ArticleBMC genomics2014
Are special read alignment strategies necessary and cost-effective when handling sequencing reads from patient-derived tumor xenografts?
Article in BMC genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Modeling Clinical Responses to Targeted Therapies by Patient-Derived Organoids of Advanced Lung Adenocarcinoma.Clinical cancer research : an official journal of the American Association for Cancer Research · 2021Article
- Chromatin conformation capture (Hi-C) sequencing of patient-derived xenografts: analysis guidelines.GigaScience · 2021Article
- Enhanced engraftment of human myelofibrosis stem and progenitor cells in MISTRG mice.Blood advances · 2020Article
- Establishment and characterization of patient-derived xenografts as paraclinical models for head and neck cancer.BMC cancer · 2020Article
- Patient-Derived Cells to Guide Targeted Therapy for Advanced Lung Adenocarcinoma.Scientific reports · 2019Article
- Genomic data analysis workflows for tumors from patient-derived xenografts (PDXs): challenges and guidelines.BMC medical genomics · 2019Article
- Primary Tumor Site Specificity is Preserved in Patient-Derived Tumor Xenograft Models.Frontiers in genetics · 2019Article
- XenofilteR: computational deconvolution of mouse and human reads in tumor xenograft sequence data.BMC bioinformatics · 2018Article
- Comparison of the Genetic Alterations between Primary Colorectal Cancers and Their Corresponding Patient-Derived Xenograft Tissues.Genomics & informatics · 2018Article
- Sensitive and specific post-call filtering of genetic variants in xenograft and primary tumors.Bioinformatics (Oxford, England) · 2018Article
- Establishment and characterisation of patient-derived xenografts as paraclinical models for gastric cancer.Scientific reports · 2016Article
- Targeting PTPRK-RSPO3 colon tumours promotes differentiation and loss of stem-cell function.Nature · 2016Article
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4 authors.
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Abstract
backgroundPatient-derived tumor xenografts in mice are widely used in cancer research and have become important in developing personalized therapies. When these xenografts are subject to DNA sequencing, the samples could contain various amounts of mouse DNA. It has been unclear how the mouse reads would affect data analyses. We conducted comprehensive simulations to compare three alignment strategies at different mutation rates, read lengths, sequencing error rates, human-mouse mixing ratios and sequenced regions. We also sequenced a nasopharyngeal carcinoma xenograft and a cell line to test how the strategies work on real data.
resultsWe found the "filtering" and "combined reference" strategies performed better than aligning reads directly to human reference in terms of alignment and variant calling accuracies. The combined reference strategy was particularly good at reducing false negative variants calls without significantly increasing the false positive rate. In some scenarios the performance gain of these two special handling strategies was too small for special handling to be cost-effective, but it was found crucial when false non-synonymous SNVs should be minimized, especially in exome sequencing.
conclusionsOur study systematically analyzes the effects of mouse contamination in the sequencing data of human-in-mouse xenografts. Our findings provide information for designing data analysis pipelines for these data.
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