users and there is no login requirement.

The search for allelic variants that cause monogenic disorders or predispose to common, complex polygenic phenotypes

The search for the mutant genes for monogenic disorders has been a spectacular success. This was accomplished because of the mapping and sequencing of the human genome, the determination of the sequence variability, the collection of well-characterized families with mendelian disorders, the development of statistical methods for linkage analysis, and laboratory methods for mutation search. The challenge of the genetic medicine is now to decipher the nucleotide sequence variants that predispose to common complex, polygenic phenotypes. The methodology for this challenge is in development and constant evolution, it is anticipated that, in the next 10 to 20 years, susceptibility alleles for these common disorders will be identified.