ArticleGenome biology2015
An ensemble approach to accurately detect somatic mutations using SomaticSeq.
Article in Genome biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 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
63 citing papers in PubMed.
- VariantMedium: sensitive and generalizable somatic point mutation calling with 3D DenseNets trained and evaluated on experimental data.Genome medicine · 2026Article
- Genetic attenuation of ALDH1A1 increases metastatic potential and aggressiveness in colorectal cancer.Molecular oncology · 2026Article
- Millennial clonal persistence and transposable element-biased somatic mutations in an herbaceous plant (Typha latifolia).Communications biology · 2026Article
- Benchmarking within-sample minority variant detection with short-read sequencing inbioRxiv : the preprint server for biology · 2026Article
- 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
- Clonal evolution and transcriptional plasticity shape metastatic dissemination routes in prostate cancer.Nature communications · 2025Article
- Reliable on-treatment prognostication and target identification with a customized assay for circulating tumor DNA in patients with newly diagnosed pancreatic cancer.Scientific reports · 2025Observational
- Integrated genomic analysis of NF1-associated peripheral nerve sheath tumors: an updated biorepository dataset.Scientific data · 2025Article
- UNISOM: Unified Somatic Calling and Machine Learning-based Classification Enhance the Discovery of CHIP.Genomics, proteomics & bioinformatics · 2025Article
- Predicting high confidence ctDNA somatic variants with ensemble machine learning models.Scientific reports · 2025Article
- A Comparative Genomic Analysis of Parathyroid Adenomas and Carcinomas Harboring Heterozygous Germline CDC73 Mutations.The Journal of clinical endocrinology and metabolism · 2025Article
- Benchmarking UMI-aware and standard variant callers for low frequency ctDNA variant detection.BMC genomics · 2024Article
- A Novel Affordable and Reliable Framework for Accurate Detection and Comprehensive Analysis of Somatic Mutations in Cancer.International journal of molecular sciences · 2024Article
- Heteroplasmy Is Rare in Plant Mitochondria Compared with Plastids despite Similar Mutation Rates.Molecular biology and evolution · 2024Article
- G-Quadruplex Forming DNA Sequence Context Is Enriched around Points of Somatic Mutations in a Subset of Multiple Myeloma Patients.International journal of molecular sciences · 2024Article
- Race-specific coregulatory and transcriptomic profiles associated with DNA methylation and androgen receptor in prostate cancer.Genome medicine · 2024Review
- Personalized cancer vaccine design using AI-powered technologies.Frontiers in immunology · 2024Review
- Leading the pack: Best practices in comparative canine cancer genomics to inform human oncology.Veterinary and comparative oncology · 2023Review
- Evaluating the performance of low-frequency variant calling tools for the detection of variants from short-read deep sequencing data.Scientific reports · 2023Article
- RFcaller: a machine learning approach combined with read-level features to detect somatic mutations.NAR genomics and bioinformatics · 2023Article
3 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
Abstract
SomaticSeq is an accurate somatic mutation detection pipeline implementing a stochastic boosting algorithm to produce highly accurate somatic mutation calls for both single nucleotide variants and small insertions and deletions. The workflow currently incorporates five state-of-the-art somatic mutation callers, and extracts over 70 individual genomic and sequencing features for each candidate site. A training set is provided to an adaptively boosted decision tree learner to create a classifier for predicting mutation statuses. We validate our results with both synthetic and real data. We report that SomaticSeq is able to achieve better overall accuracy than any individual tool incorporated.
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.