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. Author manuscript; available in PMC: 2024 Jun 1.
Published in final edited form as: Trends Genet. 2023 Mar 28;39(6):462–490. doi: 10.1016/j.tig.2023.02.014

Table 1.

Computational/in silico tools for annotation and characterization of genomic variants

Variant Type Tool Description Citation
Coding Ensembl Predicting effect of variant/amino acid substitution [14]
Meta-SNP [92]
PANTHER [93]
PolyPhen-2 [87]
PredictSNP 2.0 [8,90]
PROVEAN [88]
SIFT [86]
SNPs&GO [89]
SNPsnap [94]
SuSPect [96]
UMD-Predictor [95]
NetSurf2.0 Surface accessibility effects [97]
SOPMA Secondary structure effects [98]
I-mutant-3.0 Protein stability effects [99]
ConSurf Evolutionary conservation [100]
HOPE 3D structure effects [101]
SWISS-MODEL Homology modeling [102]
Promoter/Enhancer MotifBreakR TFBS disruption [117]
RegulomeDB Regulatory DNA variant prediction [108]
Basenji Deep learning [123]
DeepSea [121]
COLOC Colocalization [124]
eCaviar [25]
FUSION [127]
MetaXcan [125,126]
Splicing GeneSplicer Splicing site and variant effect prediction [131]
Human Splicing Finder [130]
NetGene2 [132,133]
RegSNPs-intron [128]
SpliceAI [129]
5’/3’ UTRs ExUTR 3’ UTR sequence prediction [111]
RegulomeDB UTR variant effect prediction [108]
UTRannotator 5’ UTR variant effect prediction [112]
UTRscan UTR sequence prediction [109,110]
miRNA/lncRNA CPSS 2.0 miRNA and lncRNA sequence prediction [116]
MicroSNiPer miRNA variant effect prediction [115]
miR2GO [114]
SubmiRine [113]