ArticleBMC bioinformatics2009
On reliable discovery of molecular signatures.
Article in BMC bioinformatics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- Trial
- Reconstructing the cell-cell interaction network among mouse immune cells.Biotechnology and bioengineering · 2023Article
- Current Status of Predictive Biomarker Development in Metastatic Renal Cell Carcinoma.Current oncology reports · 2023Review
- Environmental induced transgenerational inheritance impacts systems epigenetics in disease etiology.Scientific reports · 2022Article
- Augmentation of Transcriptomic Data for Improved Classification of Patients with Respiratory Diseases of Viral Origin.International journal of molecular sciences · 2022Article
- Analyzing large scale gene expression data in colorectal cancer reveals important clues; CLCA1 and SELENBP1 downregulated in CRC not in normal and not in adenoma.American journal of cancer research · 2022Article
- Review
- Epigenome-wide association study for glyphosate induced transgenerational sperm DNA methylation and histone retention epigenetic biomarkers for disease.Epigenetics · 2021Article
- A robust machine learning framework to identify signatures for frailty: a nested case-control study in four aging European cohorts.GeroScience · 2021Article
- Transgenerational disease specific epigenetic sperm biomarkers after ancestral exposure to dioxin.Environmental research · 2021Article
- Ancestral plastics exposure induces transgenerational disease-specific sperm epigenome-wide association biomarkers.Environmental epigenetics · 2021Article
- Epigenome-wide association study for transgenerational disease sperm epimutation biomarkers following ancestral exposure to jet fuel hydrocarbons.Reproductive toxicology (Elmsford, N.Y.) · 2020Article
- Epigenome-wide association study for pesticide (Permethrin and DEET) induced DNA methylation epimutation biomarkers for specific transgenerational disease.Environmental health : a global access science source · 2020Article
- Sex-Biased Molecular Signature for Overall Survival of Liver Cancer Patients.Biomolecules & therapeutics · 2020Review
- Article
- Epigenome-wide association study (EWAS) for potential transgenerational disease epigenetic biomarkers in sperm following ancestral exposure to the pesticide methoxychlor.Environmental epigenetics · 2020Article
- Article
- Genomic signatures for paclitaxel and gemcitabine resistance in breast cancer derived by machine learning.Molecular oncology · 2016Article
- Combining techniques for screening and evaluating interaction terms on high-dimensional time-to-event data.BMC bioinformatics · 2014Article
- Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMolecular signatures are sets of genes, proteins, genetic variants or other variables that can be used as markers for a particular phenotype. Reliable signature discovery methods could yield valuable insight into cell biology and mechanisms of human disease. However, it is currently not clear how to control error rates such as the false discovery rate (FDR) in signature discovery. Moreover, signatures for cancer gene expression have been shown to be unstable, that is, difficult to replicate in independent studies, casting doubts on their reliability.
resultsWe demonstrate that with modern prediction methods, signatures that yield accurate predictions may still have a high FDR. Further, we show that even signatures with low FDR may fail to replicate in independent studies due to limited statistical power. Thus, neither stability nor predictive accuracy are relevant when FDR control is the primary goal. We therefore develop a general statistical hypothesis testing framework that for the first time provides FDR control for signature discovery. Our method is demonstrated to be correct in simulation studies. When applied to five cancer data sets, the method was able to discover molecular signatures with 5% FDR in three cases, while two data sets yielded no significant findings.
conclusionOur approach enables reliable discovery of molecular signatures from genome-wide data with current sample sizes. The statistical framework developed herein is potentially applicable to a wide range of prediction problems in bioinformatics.
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