ArticleBioinformatics (Oxford, England)2008
Cancer outlier detection based on likelihood ratio test.
Article in Bioinformatics (Oxford, England), 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 22 citations in OpenAlex.
- Anomaly Detection in High-Dimensional Time Series Data with Scaled Bregman Divergence.Algorithms · 2025Article
- Multivariate Time Series Change-Point Detection with a Novel Pearson-like Scaled Bregman Divergence.Stats · 2024Article
- Integrative gene set analysis of multi-platform data with sample heterogeneity.Bioinformatics (Oxford, England) · 2014Article
- Whole-genome sequencing and comprehensive molecular profiling identify new driver mutations in gastric cancer.Nature genetics · 2014Article
- Pathway-based outlier method reveals heterogeneous genomic structure of autism in blood transcriptome.BMC medical genomics · 2013Article
- Comparison of methods to identify aberrant expression patterns in individual patients: augmenting our toolkit for precision medicine.Genome medicine · 2013Article
- Weighted change-point method for detecting differential gene expression in breast cancer microarray data.PloS one · 2012Article
- Outlier-Based Differential Expression Analysis in Proteomics Studies.Journal of proteomics & bioinformatics · 2011Article
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Corrections and comments
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Authors and funding
1 author at 1 institution in 1 country.
Funding
Abstract
motivationMicroarray experiments can be used to help study the role of chromosomal translocation in cancer development through cancer outlier detection. The aim is to identify genes that are up- or down-regulated in a subset of cancer samples in comparison to normal samples.
resultsWe propose a likelihood-based approach which targets detecting the change of point in mean expression intensity in the group of cancer samples. A desirable property of the proposed approach is the availability of theoretical significance-level results. Simulation studies showed that the performance of the proposed approach is appealing in terms of both detection power and false discovery rate. And the real data example also favored the likelihood-based approach in terms of the biological relevance of the results. AVAILABILITY: R code to implement the proposed method in the statistical package R is available at: http://odin.mdacc.tmc.edu/~jhhu/cod-analysis/.
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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.