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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arr234 •
Take your pick...
[uses various modelling algorithms and produces PDB files, which can be loaded into protein viewers like Jmol]
For further reading:
I assure you that there are even more tools than these. These are categorised to the best of my and my colleague's knowledge.
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Kevin
Great list. Don't forget the Variant Effect Predictor (Coding/Protein, mostly), SnpEff (variety of fields), and DeepSea (Non-coding/Regulatory).
You could take a look through each and try to make your choices that way.
Take a look at the material under 'further reading'. For example, in the UK, the clinical genetics regulatory body recommends certain tools over others.
what tools would you recommend to asses the effect of variants on ligand binding ?Schrodinger maestro seems good but it's a paid software.
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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