Statistical Analysis of Microarray Data

Statistical Analysis of Microarray Data

--Our related work and other interesting sites!

News!

Pan, W. (2002) ``A Comparative Review of Statistical Methods for Discovering Differentially Expressed Genes in Replicated Microarray Experiments". Bioinformatics, 12, 546-554.
This paper is selected as a Fast Breaking Paper in computer science by ISI on Dec 1, 2003, and as one of Hot Papers that are most accessed during the last 5 years in the journal Bioinformatics.

Consulting with microarray data analysis

If you need help with experimental design and data analysis with microarray data, please contact me:

Wei Pan, PhD
Division of Biostatistics, School of Public Health, University of Minnesota
A460 Mayo Building, MMC 303, Minneapolis, MN 55455

Phone: (612)626-2705 (Office); Fax: (612)626-0660
E-mail: weip@biostat.umn.edu

Meetings related with microarray data analysis

  1. Annual Bioinformatics Symposium 2005 at University of Minnesota, April 15, 2005.
  2. Craybill Bioinformatics Conference at Colorado State University, June 2003.
  3. 3-Day Workshop on Statistical Analysis of Gene Expression Data, July 11-14 2003, Wye College Conference Center, Kent, UK. Organised by Sylvia Richardson (Imperial College) and Phil Brown (University of Kent)

Research related with microarray data analysis

  1. Huang, X. and Pan, W. (2003). "Linear regression and two-class classification with gene expression data" A shortened version appeared in Bioinformatics, 19, 2072-2078. PDF reprint. (Also Research Report 2003-005, Division of Biostatistics, University of Minnesota)
  2. Guo, X., Qi, H., Verfaillie, C.M. and Pan, W. (2003). ``Statistical significance analysis of longitudinal gene expression data". Bioinformatics, 19, 1628-1635. PDF reprint. (Also Report 2003-001, Division of Biostatistics, University of Minnesota, 2003)
  3. Pan, W. (2003). ``On the use of permutation in and the performance of a class of nonparametric methods to detect differential gene expression". A shortened version appeared in Bioinformatics, 19, 1333-1340. PDF reprint. (Also Report 2002-021, Division of Biostatistics, University of Minnesota, 2002)
  4. Zhao, Y. and Pan, W. (2002). ``Modified nonparametric approaches to detecting differentially expressed genes in replicated microarray experiments". A shortened version to appear in Bioinformatics. nn(Also Report 2002-018, Division of Biostatistics, University of Minnesota, 2002)
  5. Huang, X. and Pan, W. (2002) ``Comparing three methods for variance estimation with duplicated high density oligonucleotide arrays". Functional & Integrative Genomics, 2, 126-133. (Also Report 2002-014, Division of Biostatistics, University of Minnesota, 2002)
  6. Pan, W. (2002) ``A Comparative Review of Statistical Methods for Discovering Differentially Expressed Genes in Replicated Microarray Experiments". Bioinformatics, 12, 546-554. pdf. (Also Report 2001-028, Division of Biostatistics, University of Minnesota, 2001)
    News: This paper is selected as a Fast Breaking Paper in computer science by ISI on Dec 1, 2003, and a Hot Paper by Bioinformatics.
  7. Pan, W., Lin, J. and Le, C. (2002) ``How Many Replicates of Arrays Are Required to Detect Gene Expression Changes in Microarray Experiments? A Mixture Model Approach". (Also Report 2001-012, Division of Biostatistics, University of Minnesota, 2001) ----NEW: issued July 5, 2001; revised Feb 2002 GenomeBiology, /2002/3/5/research/0022. .
    Sample Splus program
  8. Pan, W., Lin, J. and Le, C. (2001) ``A Mixture Model Approach to Detecting Differentially Expressed Genes with Microarray Data". (Also Report 2001-011, Division of Biostatistics, University of Minnesota, 2001) Replaced by a much updated revision, Report 2003-004, Functional & Integrative Genomics, 3, 117-124.
  9. Pan, W., Lin, J. and Le, C. (2002) ``Model-Based Cluster Analysis of Microarray Gene Expression Data". (First issued Feb 2001; revised Nov 2001). (Also Report 2001-027, Division of Biostatistics, University of Minnesota, 2001)
    GenomeBiology, /2002/3/2/research/0009.
  11. Rat data

Teaching related with microarray data analysis

Cavan Reilly, Hegang Chen and I have developed a new statistical genetics/genomics course, PubH 5470 Section 2 (pdf of syllabus), scheduled for Spring 2002. It contains three topics, linkage analysis, sequence alighnment and analysis of microarray data. I am covering the part for microarray data. Here is a required/recommended reading list for microarray data.
A more complete reference list is given by Brian Yandell at UW-Madison.

"Bioinformatics needs to adopt statistical thinking!"

Some links

  1. Biomedical Genomics Center at U of M.
  2. Computational Biology Centers at U of M.
  3. Supercomputing Institute at U of M.
  5. Speed's group at Berkeley (with pointers to many statisticians working on the subject).
  6. Tibshirani at Stanford (manuscripts, SAM,...)
  7. Wing Hung Wong and his Lab at Harvard (manuscripts, software,...)
  8. George M Church's Lab at Harvard (manuscripts, software,...)
  9. Richard Young's Lab at MIT (manuscripts, data...)
  11. Rockefeller U (many interesting stuffs, including a very comprehensive list of references related to microarray data analysis, some of which are available online).
  13. The Stanford Microarray Database (with many online reprints and datasets).
  14. Whitehead/MIT group (with some online reprints and datasets).
  15. BRB at NCI.
  16. Genomics and Bioinformatics Group at NCI.
  17. NHGRI site.
  18. CS 8980, Computational Techniques for Genomics, at UofM (covering gene expression data and many other topics related to bio-computing).
  19. A seminar course (with a good list of relevant references to the subject).
  20. More links
  21. Rockefeller U: W Li maintains many many interesting stuffs...
  22. CAMDA: A conference/contest on assessing proposed methods using a common data set.