Variant prioritization software tools | High-throughput sequencing data analysis
Whole-exome sequencing has become a fundamental tool for the discovery of disease-related genes of familial diseases and the identification of somatic driver variants in cancer. However, finding the causal mutation among the enormous background of individual variability in a small number of samples is still a big challenge.
Identifies damaged genes and their disease-causing variants in personal genome sequences. VAAST combines elements of amino acid substitution (AAS) and aggregative approaches. The software can assay the impact of rare variants to identify rare diseases, and can use both common and rare variants to identify genes involved in common diseases. It includes Pedigree-VAAST (pVAAST), designed for high-throughput sequence data in pedigrees, which allows disease-gene identification.
A pipeline for ranking nonsynonymous single nucleotide variants given a specific phenotype. eXtasy takes into account the putative deleteriousness of the variant, haploinsufficiency predictions of the underlying gene and the similarity of the given gene to known genes in the given phenotype.
Allows highly accurate genome-scale identification of causative variants involved in human disease. PVP is a system which annotates and prioritizes disease variants in whole exome sequencing (WES) and whole genome sequencing (WGS) data. The software can identify causative variants on a large number of synthetic whole exome and whole genome sequences, covering a wide range of diseases and syndromes.
Enables prioritization of genes and variants in next-generation sequencing (NGS) projects for novel disease-gene discovery or differential diagnostics of Mendelian disease. Exomiser is a suite that contains several different methods for variant prioritization, based on protein-protein interactions and/or phenotype comparisons between a patient and existing human disease databases and model organisms. It provides methods using clinical data, model organism phenotype data, as well as random-walk analysis of protein interactome data to perform prioritization.
A three-level filtration and prioritization framework to identify the casual mutation(s) in exome sequencing studies. This efficient and comprehensive framework successfully narrowed down whole exome variants to very small numbers of candidate variants in the proof-of-concept examples. The proposed framework will play a very useful role in exome sequencing-based discovery of human Mendelian disease genes.
Computes positively selected candidate variants for functional follow-up. FineMAV can clarify a signal of selection to a single most likely selected variant and thus to discern it from the passenger variants for functional follow-up studies. This tool is appropriate for targets of recent or ongoing local positive selection underlying local adaptations in humans following the out-of-Africa migration. It can be applied to the whole genome or to a region of prior interest for discovering novel positively selected variants.
Helps in the identification of causative variants in family and sporadic genetic diseases. The program reads lists of predicted variants (nucleotide substitutions and indels) in affected individuals or tumor samples and controls. In family studies, different modes of inheritance can easily be defined to filter out variants that do not segregate with the disease along the family. Moreover, BiERapp integrates additional information such as allelic frequencies in the general population and the most popular damaging scores to further narrow down the number of putative variants in successive filtering steps.
Provides broad support for the VCF format, custom annotations, large VCF files, and flexible analysis types. VCF.Filter is an easy-to-use, standalone, graphical software that allows the user to interactively define, run, and save filter chains of any complexity using default and custom variant annotations. It can use and also help generate such cohort-specific tables of allele frequencies. VCF.Filter was developed in close collaboration with medical geneticists working on rare diseases of the immune system.
Allows an accessible, collaborative, replicable and holistic analysis of genetic variants. GeMSTONE permits to eliminate the time and space burdens associated with modern variant analysis tools. It saves users dozens of gigabytes of potential disk space per run for the same workflow on a medium sized dataset. The tool encourages the growth of the genomics research community. It will automate the (re)analysis of genome-wide genetic variation data and enhance the reproducibility of large-scale genomic studies.
Analyzes mutation-cancer drug associations based on given cancer genomic profiles. mTCTScan can prioritize mutations by incorporating all their associations with cancer drugs and preclinical compounds to classify the drugs or compounds by considering the entire cancer genomic profile provided. This tool compiles several types of data and the latest information to build an integrative one-stop web server that allows clinicians and researchers to interpret the effects of mutations on cancer drug sensitivity.
Allows clinical interpretation of genetic variants. InterVar automates generation of the preliminary interpretations for 18 criteria and then allows manual adjustment of additional criteria to arrive at the final interpretation. It calls an annotation software to obtain necessary annotation information on variants and then uses its own internal annotation database to supplement additional annotations.
Serves for prioritizing candidate variants in family-based studies of inherited disease. MendelScan can perform variant scoring, linkage mapping for family exome sequencing, shared identity-by-descent (IBD) mapping and rare-heterozygote-rule-out (RHRO) mapping.
Provides a powerful alternative environment for whole genome studies. VCF-Explorer is a software tool which is designed to carry out analysis for large VCF files. It is lightweight in structure and can process very large files without running out of memory. The graphical user interface (GUI) makes it easy to filter variants with respect to sample or variant level annotations. Finally, this method has major advantages for large VCF file processing over existing tools.
A variant prioritization tool in which user-provided phenotypic information is exploited to infer deeper biological context. OVA combines a knowledge-based approach with a variant-filtering framework. It reduces the number of candidate variants by considering genotype and predicted effect on protein sequence, and scores the remainder on biological relevance to the query phenotype.
A computational method to prioritize a set of candidates in exome sequencing projects that aim to identify novel Mendelian disease genes. This approach involves filtering a Variant Call Format (VCF) file according to a number of user-definable criteria, for instance, off-target variants (those that are not located within or close to protein-coding exons) are removed.
A cross-platform Java application toolkit to prioritize variants (SNVs and InDels) from exome or whole genome sequencing data by using different filtering strategies and information of external databases. PriVar contains four modules: annotation, quality control, candidate gene identification and prediction of functional impact of variants.
A standalone tool for working with annotated variant files, e.g. when searching for variants causing Mendelian disease. Very flexible in terms of input file formats, FILTUS offers efficient filtering and a range of downstream utilities, including statistical analysis of gene sharing patterns, detection of de novo mutations in trios, QC plots and autozygosity mapping. The autozygosity mapping is based on a hidden Markov model and enables accurate detection of autozygous regions directly from exome-scale variant files. FILTUS is primarily intended for WES-scale data, whole-genome data can be analysed by using the built-in prefiltering functionality.
A method for prioritizing putative impaired genes in cancer. ContrastRank is based on the comparison of exome sequencing data from different cohorts and can detect putative cancer driver genes. The method can also be used to estimate a global score for an individual genome about the risk of adenocarcinoma based on the genetic variants information from a whole-exome VCF (Variant Calling Format) file.
An interactive filtering tool for next generation sequencing data coming from the study of large complex disease pedigrees. Olorin is a tool which integrates gene flow output from Merlin and next generation sequencing data. Users can interactively filter and prioritize variants based on haplotype sharing across different sets of selected individuals and allele frequency in reference datasets.
Topics (10): WGS analysis, WES analysis, Central Nervous System Neoplasms, Nervous System Neoplasms, Brain Diseases, Breast Neoplasms, Breast Diseases, Neoplasms, Neoplasms, Connective and Soft Tissue, Genetic Diseases, Inborn