Unlock your biological data


Try: RNA sequencing CRISPR Genomic databases DESeq

1 - 50 of 66 results
filter_list Filters
language Programming Language
build Technology
healing Disease
settings_input_component Operating System
tv Interface
computer Computer Skill
copyright License
1 - 50 of 66 results
VAAST / Variant Annotation, Analysis and Search Tool
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.
FineMAV / Fine-Mapping of Adaptive Variation
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.
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.
BiERapp / BioInformatic for Rare Diseases
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.
GeMSTONE / Germline Mutation Scoring Tool fOr Next-Generation sEquencing data
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.
mTCTScan / Mutation To Cancer Therapy Scan
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.
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 scoring based method to evaluate every gene for their disease association. GeneCOST has major advantages over existing programs. GeneCOST supports pedigree information and multiple patient cases. The program does not require any prior knowledge of the disease, hence it can be used to identify novel genes. The disease-likelihood score is calculated on a gene level approach, therefore GeneCOST provides a valuable tool for sporadic cases where the patients do not have any kinship relation. Finally, the proposed method does not rely on any filtering procedure, hence it is more robust to NGS related errors which has not been observed at any other programs.
GARFIELD-NGS / Genomic vARiants FIltering by dEep Learning moDels in NGS
Classifies true and false variants. GARFIELD-NGS can be applied in single sample whole exome sequencing (WES) analysis and it is effective on single nucleotide polymorphisms (SNPs) and insertion/deletions (INDELs) variants derived from both Illumina or ION platform. It can be useful for medium and low coverage dataset and be applied to experiments based on the recent 2-colour Illumina chemistry. The tool relies on neural networks algorithm.
SPRING / Snv PRioritization via the INtegration of Genomic data
A bioinformatics method for the prediction of disease-causing nonsynonymous single nucleotide variants (SNVs) in exome sequencing studies. Given a query disease and a set of candidate nonsynonymous SNVs, SPRING calculates a q-value to indicate the statistical significance that a variant is causative for a query disease and hence provides a means of prioritizing candidate variants. SPRING achieves this goal by integrating six deleterious scores calculated by existing methods (SIFT, PolyPhen2, LRT, MutationTaster, GERP and PhyloP) and five association scores derived from a variety of genomic data sources (gene ontology, protein-protein interactions, protein sequences, protein domain annotations and gene pathway annotations).
A graphical user interface for sorting, filtering and querying information encoded in VCF files. Powered by a MongoDB database engine, VCF-Miner enables the stepwise trimming of non-relevant variants. The grouping feature implemented in VCF-Miner can be used to identify somatic variants by contrasting variants in tumor and in normal samples or to identify recessive/dominant variants in family studies. It is not limited to human data, but can also be extended to include non-diploid organisms. It also supports copy number or any other variant type supported by the VCF specification.
Enables researchers to browse, query and filter millions of variants in a few seconds. Top features include the possibility to store intermediate search results, to query user-defined gene lists, to group samples for family or tumour/normal studies, to download a report of the filters applied, and to export the filtered variants in spreadsheet format. Additionally, BrowseVCF is suitable for any DNA variant analysis (exome, whole-genome and targeted sequencing), can be used also for non-diploid genomes, and is able to discriminate between single nucleotide polymorphisms (SNPs), insertions/deletions (InDels), and multiple nucleotide polymorphisms (MNPs). Thanks to its portable implementation, BrowseVCF can be used either on personal computers or as part of automated analysis pipelines. It consists of a back-end service of Python scripts and a web server that runs locally, and of a front end built in JavaScript, CSS, and HTML5, leveraging popular cross-platform libraries such as AngularJS and Bootstrap.
A computational combinatorial system to efficiently annotate cDNA substitutions of all human transcripts for their potential pathogenicity. UMD-Predictor combines biochemical properties, impact on splicing signals, localization in protein domains, variation frequency in the global population, and conservation through the BLOSUM62 global substitution matrix and a protein-specific conservation among 100 species. We compared its accuracy to the seven most used and reliable prediction tools, using the largest reference variation datasets including more than 140,000 annotated variations. This system consistently demonstrated a better accuracy, specificity, Matthews correlation coefficient, Diagnostic Odds Ratio, speed and provided the shortest list of candidate mutations for WES.
A flexible gene-ranking method that incorporates interaction network data. HetRank consistently prioritizes more disease-causing genes than existing analysis methods. It addresses the problem of genetic heterogeneity in exome sequencing studies by incorporating information from biological networks. Finally, HetRank can incorporate healthy control exomes to address the overrepresentation of long and variant-tolerating genes among prioritized variants, a common problem in exome sequencing studies.
A user-friendly online framework, wKGGSeq, to provide systematic annotation, filtration, prioritization, and visualization functions for characterizing causal mutation(s) in exome sequencing studies of inherited disorders. wKGGSeq provides: (1) a novel strategy-based procedure for downstream analysis of a large amount of exome sequencing data and (2) a disease-targeted analysis procedure to facilitate clinical diagnosis of well-studied genetic diseases. In addition, it is also equipped with abundant online annotation functions for sequence variants.
