ArticleGenomics2016
Practicability of detecting somatic point mutation from RNA high throughput sequencing data.
Article in Genomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 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
25 citing papers in PubMed, 41 citations in OpenAlex.
- AI/ML-Driven Gene Analysis: New Perspectives on Variant Calling in Normal Human Tissue Using scRNA-seq Data.Methods in molecular biology (Clifton, N.J.) · 2026Article
- MutAnt: mutation annotation tool predicts deleteriousness of missense mutations and improves mutation calling from transcriptomics.Human genetics · 2025Article
- RNA sequencing enables neoantigen discovery and vaccine validation in breast and lung cancer.Frontiers in immunology · 2025Article
- Review
- Pan-cancer discovery of somatic mutations from RNA sequencing data.Communications biology · 2024Article
- Treasures from trash in cancer research.Oncotarget · 2022Article
- RNA splicing: a dual-edged sword for hepatocellular carcinoma.Medical oncology (Northwood, London, England) · 2022Review
- RNA-SSNV: A Reliable Somatic Single Nucleotide Variant Identification Framework for Bulk RNA-Seq Data.Frontiers in genetics · 2022Article
- Screening of Variants in the Transcript Profile of Eutopic Endometrium from Infertile Women with Endometriosis during the Implantation Window.Revista brasileira de ginecologia e obstetricia : revista da Federacao Brasileira das Sociedades de Ginecologia e Obstetricia · 2021Article
- Adaptive Differences in Gene Expression in Farm-Impacted Seedbeds of the Native Blue MusselFrontiers in genetics · 2021Article
- Neoantigen prediction in human breast cancer using RNA sequencing data.Cancer science · 2021Article
- Article
- Application of Biological Domain Knowledge Based Feature Selection on Gene Expression Data.Entropy (Basel, Switzerland) · 2020Review
- Main Strategies for the Identification of Neoantigens.Cancers · 2020Review
- Single-cell RNA-seq variant analysis for exploration of genetic heterogeneity in cancer.Scientific reports · 2019Article
- RNA sequence analysis reveals macroscopic somatic clonal expansion across normal tissues.Science (New York, N.Y.) · 2019Article
- Single-nucleotide variants in human RNA: RNA editing and beyond.Briefings in functional genomics · 2019Review
- Mutational landscape of canine B-cell lymphoma profiled at single nucleotide resolution by RNA-seq.PloS one · 2019Article
- Power and sample size calculations for high-throughput sequencing-based experiments.Briefings in bioinformatics · 2018Article
- Expressed HNSCC variants by HPV-status in a well-characterized Michigan cohort.Scientific reports · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
Abstract
Traditionally, somatic mutations are detected by examining DNA sequence. The maturity of sequencing technology has allowed researchers to screen for somatic mutations in the whole genome. Increasingly, researchers have become interested in identifying somatic mutations through RNAseq data. With this motivation, we evaluated the practicability of detecting somatic mutations from RNAseq data. Current somatic mutation calling tools were designed for DNA sequencing data. To increase performance on RNAseq data, we developed a somatic mutation caller GLMVC based on bias reduced generalized linear model for both DNA and RNA sequencing data. Through comparison with MuTect and Varscan we showed that GLMVC performed better for somatic mutation detection using exome sequencing or RNAseq data. GLMVC is freely available for download at the following website: https://github.com/shengqh/GLMVC/wiki.
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.