How to choose good tools for identifying functional SNPs?
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4.0 years ago
arr234 ▴ 40

If you look at the materials and methods of (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5449402/) this paper, they have suggested using any three tools from each method (sequence homology-based methods, supervised learning methods, protein sequence and structure-based methods and consensus-based methods) to find the deleterious SNP. How do I choose the three best tools for each method?

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4.0 years ago

Take your pick...

Sequence and evolutionary- / homology- / conservation-based methods (for missense predictions)

Protein sequence and structure-based methods (for missense predictions)

Supervised-learning methods (for missense predictions)

Splice predictions

Protein modelling (from amino acid sequence)

[uses various modelling algorithms and produces PDB files, which can be loaded into protein viewers like Jmol]

Non-coding (i.e. regulatory)

  • CADD (germline variants)
  • DANN (germline variants)
  • FATHMM-MKL (germline variants)
  • GWAVA (germline variants | somatic mutations)
  • Funseq2 (somatic mutations)
  • SurfR (rare variants | complex disease variants | all other variants)

Other


For further reading:

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I assure you that there are even more tools than these. These are categorised to the best of my and my colleague's knowledge.

Previous posting: A: pathogenicity predictors of cancer mutations

Kevin

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Great list. Don't forget the Variant Effect Predictor (Coding/Protein, mostly), SnpEff (variety of fields), and DeepSea (Non-coding/Regulatory).

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Thank you, Kevin Blighe. So now I can choose randomly any tool from each category in this list or should the choice be based on any criteria for best tools?

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You could take a look through each and try to make your choices that way.

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Take a look at the material under 'further reading'. For example, in the UK, the clinical genetics regulatory body recommends certain tools over others.

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what tools would you recommend to asses the effect of variants on ligand binding ?Schrodinger maestro seems good but it's a paid software.

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Sounds more like quantum chemistry ... ? Take a look at Spartan molecular modelling, although, you will require a powerful computer to accurately predict the effects. Could also look at the link that I posted under Protein modelling (from amino acid sequence)

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