ArticleGenome biology2019
Impact of mouse contamination in genomic profiling of patient-derived models and best practice for robust analysis.
Article in Genome biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 30 citations in OpenAlex.
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- Nucleosome Patterns in Circulating Tumor DNA Reveal Transcriptional Regulation of Advanced Prostate Cancer Phenotypes.Cancer discovery · 2023Article
- Characterization of Leukemic Resistance to CD19-Targeted CAR T-cell Therapy through Deep Genomic Sequencing.Cancer immunology research · 2023Article
- Weight-bearing activity impairs nuclear membrane and genome integrity via YAP activation in plantar melanoma.Nature communications · 2022Article
- A renal cell carcinoma tumorgraft platform to advance precision medicine.Cell reports · 2021Article
- Subtype heterogeneity and epigenetic convergence in neuroendocrine prostate cancer.Nature communications · 2021Article
- TPM, FPKM, or Normalized Counts? A Comparative Study of Quantification Measures for the Analysis of RNA-seq Data from the NCI Patient-Derived Models Repository.Journal of translational medicine · 2021Article
- Fast lightweight accurate xenograft sorting.Algorithms for molecular biology : AMB · 2021Article
- Impact of mouse contamination in genomic profiling of patient-derived models and best practice for robust analysis.Genome biology · 2019Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPatient-derived xenograft and cell line models are popular models for clinical cancer research. However, the inevitable inclusion of a mouse genome in a patient-derived model is a remaining concern in the analysis. Although multiple tools and filtering strategies have been developed to account for this, research has yet to demonstrate the exact impact of the mouse genome and the optimal use of these tools and filtering strategies in an analysis pipeline.
resultsWe construct a benchmark dataset of 5 liver tissues from 3 mouse strains using human whole-exome sequencing kit. Next-generation sequencing reads from mouse tissues are mappable to 49% of the human genome and 409 cancer genes. In total, 1,207,556 mouse-specific alleles are aligned to the human genome reference, including 467,232 (38.7%) alleles with high sensitivity to contamination, which are pervasive causes of false cancer mutations in public databases and are signatures for predicting global contamination. Next, we assess the performance of 8 filtering methods in terms of mouse read filtration and reduction of mouse-specific alleles. All filtering tools generally perform well, although differences in algorithm strictness and efficiency of mouse allele removal are observed. Therefore, we develop a best practice pipeline that contains the estimation of contamination level, mouse read filtration, and variant filtration.
conclusionsThe inclusion of mouse cells in patient-derived models hinders genomic analysis and should be addressed carefully. Our suggested guidelines improve the robustness and maximize the utility of genomic analysis of these models.
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