The mutation impact filters introduced in COSMIC v73 have been derived from the new FATHMM-MKL algorithm. This algorithm predicts the functional, molecular and phenotypic consequences of protein missense variants using hidden Markov models.

More information about FATHMM-MKL is available here

The new method improves on the older version of FATHMM and now incorporates ENCODE annotation for its prediction. This method is as powerful as CADD scores for coding variants and shows improved prediction for non-coding variants (compared to GWAVA and CADD).

The functional scores for individual mutations from FATHMM-MKL are in the form of a single p-value, ranging from 0 to 1. Scores above 0.5 are deleterious, but in order to highlight the most significant data in COSMIC, only scores ≥ 0.7 are classified as 'Pathogenic'. Mutations are classed as 'Neutral' if the score is ≤ 0.5. In addition, each functional score is classified into 10 groups of features, depending on whether it is a coding or non-coding variant. Please see the original publication for more details regarding the feature classification (doi:10.1093/bioinformatics/btv009).

The following is reproduced from the publication in order to aid interpretation:

Description for each of the feature groups [A-J]

• A. 46-Way Sequence Conservation: based on multiple sequence alignment scores, at the nucleotide level, of 46 vertebrate genomes compared with the human genome.
• B. Histone Modifications (ChIP-Seq): based on ChIP-Seq peak calls for histone modifications.
• C. Transcription Factor Binding Sites (TFBS PeakSeq): based on PeakSeq peak calls for various transcription factors.
• D. Open Chromatin (DNase-Seq): based on DNase-Seq peak calls.
• E. 100-Way Sequence Conservation: based on multiple sequence alignment scores, at the nucleotide level, of 100 vertebrate genomes compared with the human genome.
• F. GC Content: based on a single measure for GC content calculated using a span of five nucleotide bases from the UCSC Genome Browser.
• G. Open Chromatin (FAIRE): based on formaldehyde-assisted isolation of regulatory elements (FAIRE) peak calls.
• H. Transcription Factor Binding Sites (TFBS SPP): based on SPP peak calls for various transcription factors.
• I. Genome Segmentation: based on genome-segmentation states using a consensus merge of segmentations produced by the ChromHMM and Segway software.
• J. Footprints: based on annotations describing DNA footprints across cell types from ENCODE.

Please note: The current FATHMM-MKL algorithm is trained on the human gene mutation database (The HGMD database http://www.hgmd.cf.ac.uk/ac/index.php), which now also contains somatic variants. Results from the current available version of FATHMM-MKL can be used/has been used for somatic variants, but the user should be aware of the caveats. The cancer specific version of FATHMM-MKL is under development and when available these scores will be updated.

Recurrence is defined by counting whole genome screened tumour samples, according to the mutation type -

Substitutions: ≥ 3 samples with a missense substitution in the same codon
Inframe Indels: ≥ 3 samples with an inframe indel in the same codon
Terminations: > 10 samples with a mutation causing premature protein termination