Significance analysis of microarrays applied to the ionizing radiation response. Presented by Wenlei Liu Department of Health Evaluation Sciences September 19, 2004. Goal. Differential Analysis of Microarray data :
Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.
Presented by Wenlei Liu
Department of Health Evaluation Sciences
September 19, 2004
Differential Analysis of Microarray data :
Individually identifying genes differentially expressed between two conditions
Study the transcriptional response of lymphoblastoid cells to ionizing radiation (IR).
Two cell lines (1 & 2) were used. Allow cell lines to grow in unirradiated state (U) or in an irradiated state (I) 4 hours after exposure to a modest dose of 5 Gy of ionizing radiation (IR). Divide RNA samples into two parts and performed two independent hybridizations, A and B.
Eight chips– U1A, U1B, U2A, U2B,
I1A, I1B, I2A, I2B.
Compare SAM with
Fold change method –
gene (i) is significant if r(i) > R or < 1/R
Pairwise fold change –compute pairwise fold change using four data sets in state U and state I. A gene is significant if 12 of 16 pairings satisfied the above criteria.
Errors in the Biopsy Diagnosis of Cancer can lead to:
C(x) = k, where
xij denotes the expression of genes i=1, 2, …, p and samples j=1, 2, ..n. k indexes the cancer classes.
Shrink each dik towards zero, giving dik’ and new shrunken centroids
For gene i, if dik’=0 for all k, then for all k. Gene i does not contribute to the nearest centroid computation.
was chosen by cross-validation.
For a test sample with expression levels
The discriminant score for class k
where k is the prior probability of class k and k=1. And
Small round blue cell tumors (SRBCT) of childhood.
1 2 3 4 5 6 7 8 9 10