ReviewInternational journal of genomics2016
A Survey of Computational Tools to Analyze and Interpret Whole Exome Sequencing Data.
Review in International journal of genomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
24 citing papers in PubMed.
- Genetic Sequencing in Saudi Patients with Systemic Lupus Erythematosus.Open access rheumatology : research and reviews · 2026Article
- Article
- Authors' Reply: Using VNtyper from Whole Exome Sequencing Data to Detect Pathogenic Variants in the MUC1 Gene.Journal of the American Society of Nephrology : JASN · 2025Article
- Whole-Exome Analysis and Osteosarcoma: A Game Still Open.International journal of molecular sciences · 2024Review
- Research progress of CTC, ctDNA, and EVs in cancer liquid biopsy.Frontiers in oncology · 2024Review
- Article
- Local data commons: the sleeping beauty in the community of data commons.BMC bioinformatics · 2022Article
- Diagnosis of a Single-Nucleotide Variant in Whole-Exome Sequencing Data for Patients With Inherited Diseases: Machine Learning Study Using Artificial Intelligence Variant Prioritization.JMIR bioinformatics and biotechnology · 2022Article
- LeMeDISCO is a computational method for large-scale prediction & molecular interpretation of disease comorbidity.Communications biology · 2022Article
- Multiple Variant Calling Pipelines in Wheat Whole Exome Sequencing.International journal of molecular sciences · 2021Article
- Simulation of African and non-African low and high coverage whole genome sequence data to assess variant calling approaches.Briefings in bioinformatics · 2021Article
- Cruxome: a powerful tool for annotating, interpreting and reporting genetic variants.BMC genomics · 2021Article
- PedMiner: a tool for linkage analysis-based identification of disease-associated variants using family based whole-exome sequencing data.Briefings in bioinformatics · 2021Review
- Genetic variants of small airways and interstitial pulmonary disease in children.Scientific reports · 2021Article
- An Exploration of Mutagenesis in a Family with Cleidocranial Dysplasia withoutFrontiers in genetics · 2021Article
- Culture-free genome-wide locus sequence typing (GLST) provides new perspectives on Trypanosoma cruzi dispersal and infection complexity.PLoS genetics · 2020Article
- Computational Prediction and Validation of Tumor-Associated Neoantigens.Frontiers in immunology · 2020Review
- Genome analysis and knowledge-driven variant interpretation with TGex.BMC medical genomics · 2019Article
- Frequency of pathogenic germline variants in BRCA1, BRCA2, PALB2, CHEK2 and TP53 in ductal carcinoma in situ diagnosed in women under the age of 50 years.Breast cancer research : BCR · 2019Article
- Circulating tumor DNA detection: A potential tool for colorectal cancer management.Oncology letters · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Whole Exome Sequencing (WES) is the application of the next-generation technology to determine the variations in the exome and is becoming a standard approach in studying genetic variants in diseases. Understanding the exomes of individuals at single base resolution allows the identification of actionable mutations for disease treatment and management. WES technologies have shifted the bottleneck in experimental data production to computationally intensive informatics-based data analysis. Novel computational tools and methods have been developed to analyze and interpret WES data. Here, we review some of the current tools that are being used to analyze WES data. These tools range from the alignment of raw sequencing reads all the way to linking variants to actionable therapeutics. Strengths and weaknesses of each tool are discussed for the purpose of helping researchers make more informative decisions on selecting the best tools to analyze their WES data.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.