Clinical NGS DB / Clinical Next‐Generation Sequencing Database
Allows efficient clinical Next Generation Sequencing (NGS) analysis of inherited diseases through the collection of data. Clinical NGS DB contains a database that offers a two-featured approach to variant pathogenicity classification. It permits to manage data and clinical diagnosis using the patient’s clinical information. The tool permits management of genome analysis information and patient clinical information for efficient clinical diagnosis.
Organizes, annotates, filters and diagnoses patients with Mendelian Disorders using Exome and Genome sequencing data or experimental validation and possible diagnosis. Mendel,MD combines several types of filter options and uses regularly updated databases to facilitate exome and genome annotation, the filtering process and the selection of candidate genes and variants. The software provides a limited list of good candidates that can always be manually investigated by researchers and doctors using their research and clinical skills.
A free web-based phenotype-dependent NGS variant prioritizer, which leverages the wealth of information in GeneCards and its affiliated databases. VarElect employs GeneCards’ powerful search and scoring capacities, and its algorithm affords inferring direct as well as indirect links between sequenced genes and disease/symptom/phenotype keywords. The indirect links benefit from GeneCards’ excellent capacity to relate genes to each other via numerous annotations. VarElect thus provides a robust facility for ranking genes and pointing out their likelihood to be related to a patient’s disease.
A tool to improve the clinical utility of computational CNV prediction in exome data. cnvScan can accept input from any CNV prediction program. cnvScan consists of two steps: CNV screening and CNV annotation. CNV screening evaluates CNV prediction using quality scores and refines this using an in-house CNV database, which greatly reduces the false positive rate. The annotation step provides functionally and clinically relevant information using multiple source datasets. cnvScan enables researchers to use different programs to predict CNVs and apply suitable filtration thresholds to remove false positives and non-disease- casing variants. This reduces the time and effort required to detect disease-causing CNVs and improves the clinical utility of exonic CNV prediction.
Permits analysis of several types of variants, including single nucleotide polymorphisms (SNPs), insertion-deletions (indels) and structural variants (SV). Mendelian was tested by reanalyzing the data of a human whole exome sequencing (WES) experiment and by revalidating the recessively inherited yellow and brown coat color phenotypes in the Labrador Retriever. It can be useful to identify causal variant in sequencing studies, especially in non-human species were the alternatives are very limited.
Variant Ranker
Provides the ability to rank both coding and noncoding variants by encoding and integrating information from multiple sources. Variant Ranker is a web server for performing annotation, filtering and ranking of identified genomic variants based on various available databases of genetic variants and facilitating a system for a-priori weight input by user to identify the most important variants under study. It was developed to help researchers without much computational skills to perform their genomic data analysis.
quantile-based approach
Offers a way to filter variants. Quantile-based approach is a method based on features from both database and disease. It calculates the assumed allele frequency of the disease-causing allele in variant databases by combining knowledge on disease prevalence, mode of inheritance, database size and properties. The method can be used for the determination of variants that divert from their proposed role in specific phenotypes as well as for improving search about novel disease-causing mutations.
OVAS / Open-source Variant Analysis Sequencing
Allows analysis of sequence variants. OVAS is designed for annotating and extracting useful variants from Variant Call Format (VCF) files. The software provides a self-contained environment allowing users to tailor all aspects of their analysis and retain control of their data sets at any phase of processing, using the modules that comprise the pipeline. OVAS annotates variants using data from trusted public domain databases such as RefGene, dbSNP, UniProt, and others.
A simple and powerful tool designed for variant ranking from next generation sequencing data. VaRank provides a comprehensive workflow for annotating and ranking SNVs and indels. Four modules create the strength of this workflow: (i) Variant call quality summary (total and variant depth of coverage, phred like information), to filter out false positive calls, (ii) Alamut Batch or SnpEff variant annotations, to integrate genetic and predictive information (functional impact, putative effects in the protein coding regions, population frequency...) from different sources, using HGVS nomenclature, (iii) Barcode representing the presence/absence of variants (with homozygote/heterozygote status), to search for recurrence between families or group of individuals, and (iv) Prioritization score, to rank variants according to their predicted pathogenic status. VaRank results aims at reducing the daily work of clinical geneticists and molecular biologists and will help to accelerate the progress in identifying disease causing variants.
Provides a one-stop analysis of these data and a comprehensive, interactive and easy-to-understand report with many advanced visualization features. RETA is an R package that includes various in-depth quality control measures, integrative coverage examination and visualization, detection of runs-of-homozygosity and interactive, straightforward analysis results presentation. It facilitates clinicians and scientists alike to better analyze and interpret this type of sequencing data for disease diagnoses.
0 - 0 of 0 results
1 - 7 of 7 results
filter_list Filters
computer Job seeker
Disable 4
person Position
thumb_up Fields of Interest
public Country
language Programming Language
1 - 7 of 7 results

By using OMICtools you acknowledge that you have read and accepted the terms of the end user license agreement.