If you look at the materials and methods of ([https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5449402/][1]) 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? 


  [1]: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5449402/
Take your pick...

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

 - <a href="http://sift.jcvi.org/">SIFT</a>
 - <a href="http://agvgd.iarc.fr/">Align-GVGD</a>

 - <a href="http://mutationassessor.org/r3/">Mutation Assessor</a>
 - <a href="http://www.pantherdb.org/">PANTHER</a>
 - <a
   href="http://mendel.stanford.edu/SidowLab/downloads/MAPP/index.html">MAPP</a>
 - <a href="http://mupro.proteomics.ics.uci.edu/">MUpro</a>
 - <a href="http://www.mutationtaster.org/">MutationTasster</a>
 - <a
   href="http://folding.biofold.org/i-mutant/i-mutant2.0.html">I-Mutant</a>
 - <a href="http://decrypthon.igbmc.fr/kd4v">KD4v</a>
 - <a href="http://fathmm.biocompute.org.uk/">FATHMM</a>
 - <a href="http://sites.google.com/site/jpopgen/dbNSFP">dbNSFP</a>

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

 - <a href="http://genetics.bwh.harvard.edu/pph2/">PolyPhen-2</a>
 - <a href="http://ls-snp.icm.jhu.edu/ls-snp-pdb/">LS-SNP/PDB</a>
 - <a href="http://snpeffect.switchlab.org/">SNPeffect 4.0</a>

#Supervised-learning methods (for missense predictions)

 - <a href="http://mmb.irbbarcelona.org/PMut/">PMut</a>
 - <a href="https://www.rostlab.org/services/SNAP/">SNAP</a>
 - <a href="http://snps.biofold.org/phd-snp/phd-snp.html">PhD-SNP</a>
 - <a
   href="http://snps.biofold.org/snps-and-go/snps-and-go.html">SNPs&GO</a>
 - <a href="http://www.mobioinfor.cn/parepro/contact.htm">Parepro</a>
 - <a href="http://research-public.gene.com/">CanPredict</a>
 - <a href="http://snpanalyzer.uthsc.edu/">nsSNPAnalyzer</a>
 - <a href="http://mutpred.mutdb.org/">MutPred2</a>
 - <a href="http://hansa.cdfd.org.in:8080/">HANSA</a>
 - <a href="http://www.mutationtaster.org/">MutationTaster</a>

#Splice predictions

 - <a href="http://www.fruitfly.org/seq_tools/splice.html">NNSplice</a>
 - <a
   href="http://www.cbcb.umd.edu/software/GeneSplicer/gene_spl.shtml">GeneSplicer</a>
 - <a
   href="http://genes.mit.edu/burgelab/maxent/Xmaxentscan_scoreseq.html">MaxEntScan</a>
 - <a href="http://www.umd.be/HSF/">HSF</a>
 - <a href="http://www.cbs.dtu.dk/services/NetGene2/">NetGene2</a>

#Protein modelling (from amino acid sequence)

 - <a
   href="https://www.proteinmodelportal.org/?pid=modelling_interactive">Protein
   Model Portal</a>

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


#Non-coding (i.e. regulatory)

 - <a href="http://cadd.gs.washington.edu/">CADD</a> (germline
   variants)
 - <a href="https://www.ncbi.nlm.nih.gov/pubmed/25338716">DANN</a>
   (germline variants)
 - <a
   href="http://fathmm.biocompute.org.uk/fathmmMKL.htm">FATHMM-MKL</a>
   (germline variants)
 - <a
   href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5015703/">GWAVA</a>
   (germline variants | somatic mutations)
 - <a href="http://funseq2.gersteinlab.org/">Funseq2</a> (somatic
   mutations)
 - <a
   href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4224693/">SurfR</a>
   (rare variants | complex disease variants | all other variants)

# Other

 - <a href="http://mulinlab.tmu.edu.cn/gwas4d">GWAS3D / GWAS4D</a>

-------------------------

For further reading:

 - UK perspective, refer to the guidelines by the Association for
   Clinical Genomic Science:
   http://www.acgs.uk.com/quality/best-practice-guidelines/
 - US perspective, refer to American College of Medical Genetics:
   https://www.acmg.net/docs/Standards_Guidelines_for_the_Interpretation_of_Sequence_Variants.pdf

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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: https://www.biostars.org/p/286364/#286483

Kevin