The Functional Analysis through Hidden Markov Models (fathmm) software and server is is capable of predicting the functional
effects of protein missense mutations by combining sequence conservation within hidden Markov models (HMMs), representing the
alignment of homologous (orthologous and/or paralogous) sequences and conserved protein domains, with "pathogenicity weights", representing the overall tolerance
of the corresponding model to mutations.
For more information, please refer to the following publications:
Shihab HA, Gough J, Cooper DN, Stenson PD, Barker GLA, Edwards KJ, Day INM, Gaunt, TR. (2013). Predicting the Functional, Molecular and Phenotypic
Consequences of Amino Acid Substitutions using Hidden Markov Models. Hum. Mutat., 34:57-65
Shihab HA, Gough J, Cooper DN, Day INM, Gaunt, TR. (2013). Predicting the Functional Consequences of Cancer-Associated Amino Acid Substitutions.
Bioinformatics 29:1504-1510.
Our software accepts one of the following formats (see here for annotating VCF files):
<protein> <substitution>
dbSNP rs identifiers
<protein>
is the protein identifier and <substitution>
is the amino acid substitution in the conventional one
letter format. At present, our server accepts SwissProt/TrEMBL, RefSeq and Ensembl protein identifiers, e.g.:
P43026 L441Por:
rs137854462
It is possible to submit multiple amino acid substitutions as a 'Batch Submission' via our server. Here, all amino acid substitutions for a protein can be
entered on a single line and should be separated by a comma, e.g:
P43026 L441P ENSP00000325527 N548I,E1073K,C2307S
Unfortunately, due to disk space constraints, we are unable to annotate Variant Call Format (VCF) files on your behalf. However, the consequences of all VCF variants
can be derived using the Ensembl Variant Effect Predictor (VEP).
Once annotated, the following script (available here) is capable of parsing these annotations and will provide you with a list of protein
consequences which can then be used as input into our server/software.
Additional help on using our script is available by typing the following command:
python parseVCF.py --help