ArticleBMC bioinformatics2019
Performance assessment of variant calling pipelines using human whole exome sequencing and simulated data.
Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 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
39 citing papers in PubMed.
- Exome Sequencing in Patients with Loin Pain Hematuria Syndrome and Persistent Isolated Hematuria.Kidney international reports · 2026Article
- Best practices for improving alignment and variant calling on human sex chromosomes.American journal of human genetics · 2026Article
- Synth4bench: generating synthetic data for benchmarking tumor-only somatic variant calling algorithms.Frontiers in bioinformatics · 2026Article
- Comprehensive assessment of whole-genome sequencing-based variant calling pipelines in monozygotic twins.Briefings in bioinformatics · 2025Article
- Systematic evaluation of de novo mutation calling tools using whole genome sequencing data.Briefings in bioinformatics · 2025Article
- Performance comparison of germline variant calling tools in sporadic disease cohorts.Molecular genetics and genomics : MGG · 2025Article
- Current Bioinformatics Tools in Precision Oncology.MedComm · 2025Review
- A comprehensive catalog of single nucleotide polymorphisms (SNPs) from the black pepper (Piper nigrum L.) genome.BMC genomics · 2025Article
- Benchmarking accelerated next-generation sequencing analysis pipelines.Bioinformatics advances · 2025Article
- Decoding the mystery: AI-assisted bioinformatics and functional genomics technologies in medicinal plants.Frontiers in plant science · 2025Article
- SurVIndel2: improving copy number variant calling from next-generation sequencing using hidden split reads.Nature communications · 2024Article
- Reference Materials for Improving Reliability of Multiomics Profiling.Phenomics (Cham, Switzerland) · 2024Review
- Whole genome resequencing unveils low-temperature stress tolerance specific genomic variations in jute (Corchorus sp.).Journal, genetic engineering & biotechnology · 2024Article
- Validation of genetic variants from NGS data using deep convolutional neural networks.BMC bioinformatics · 2023Article
- Detection of potential functional variants based on systems-biology: the case of feed efficiency in beef cattle.BMC genomics · 2022Article
- Rapid genome sequencing for pediatrics.Human mutation · 2022Review
- Performance comparison of Agilent new SureSelect All Exon v8 probes with v7 probes for exome sequencing.BMC genomics · 2022Article
- Clinical exome sequencing-Mistakes and caveats.Human mutation · 2022Review
- A review of deep learning applications in human genomics using next-generation sequencing data.Human genomics · 2022Review
- The evaluation of Bcftools mpileup and GATK HaplotypeCaller for variant calling in non-human species.Scientific reports · 2022Article
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
backgroundWhole exome sequencing (WES) is a cost-effective method that identifies clinical variants but it demands accurate variant caller tools. Currently available tools have variable accuracy in predicting specific clinical variants. But it may be possible to find the best combination of aligner-variant caller tools for detecting accurate single nucleotide variants (SNVs) and small insertion and deletion (InDels) separately. Moreover, many important aspects of InDel detection are overlooked while comparing the performance of tools, particularly its base pair length.
resultsWe assessed the performance of variant calling pipelines using the combinations of four variant callers and five aligners on human NA12878 and simulated exome data. We used high confidence variant calls from Genome in a Bottle (GiaB) consortium for validation, and GRCh37 and GRCh38 as the human reference genome. Based on the performance metrics, both BWA and Novoalign aligners performed better with DeepVariant and SAMtools callers for detecting SNVs, and with DeepVariant and GATK for InDels. Furthermore, we obtained similar results on human NA24385 and NA24631 exome data from GiaB.
conclusionIn this study, DeepVariant with BWA and Novoalign performed best for detecting accurate SNVs and InDels. The accuracy of variant calling was improved by merging the top performing pipelines. The results of our study provide useful recommendations for analysis of WES data in clinical genomics.
Indexed as
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.