| Coding variant effects/prioritization | Non-coding and coding variant effects/prioritization | CADD | Deleteriousness of variants | File of variants, precomputation of complete hg37/38 available | https://cadd.kircherlab.bihealth.org/ | Martin Kircher, BIH |
| Coding variant effects/prioritization | Impact on functional residues, e.g. protein-protein
interaction residues, stability, PTM sites, etc. | MutPred2 | A general score indicative of pathogenicity
and a ranked list of impacted mechanisms
(scores and P-values) | Protein sequences in FASTA format
with amino acid variants in XnY
format | http://mutpred.mutdb.org/ | Predrag Radivojac, Northeastern |
| Coding variant effects/prioritization | Impact on functional residues, e.g. protein-protein
interaction residues, stability, PTM sites, etc. | MutPred-LOF | A general score indicative of pathogenicity
and a ranked list of impacted mechanisms
(scores and P-values) | Protein sequences in FASTA format
with amino acid variants in ANNOVAR
format | http://mutpred2.mutdb.org/mutpredlof/ | Predrag Radivojac, Northeastern |
| Coding variant effects/prioritization | Impact on functional residues, e.g. protein-protein
interaction residues, stability, PTM sites, etc. | MutPred-Indel | A general score indicative of pathogenicity
and a ranked list of impacted mechanisms
(scores and P-values) | Protein sequences in FASTA format
with amino acid variants in ANNOVAR
format | http://mutpred2.mutdb.org/mutpredindel/ | Predrag Radivojac, Northeastern |
| Gene Regulatory Networks | | DREM | Dynamic regultory map of gene expression bifurcations and TFs associated with them | Time series gene expression and (static) TF-gene associations | https://github.com/jernst98/STEM_DREMhttp://sb.cs.cmu.edu/drem/ | Jason Ernst, UCLA |
| Gene Regulatory Networks | | cNMF | Sets of genes that are cofunctional/coexpressed in a given cell type | single-cell RNA data from tissue or Perturb-seq | https://github.com/dylkot/cNMF | Jesse Engreitz, Stanford |
| Noncoding variant effects/prioritization | GWAS | PoPS | Causal gene in a GWAS locus | Summary stats, catalog of gene sets | https://pmc.ncbi.nlm.nih.gov/articles/PMC10836580/ | Hilary Finucane, Broad & Jesse Engreitz, Stanford |
| Noncoding variant effects/prioritization | GWAS | ABC-Max | Causal gene ( with variant and cell context) in a GWAS locus; cell types enriched for fine-mapped variants for a trait | scATAC-seq/ATAC-seq/H3K27ac + fine-mapped variants | https://pubmed.ncbi.nlm.nih.gov/33828297/ | Jesse Engreitz, Stanford |
| Noncoding variant effects/prioritization | TF binding, regulatory element annotation | BPNet | Effect of a sequence variant on signal counts/shape in various assays e.g. ChIP-seq | A single epigenomic dataset (e.g. ChIP-seq) | https://github.com/kundajelab/bpnet | Anshul Kundaje, Stanford |
| Noncoding variant effects/prioritization | TF binding | Qbic | Calculates binding affinity change of a sequence variant (from reference) for a given TF | file of variants | http://qbic.genome.duke.edu | Andrew Allen, Duke & Raluca Gordan, Duke |
| Noncoding variant effects/prioritization | | ReMM | Deleteriousness of variants | File of variants, precomputation of complete hg37/38 available | https://remm.kircherlab.bihealth.org/ | Martin Kircher, BIH |
| Noncoding variant effects/prioritization | | CTMC | disease-specific (and optionally cell type-specific) variant-gene pairs | eQTL, GWAS, known variant-gene links, ATAC-seq, variant-TFBSs, GO and expression-based gene-gene similarities | https://academic.oup.com/bib/article/22/2/2161/5809565 | Maureen Sartor, UMich |
