Online citations, reference lists, and bibliographies.
Please confirm you are human
(Sign Up for free to never see this)
← Back to Search

Diagnosis Of Multiple Cancer Types By Shrunken Centroids Of Gene Expression

R. Tibshirani, T. Hastie, B. Narasimhan, G. Chu
Published 2002 · Medicine, Biology

Save to my Library
Download PDF
Analyze on Scholarcy
Share
We have devised an approach to cancer class prediction from gene expression profiling, based on an enhancement of the simple nearest prototype (centroid) classifier. We shrink the prototypes and hence obtain a classifier that is often more accurate than competing methods. Our method of “nearest shrunken centroids” identifies subsets of genes that best characterize each class. The technique is general and can be used in many other classification problems. To demonstrate its effectiveness, we show that the method was highly efficient in finding genes for classifying small round blue cell tumors and leukemias.
This paper references
10.1097/00019606-199802000-00007
Neuroendocrine Differentiation in Ewing's Sarcomas and Primitive Neuroectodermal Tumors Revealed by Reverse Transcriptase‐Polymerase Chain Reaction of Chromogranin mRNA
A. Pagani (1998)
10.1073/pnas.091062498
Significance analysis of microarrays applied to the ionizing radiation response
V. G. Tusher (2001)
10.1093/emboj/20.6.1383
N‐myc enhances the expression of a large set of genes functioning in ribosome biogenesis and protein synthesis
K. Boon (2001)
10.1097/00000478-200012000-00010
Immunohistochemical Detection of FLI-1 Protein Expression: A Study of 132 Round Cell Tumors With Emphasis on CD99-Positive Mimics of Ewing's Sarcoma/Primitive Neuroectodermal Tumor
A. Folpe (2000)
10.1198/jasa.2004.s339
The Elements of Statistical Learning: Data Mining, Inference, and Prediction
D. Ruppert (2004)
10.1126/SCIENCE.286.5439.531
Molecular classification of cancer: class discovery and class prediction by gene expression monitoring.
T. Golub (1999)
10.1056/NEJM200102223440801
Gene-expression profiles in hereditary breast cancer.
I. Hedenfalk (2001)
10.1073/PNAS.95.25.14863
Cluster analysis and display of genome-wide expression patterns.
M. Eisen (1998)
10.1002/SIM.1616
The Elements of Statistical Learning, Data Mining, Inference, and Prediction. Trevor Hastie, Robert Tibshirani and Jerome Friedman, Springer, New York, 2001. No. of pages: xvi+533. ISBN 0‐387‐95284‐5
H. C. Houwelingen (2004)
10.1093/BIOMET/81.3.425
Ideal spatial adaptation by wavelet shrinkage
D. Donoho (1994)
Overexpression of the pseudoautosomal gene MIC2 in Ewing's sarcoma and peripheral primitive neuroectodermal tumor.
H. Kovar (1990)
Desmin is a specific marker for rhabdomyosarcomas of human and rat origin.
M. Altmannsberger (1985)
10.1038/89044
Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks
J. Khan (2001)
Expression of myogenic regulatory proteins (myogenin and MyoD1) in small blue round cell tumors of childhood.
N. Wang (1995)
10.1054/bjoc.2001.2008
Detection of the PAX3-FKHR fusion gene in paediatric rhabdomyosarcoma: a reproducible predictor of outcome?
J. Anderson (2001)



