Hi, I am learning how to use edgeR to analyze RNA-seq data generated from Illumina GAII. The experimental design is fairly complex. I have a mixed 4x2 factorial randomized complete block design (RCBD) consisting of: 4 tissues: A, B, C, D 2 treatments: control, stressed 3 blocks: Block1, Block2, Block3 Tissue and treatment are fixed effects and block is a random effect. Here is the code I tried to use in edgeR: > counts <- read.delim( file = "Mycounts.txt", header = TRUE) > rownames <-counts [ , 1 ] > d <- counts [, 2:25] # counts are in columns 2-25 > d > group <- c(rep("Control", 3), rep("Stress", 3), rep("Control", 3), rep("Stress", 3), rep("Control", 3), rep("Stress", 3), rep("Control", 3), rep("Stress", 3)) > d <- DGEList(counts = d, group = group) > design <- model.matrix(~group) > d <- calcNormFactors(d) > d$samples > d <- estimateGLMCommonDisp(d, design) > d <- estimateGLMTagwiseDisp(d, design) > d$common.dispersion > fit <- glmFit(d, design) > lrt <- glmLRT(d, fit, coef=2) > topTags(lrt, n=4) I am interested to know genes differentially expressed in each of the four tissues under stress. However, I feel like I am not specifying the factors correctly in the design statement. My questions are: 1) How do I specify the fixed effects Tissue, Stress, and Tissue*Stress interaction in the model? 2) How do I tell edgeR to use block as a random effect? 3) How do I obtain differentially expressed genes in each Tissue*Stress combination? I appreciate your help. Cheers. Tilahun Abebe, Ph.D. University of northern Iowa Cedar Falls, IA [[alternative HTML version deleted]]

Dear Tilahun, The first step is that you need to create a data frame containing the experimental factors, just as you would for a SAS analysis. So you need to create three factors: Tissue Treatment Block each containing 24 values, one for each RNA sample. Then the design marix is formed by: design <- model.matrix(~Tissue*Treatment+Block) Type colnames(design) to see how the coefficients are defined. You will see that the interaction coefficients are coefficients 6 to 8. After fitting your linear model, you could find genes that show significant Tissue*Treatment interaction (on 3df) by lrt <- glmLRT(d, fit, coef=6:8) and so on. I don't understand your question "How do I obtain differentially expressed genes in each Tissue*Stress combination?", so I can't give specific advice on that. Differentially expressed compared to what? Best wishes Gordon ---------------- original message ------------------- [BioC] Please help! How to specify factors for a RCBD in edgeR Tilahun Abebe tilahun.abebe at uni.edu Wed Jan 25 22:16:41 CET 2012 Hi, I am learning how to use edgeR to analyze RNA-seq data generated from Illumina GAII. The experimental design is fairly complex. I have a mixed 4x2 factorial randomized complete block design (RCBD) consisting of: 4 tissues: A, B, C, D 2 treatments: control, stressed 3 blocks: Block1, Block2, Block3 Tissue and treatment are fixed effects and block is a random effect. Here is the code I tried to use in edgeR: > counts <- read.delim( file = "Mycounts.txt", header = TRUE) > rownames <-counts [ , 1 ] > d <- counts [, 2:25] # counts are in columns 2-25 > d > group <- c(rep("Control", 3), rep("Stress", 3), rep("Control", 3), rep("Stress", 3), rep("Control", 3), rep("Stress", 3), rep("Control", 3), rep("Stress", 3)) > d <- DGEList(counts = d, group = group) > design <- model.matrix(~group) > d <- calcNormFactors(d) > d$samples > d <- estimateGLMCommonDisp(d, design) > d <- estimateGLMTagwiseDisp(d, design) > d$common.dispersion > fit <- glmFit(d, design) > lrt <- glmLRT(d, fit, coef=2) > topTags(lrt, n=4) I am interested to know genes differentially expressed in each of the four tissues under stress. However, I feel like I am not specifying the factors correctly in the design statement. My questions are: 1) How do I specify the fixed effects Tissue, Stress, and Tissue*Stress interaction in the model? 2) How do I tell edgeR to use block as a random effect? 3) How do I obtain differentially expressed genes in each Tissue*Stress combination? I appreciate your help. Cheers. Tilahun Abebe, Ph.D. University of northern Iowa Cedar Falls, IA ______________________________________________________________________ The information in this email is confidential and intend...{{dropped:4}}