| Noncoding variant effects/prioritization | | SURF and TURF | Variant effect on TF binding in cell specific manner | DNase-seq, TF & Histone ChIP-seq, Footprints, PWMs through RegulomeDB | https://regulomedb.org/regulome-search/ | Alan Boyle, UMich |
| Noncoding variant effects/prioritization | coding variants and
gene annotations | FAVOR | Functionality of variants | 9 billion variants, multi-faceted pre-collected
variant and gene functional annotations | https://favor.genohub.org/ | Xihong Lin, HSPH |
| Noncoding variant effects/prioritization | | DragoNNFruit | Effect of a sequence variant on signal counts/shape in various single-cell and multimodal assays e.g. scATAC-seq | Nucleotide sequence and cell representations from a single-cell/multiome experiment | https://github.com/jmschrei/dragonnfruit | Anshul Kundaje, Stanford |
| Regulatory element annotation | | ChromHMM | Chromatin state annotations, cell type specific or cross-cell type | ChIP-seq, ATAC/DNase | https://ernstlab.biolchem.ucla.edu/ChromHMM/https://www.nature.com/articles/nmeth.1906 | Jason Ernst, UCLA |
| Regulatory element annotation | | ENCODE cCREs | Annotated promoter, enhancers, and other regulatory elements across hundreds of cell and tissue types | DNase/ATAC, H3K4me3, H3K27ac, CTCF | screen.encodeproject.org | Zhiping Weng, UMass & Jill Moore, UMass |
| Regulatory element annotation | | CAPRA | Calculates per element characterization score for WG-STARR-seq data and allow for studying combinatorial effects | WG-STARR-seq + element list | https://github.com/Moore-Lab-UMass/CAPRA | Jill Moore, UMass |
| Regulatory element annotation | | MACS2 | Does a variant overlap a DNase or ATAC peak (e.g., extended to a constant distance threshold) | ATAC-seq (bulk or sc), DNase-seq | https://github.com/macs3-project/MACS | |
| TF binding/motif discovery | Noncoding variant effects | ZMotif | Locations of high confidenceTF motifs | TF ChIP-seq, DNase/ATAC-seq | https://github.com/weng-lab/ZMotif | Zhiping Weng, UMass |
| TF binding/motif discovery | TF footprinting from ATAC data | PRINT | Predicting TF binding (footprints) from ATAC data | ATAC-seq (bulk or sc) | https://github.com/buenrostrolab/PRINT | Jason Buenrostro, Broad |
| Target gene prediction (element) | | ABC | Percent effect of DNase peak on gene expression in a given cell type; and whether a given ATAC/DNase peak is predicted to regulate any gene in a given cell type | scATAC (minimal). Ideally can also use H3k27ac ChIP-seq, Hi-C, good TSS annotations | https://github.com/broadinstitute/ABC-Enhancer-Gene-Prediction | Jesse Engreitz, Stanford |
| Target gene prediction (element) | | SCENT | Enhancer-gene links based on single-cell multimodal data | Single-cell multiome (ATAC+RNA) data | https://www.medrxiv.org/content/10.1101/2022.10.27.22281574v1 | Soumya Raychaudhuri, Brigham and Women’s Hospital |
| Target gene prediction (element) | | ENCODE-E2G | Enhancer-gene regulatory connections predicted from DNase-seq derived features in 352 ENCODE4 biosamples from a logistic regression model trained on K562 CRISPRi enhancer screen data. | DNase-seq, genome annotations/features | https://github.com/karbalayghareh/ENCODE-E2G | Christina Leslie, MSKCC & Jesse Engreitz, Stanford |
| Target gene prediction (variant) | | cS2G | Target gene for every variant | Genome-wide SNP-gene predictions | https://www.nature.com/articles/s41588-022-01087-y and data in https://alkesgroup.broadinstitute.org/cS2G/ | Steven Gazal, USC |