This paper is referenced by
10.1002/sam.11367
Sparse Fisher's linear discriminant analysis for partially labeled data
Qiyi Lu (2018)
10.1186/1471-2105-13-298
Improving accuracy for cancer classification with a new algorithm for genes selection
H. Zhang (2012)
10.1016/j.patrec.2005.09.028
Feature selection in robust clustering based on Laplace mixture
Aurélien Cord (2006)
10.1074/mcp.R800007-MCP200
The Role of Proteomics in Clinical Cardiovascular Biomarker Discovery*
A. V. Edwards (2008)
10.1089/aid.2008.0059
CD4+ T-cell decline after the interruption of antiretroviral therapy in ACTG A5170 is predicted by differential expression of genes in the ras signaling pathway.
M. Vahey (2008)
10.1186/bcr2472
Gene expression profiling of peripheral blood cells for early detection of breast cancer
J. Aarøe (2009)
Bayesian Model Averaging for Biomarker Discovery From Genome-Wide Microarray Data
K. Yeung (2010)
Molecular Bases of Disease
Y. Kang (2013)
10.1007/s10115-015-0878-8
Faster and more accurate classification of time series by exploiting a novel dynamic time warping averaging algorithm
F. Petitjean (2015)
10.1371/journal.pone.0066574
A Molecular Predictor Reassesses Classification of Human Grade II/III Gliomas
T. Rème (2013)
10.1109/BIBE.2006.253330
Learning the Tree of Phenotypes Using Genomic Data and VISDA
Yuanjian Feng (2006)
10.1530/ERC-10-0235
Decreased progesterone receptor isoform expression in luteal phase fallopian tube epithelium and high-grade serous carcinoma
A. Tone (2011)
10.1007/978-3-642-12159-3_7
Robustness Analysis of Eleven Linear Classifiers in Extremely High-Dimensional Feature Spaces
L. Lausser (2010)
10.1101/2020.05.27.118471
Pharmacologically modified pluripotent stem cell-based cancer vaccines with anti-metastatic potential
Masae Heront-Kishi (2020)
10.1111/RSSB.12326
High-dimensional Linear Discriminant Analysis: Optimality, Adaptive Algorithm, and Missing Data
T. Cai (2018)
10.5705/SS.202016.0117
Multiclass Sparse Discriminant Analysis
Qing Mai (2015)
10.1038/s41591-018-0323-0
Deciphering the genomic, epigenomic, and transcriptomic landscapes of pre-invasive lung cancer lesions
V. Teixeira (2019)
10.1186/s12920-016-0169-6
Cancer survival analysis using semi-supervised learning method based on Cox and AFT models with L1/2 regularization
Yong Liang (2016)
10.1109/ICCV.2019.00042
Few-Shot Learning With Embedded Class Models and Shot-Free Meta Training
A. Ravichandran (2019)
10.2147/OTT.S144015
Prognostic immune-related gene models for breast cancer: a pooled analysis
Jian-li Zhao (2017)
10.1002/9781119183952.CH11
Statistical Inference in High‐Dimensional Omics Data
Eleni‐Ioanna Delatola (2018)
Assessment of five microarray experiments on gene expression profiling of breast cancer
J. Toedling (2003)
10.1023/B:JOMG.0000010035.57912.5a
Statistical Issues in the Design and Analysis of Gene Expression Microarray Studies of Animal Models
L. McShane (2004)
10.1186/1471-2105-6-195
Sample phenotype clusters in high-density oligonucleotide microarray data sets are revealed using Isomap, a nonlinear algorithm
K. Dawson (2004)
Differential Friendly Neighbors Algorithm for Differential Relationships Based Gene Selection and Classification using Microarray Data
K. R. K. Murthy (2006)
10.1016/J.HLC.2007.06.199
Beta 2 Microglobulin as a Biomarker in Peripheral Arterial Disease: Proteomic Profiling and Clinical Studies
Andrew M. Wilson (2007)
10.1016/b978-012373698-7/50015-2
Molecular Analysis of Heart Failure and Remodeling
J. Marín-García (2007)
10.5351/CKSS.2009.16.3.397
Developing a Parametric Method for Testing the Significance of Gene Sets in Microarray Data Analysis
S. Lee (2009)
AN INTEGRATIVE COMPUTATIONAL FRAMEWORK FOR DEFINING ASTHMA ENDOTYPES
Judie A. Howrylak (2013)
10.1007/978-94-007-5842-1_17
Genome-Wide Analysis and Gene Expression Profiling of Neuroblastoma: What Contribution Did They Give to the Tumor Treatment?
Gian Paolo Tonini (2013)
Variable Screening Methods in Multi-Category Problems for Ultra-High Dimensional Data
Yue Zeng (2017)
10.3929/ETHZ-A-010286839
Multiclass cancer classfication and gene selection using mutation information
Kee Pang Soh (2014)
See more
Semantic Scholar Logo Some data provided by SemanticScholar