References for Microarray Data Analysis
NEW References for Microarray Data Analysis
PubH 5470-2 (Spring 2003)
http://www.biostat.umn.edu/~weip/course/ge/ref02s.html
- Introduction to microarray technologies
- Yeoh E et al. (2002). Classification, subtype discovery, and prediction
of outcome in pediatric acute lymphoblastic leukemia by gene
expression profiling. Cancer Cell, 1:133-143.
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- Measuring gene expression levels
- Affymetrix (2002). Statistical algorithms description document.
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- WJ Lemon, J.J.T. Palatini, R Krahe and
FA Wright (2002).
Theoretical and experimental comparisons of gene expression indexes
for oligonucleotide arrays.
Bioinformatics, 18: 1470-1476.
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- Irizarry RA et al. (2003). Summaries of Affymetrix GeneChip probe
level data. Nucleic Acids Research, 31: e15.
PDF
- Irizarry, RA, Hobbs, B, Collin, F, Beazer-Barclay, YD,
Antonellis, KJ, Scherf, U, Speed, TP (2003b)
Exploration, Normalization, and Summaries of
High Density Oligonucleotide Array Probe Level Data.
Accepted for publication in Biostatistics.
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- Y Zhou and R Abagyan (2002). Match-only integral distribution (MOID)
algorithm for high-density oligonucleotide array analysis.
BMC Bioinformatics, 3:3.
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- Kooperberg C et al. (2002). Improved background correction for
spotted DNA microarraya. J of Computational Biology,
9: 55-66.
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- Data normalization
- Quackenbush J (2002). Microarray data normalization and
transformation. Nature Genetics Supplement, 32, 496-501.
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(This is a review article containing other references.)
- Y. H. Yang, S. Dudoit, P. Luu and T. P. Speed (2001).
Normalization for cDNA Microarray Data. SPIE BiOS 2001, San
Jose, California, January 2001.
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- George C. Tseng, Min-Kyu Oh, Lars Rohlin, James C. Liao and
Wing Hung Wong (2001). Issues in cDNA
microarray analysis: quality filtering, channel normalization,
models of variation and assessment of
gene effects. Nucleic Acids Research, Vol 29, No. 12. 2549-2557.
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- Eric E. Schadt, Cheng Li, Byron Ellis and Wing H. Wong (2001).
Feature extraction and normalization algorithms for high-density
oligonucleotide gene expression array data.
Journal of Cellular Biochemistry. Supplement 37, 120-125.
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- Eric E. Schadt, Cheng Li, Cheng Su, Wing H. Wong (2000).
Analyzing high-density oligonucleotide gene expression array data.
Journal of Cellular Biochemistry. 80, 192-202.
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- Bolstad, B.M., Irizarry RA, Astrand, M, and Speed, TP (2003).
A Comparison of Normalization Methods for High Density Oligonucleotide
Array Data Based on Bias and Variance.
Bioinformatics>/I>. 19(2):185-193.
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- Durbin, B.P., Hardin, J.S., Hawkins, D.M. and Rocke, D.M. (2002).
A variance-stabilizing transformation for gene-expression microarray
data. Bioinformatics, 18, S105-S110.
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- Detecting differentially expressed genes
- Kendziorski, C.M., M.A. Newton, H. Lan, and M.N. Gould (2003).
On parametric empirical Bayes methods for comparing multiple groups using
replicated gene expression profiles. Technical Report #166,
Department of Biostatistics and Medical Informatics,
University of Wisconsin - Madison.
Statistics in Medicine (in press).
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- M.A. Newton , A. Noueiry, D. Sarkar, and P. Ahlquist (2003). Detecting
differential gene expression with a semiparametric hierarchical mixture
method. Technical Report #1074, Department of Statistics, UW Madison.
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- Cluster analysis
- McShane LM, Radmacher MD, Freidlin B, Yu R, Li M-C and Simon R (2002).
Methods for assessing reproducibility of clustering patterns observed
in analysis of microarray data.
Bioinformatics, 18, 1462-1469.
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- Tibshirani R, Walther G and Hastie T (2001).
Estimating the number of clusters in a data set via the gap statistic.
JRSS-B, 63, 411-423.
- Dudoit, S. and J. Fridlyand (2002). A prediction-based resampling method
to estimate the number of clusters in a dataset.
Genome Biology, 3(7), research0036.1 -- 0036.21.
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- Classification
- Tibshirani, Hastie, Narasimhan and Chu (2002).
Diagnosis of multiple cancer types by shrunken centroids of gene
expression.
PNAS, 99:6567-6572 (May 14).
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