ArticleNucleic acids research2014
The eSNV-detect: a computational system to identify expressed single nucleotide variants from transcriptome sequencing data.
Article in Nucleic acids research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed.
- Descriptive transcriptomic profiling differentiates oral leukoplakia from proliferative verrucous leukoplakia and reveals distinct molecular signatures.Medicina oral, patologia oral y cirugia bucal · 2026Article
- A Global Assessment of the Transcription-Dependent Single Nucleotide Variants Relies on the Characteristics of RNA-Sequencing Technologies.Biomolecules · 2026Article
- Refined variant calling pipeline on RNA-seq data of breast cancer cell lines without matched-normal samples.BMC research notes · 2025Article
- Article
- Review
- Selective Effect of DNA N6-Methyladenosine Modification on Transcriptional Genetic Variations in East Asian Samples.International journal of molecular sciences · 2024Article
- Genotype prediction of 336,463 samples from public expression data.bioRxiv : the preprint server for biology · 2024Article
- RNA-Seq-based discovery of genetic variants and allele-specific expression of two layer lines and broiler chicken.Evolutionary applications · 2023Article
- RNA-Seq Data for Reliable SNP Detection and Genotype Calling: Interest for Coding Variant Characterization andFrontiers in genetics · 2021Article
- Finding a suitable library size to call variants in RNA-Seq.BMC bioinformatics · 2020Article
- RNAIndel: discovering somatic coding indels from tumor RNA-Seq data.Bioinformatics (Oxford, England) · 2020Article
- Cell-level somatic mutation detection from single-cell RNA sequencing.Bioinformatics (Oxford, England) · 2019Article
- RNA sequence analysis reveals macroscopic somatic clonal expansion across normal tissues.Science (New York, N.Y.) · 2019Article
- Variant analysis pipeline for accurate detection of genomic variants from transcriptome sequencing data.PloS one · 2019Article
- Cancer transcriptome profiling at the juncture of clinical translation.Nature reviews. Genetics · 2018Review
- Pan-cancer analysis of expressed somatic nucleotide variants in long intergenic non-coding RNA.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2018Article
- A comparative study of RNA-Seq and microarray data analysis on the two examples of rectal-cancer patients and Burkitt Lymphoma cells.PloS one · 2018Article
- A review of somatic single nucleotide variant calling algorithms for next-generation sequencing data.Computational and structural biotechnology journal · 2018Review
- Characteristics of allelic gene expression in human brain cells from single-cell RNA-seq data analysis.BMC genomics · 2017Article
- Enabling Precision Cardiology Through Multiscale Biology and Systems Medicine.JACC. Basic to translational science · 2017Review
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Authors and funding
15 authors.
Funding
Abstract
Rapid development of next generation sequencing technology has enabled the identification of genomic alterations from short sequencing reads. There are a number of software pipelines available for calling single nucleotide variants from genomic DNA but, no comprehensive pipelines to identify, annotate and prioritize expressed SNVs (eSNVs) from non-directional paired-end RNA-Seq data. We have developed the eSNV-Detect, a novel computational system, which utilizes data from multiple aligners to call, even at low read depths, and rank variants from RNA-Seq. Multi-platform comparisons with the eSNV-Detect variant candidates were performed. The method was first applied to RNA-Seq from a lymphoblastoid cell-line, achieving 99.7% precision and 91.0% sensitivity in the expressed SNPs for the matching HumanOmni2.5 BeadChip data. Comparison of RNA-Seq eSNV candidates from 25 ER+ breast tumors from The Cancer Genome Atlas (TCGA) project with whole exome coding data showed 90.6-96.8% precision and 91.6-95.7% sensitivity. Contrasting single-cell mRNA-Seq variants with matching traditional multicellular RNA-Seq data for the MD-MB231 breast cancer cell-line delineated variant heterogeneity among the single-cells. Further, Sanger sequencing validation was performed for an ER+ breast tumor with paired normal adjacent tissue validating 29 out of 31 candidate eSNVs. The source code and user manuals of the eSNV-Detect pipeline for Sun Grid Engine and virtual machine are available at http://bioinformaticstools.mayo.edu/research/esnv-detect/.
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