ArticleStatistical methods in medical research
Robust identification of target genes and outliers in triple-negative breast cancer data.
Article in Statistical methods in medical research. 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.
- UGT8/GalCer-dependent resistance of breast cancer cells to drug-induced apoptosis is potentially regulated by the LIM/homeobox protein LHX6.Scientific reports · 2026Article
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- Junctional adhesion molecular 3 (JAM3) is a novel tumor suppressor and improves the prognosis in breast cancer brain metastases via the TGF-β/Smad signal pathway.Journal of neuro-oncology · 2024Article
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- Machine learning-guided differential gene expression analysis identifies a highly-connected seven-gene cluster in triple-negative breast cancer.BioMedicine · 2024Article
- Transcriptomics of Canine Inflammatory Mammary Cancer Treated with Empty Cowpea Mosaic Virus Implicates Neutrophils in Anti-Tumor Immunity.International journal of molecular sciences · 2023Article
- Statistical analysis of high-dimensional biomedical data: a gentle introduction to analytical goals, common approaches and challenges.BMC medicine · 2023Review
- Gene expression signatures of individual ductal carcinoma in situ lesions identify processes and biomarkers associated with progression towards invasive ductal carcinoma.Nature communications · 2022Article
- ROSIE: RObust Sparse ensemble for outlIEr detection and gene selection in cancer omics data.Statistical methods in medical research · 2022Article
- An Efficient Algorithm for the Detection of Outliers in Mislabeled Omics Data.Computational and mathematical methods in medicine · 2021Article
- Comparison of methods for the detection of outliers and associated biomarkers in mislabeled omics data.BMC bioinformatics · 2020Article
- Multiplatform biomarker identification using a data-driven approach enables single-sample classification.BMC bioinformatics · 2019Article
- Twiner: correlation-based regularization for identifying common cancer gene signatures.BMC bioinformatics · 2019Article
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Authors and funding
5 authors.
Funding
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Abstract
Correct classification of breast cancer subtypes is of high importance as it directly affects the therapeutic options. We focus on triple-negative breast cancer which has the worst prognosis among breast cancer types. Using cutting edge methods from the field of robust statistics, we analyze Breast Invasive Carcinoma transcriptomic data publicly available from The Cancer Genome Atlas data portal. Our analysis identifies statistical outliers that may correspond to misdiagnosed patients. Furthermore, it is illustrated that classical statistical methods may fail to identify outliers due to their heavy influence, prompting the need for robust statistics. Using robust sparse logistic regression we obtain 36 relevant genes, of which ca. 60% have been previously reported as biologically relevant to triple-negative breast cancer, reinforcing the validity of the method. The remaining 14 genes identified are new potential biomarkers for triple-negative breast cancer. Out of these,
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