SynthesisNature communications2024
Clinical application of tumour-in-normal contamination assessment from whole genome sequencing.
Synthesis in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
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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
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.
- Clinical application of tumour-in-normal contamination assessment from whole genome sequencing.Nature communications · 2024Pooled it
- Dissecting cancer in a non-mammalian model: genomic insights from lemon frost geckos.BMC biology · 2026Article
- Evaluation of reference sample type for somatic variant calling in myeloid cancers.Annals of hematology · 2025Observational
- Article
- The microbial conductor of cancer hallmarks: intratumoral microbiome as a multidimensional oncogenic modulator.Frontiers in microbiology · 2025Review
- Computational validation of clonal and subclonal copy number alterations from bulk tumor sequencing using CNAqc.Genome biology · 2024Article
- Genomic Stratification of Hematological Malignancies.HemaSphere · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 4 institutions in 2 countries.
Funding
Abstract
The unexpected contamination of normal samples with tumour cells reduces variant detection sensitivity, compromising downstream analyses in canonical tumour-normal analyses. Leveraging whole-genome sequencing data available at Genomics England, we develop a tool for normal sample contamination assessment, which we validate in silico and against minimal residual disease testing. From a systematic review of [Formula: see text] patients with haematological malignancies and sarcomas, we find contamination across a range of cancer clinical indications and DNA sources, with highest prevalence in saliva samples from acute myeloid leukaemia patients, and sorted CD3+ T-cells from myeloproliferative neoplasms. Further exploration reveals 108 hotspot mutations in genes associated with haematological cancers at risk of being subtracted by standard variant calling pipelines. Our work highlights the importance of contamination assessment for accurate somatic variants detection in research and clinical settings, especially with large-scale sequencing projects being utilised to deliver accurate data from which to make clinical decisions for patient care.
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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.