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Bioinformatics 5890/6890
Project
Gene Expression
Characterization of inconsistency in the expression profiles
of genes in gene set testing.
Team Member Professor
Sanket Singhvi Dr. John R. Stevens
Hyoung-Il Oh
Chang-su Seo
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Project on Gene Expression - Topics in Computer Science | CS 5890, Study Guides, Projects, Research of Computer Science
Material Type: Project; Professor: Flann; Class: TOPICS: GAME DEVELOPMENT; Subject: Computer Science; University: Utah State University; Term: Unknown 2000;
Typology: Study Guides, Projects, Research
Pre 2010
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1
Bioinformatics 5890/
Project
Gene Expression
Characterization of inconsistency in the expression profiles
of genes in gene set testing.
Team Member Professor Sanket Singhvi Dr. John R. Stevens Hyoung-Il Oh Chang-su Seo
Background: ALL data
Acute Lymphoblastic Leukemia (Ritz lab)
12,625 genes
128 samples (arrays)
phenotypic data on all 128 patients, including:
95 B-cell cancer patients
33 T-cell cancer patients
R
Tool to analyse the Microarray Data.
First 2 Weeks
Test for the Differential Expression
Global Test
(^) performed on the set of 2000 Randomly selected Genes. (^) Outcome of Global Test: (^) P-Value for each GO Code. (^) Graph that shows the problem areas
Ebayes/Limma Test
(^) Ebayes/Limma Test is performed on the set of Gene. (^) Outcome (^) P-Values for all gene. (^) Different plots like Log Fold Change, histogram of P- Values, volcano plot.
Global Test Results
(^) P Values For Yellow Nodes < 0. Red Nodes 0.05 <=p< 0. Gray Nodes P >= 0. (^) Node A is subset of Node B and Node B is subset of Node C
Ebayes/Limma Test -- Plots
Work in Progress..
A Different approach for the analysis of P-Value.
Ebayes/Limma Test is performed on 12625
Genes.
(^) Results of test: (^) No. of significant Genes -- 3021 (^) No. of non-significant Genes -- 9604 (^) P-Values for each individual Gene.
Purpose of Current Work….
To find the answer of following question (^) What summaries of local test P-Values are closely related to Global test P-value. e.g. Mean, Median, Standard Deviation, Skewness etc. (^) Different trends for different values of N and proportion of significant gene? (^) What graphical Summaries most effectively communicate these results? (^) What variation on the sampling scheme might affect the results?
Work in Progress..
(^) We have tested for number of genes from 100 to 9000. Mean Plots N = 250 N = 500 N = 750 `
Work in Progress..
(^) Skewness Plots – Measure of Non-Symmetry N = 250 N = 500 N = 750 `
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Schedule / Remaining Tasks
Next 2 Weeks (week # 4-5)
(^) Run the simulation for the smaller number of Genes. (^) Instead of randomly selecting the genes, Select Genes using the Extreme Values of P-Value. (^) Write up for Poster.
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