Welcome to DeMAG web server!
We present DeMAG (Deciphering Mutations in Actionable Genes) a supervised and specialized VEP (Variant Effect Predictor) to interpret any missense mutations in 59 actionable genes (ACMG SF v2.0 genes).
DeMAG web server allows scientists, health professionals or anyone curious to:
- access and download predictions for all ~1.3 million missense mutations for the ACMG SF v2.0 genes (ACMG59 genes),
- investigate the features of the model for any mutation to better understand DeMAG's pathogenicity score,
- download the high-quality training set to fully reproduce our results,
- download the validation sets we used to benchmark DeMAG against popular VEPs (REVEL, EVE, …).
DeMAG is a joint collaboration between the Max Planck Insitute of Molecular Cell Biology and Genetics (MPI-CBG) and Harvard Medical School (HMS). You can read our paper on bioRxiv:
DeMAG predicts the effect of variants in clinically actionable genes by integrating structural and evolutionary epistatic features
Federica Luppino1,2, Ivan A. Adzhubei4,5, Christopher A. Cassa4, Agnes Toth-Petroczy*1,2,3
1. Max Planck Institute of Molecular Cell Biology and Genetics, Dresden 01307, Germany. 2. Center for Systems Biology, Dresden 01307, Germany. 3. Cluster of Excellence Physics of Life, TU Dresden, 01062 Dresden, Germany. 4. Brigham and Womenʼs Hospital Division of Genetics, Harvard Medical School, Boston, MA, 02115 USA. 5. Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115.
 Kalia, S. S. et al. (2017). Recommendations for reporting of secondary findings in clinical exome and genome sequencing, 2016 update (ACMG SF v2.0): a policy statement of the American College of Medical Genetics and Genomics. Genet. Med. 19, 249–255
ACMG SF v2.0 genes
Table content downloaded from UniProt and ClinVar
Here you can search for your variant!
Variants with a pathogenicity probability greater or equal than 0.5 are predicted as pathogenic
The plot shows all missense substitutions for the selected gene. The black dot indicates the selected mutation
The violinplots show the distribution of the selected features for the benign and pathogenic class as in our training set. The white line corresponds to the specific variant's feature-value.
AlphaFold2 3D model
|Score1||PSIC score for wild type amino acid residue (aa1)||pph2|
|Score2||PSIC score for wild type amino acid residue (aa2)||pph2|
|dScore||difference of PSIC scores for two amino acid residue variants (Score1-Score2)||pph2|
|DistQmin||minimum distance (sum of branch lengths) along the phylogenetic tree across all substitution types encountered at the substitution position||pph2|
|phylop||conservation scoring by phyloP (phylogenetic p-values) from the PHAST package for multiple alignments of 99 vertebrate genomes to the human genome||pph2|
|BaRE||Bayesian Rate Estimator for scoring evolutionary conservation, D.M. Jordan (2015)||pph2|
|Nres||number of unique residues observed at the substitution position in multiple alignment (without gaps)||pph2|
|Nsubs||number of residues different from reference residue (aa1) observed at the substitution position in multiple alignment||pph2|
|EVmutation||A log-odds ratio between the sequence probability of the wild-type and the mutant sequence||T. A. Hopf (2017)|
|Partners score||residue's posterior probability of pathogenicity given the residue score of its co-evlving and spatially close residues positions||See Methods of the manuscript|
|NormASA||normalized accessible surface||pph2|
|IUPred2A disorder score||sequence-based disorder propensity predictor||IUPred2A|
|AlphaFold2 pLDDT||per-residue confidence metric on a scale from 0-100||AlphaFold2 FAQ|
The training data is available with the exception of HGMD variants as they are license protected.Download
We benchamrked DeMAG on clinical, functional and population data. The clinical and functional data can be found below, while the population data will be available on request. The population data refers to putatively benign common variants from the Estonia Biobank and as it is not public yet we can't upload the data on web server. Please refer to the methods section of the manuscript for a detailed description of the analysis of the testing set.