Patterns from Gene Expression

eagle-i ID

Resource Type

Properties

1. Resource Description

   "PaGE can be used to produce sets of differentially expressed genes with confidence measures attached. These lists are generated the False Discovery Rate method of controlling the false positives. But PaGE is more than a differential expression analysis tool. PaGE is a tool to attach descriptive , dependable, and easily interpretable expression patterns to genes across multiple conditions, each represented by a set of replicated array experiments. The input consists of (replicated) intensities from a collection of array experiments from two or more conditions (or from a collection of direct comparisons on 2-channel arrays). The output consists of patterns, one for each row identifier in the data file. One condition is used as a reference to which the other types are compared. The length of a pattern equals the number of non-reference sample types. The symbols in the patterns are integers, where positive integers represent up-regulation as compared to the reference sample type and negative integers represent down-regulation. The patterns are based on the false discovery rates for each position in the pattern, so that the number of positive and negative symbols that appear in each position of the pattern is as descriptive as the data variability allows. The patterns generated are easily interpretable in that integers are used to represent different levels of up- or down-regulation as compared to the reference sample type."

2. Additional Name

   PaGE

3. Used by

   Computational Biology and Informatics Laboratory

4. Version

   5.1

5. Data Input

   Gene expression intensities

6. Data Output

   Gene expression patterns

7. Software purpose

   Differential expression analysis objective

8. Related Publication or Documentation

   A practical false discovery rate approach to identifying patterns of differential expression in microarray data

9. Website(s)

   http://www.cbil.upenn.edu/PaGE/

10. Related Technique

    Data analysis

11. Related Technique

    RNA sequencing

12. Related Technique

    MeDIP-SEQ assay

13. Related Technique

    ChIP-seq assay

14. Developed by

    Grant, Gregory R., Ph.D.

15. Developed by

    Manduchi, Elisabetta, Ph.D.

16. Algorithm used

    Multiple testing

17. Coded in

    Java

18. Coded in

    Perl