Identifying expression trends in RNA-seq experiment - through edgeR
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@sandhya-pemmasani-kiran-5878
Last seen 5.5 years ago
India
Hi all, We have data from RNA-seq experiment conducted on two siRNA knockdowns. Three conditions - Control, si1 and si2. Four doses - D0, D1, D2 and D3. There were no replicates. Total 12 samples. We are trying to use edgeR to identify differentially regulated genes. Since edgeR doesn't give p-values without replicates, we took samples coming from D0 as replicates i.e. Control-D0, si1-Do and si2-D0 (This decision was taken based on our analysis with DE-seq. We didn't get any DE genes from 'Control-D0 vs. si1-D0' and 'Control-D0 vs. si2-D0'). After building the model, we performed pair-wise comparisons between Control and experimental conditions at each dose, excluding D0, and identified overlapping genes. Now, we want to see the genes that have increasing or decreasing trends across the doses i.e. the genes should not have significant differences in Controls, but should show a trend in experimental conditions. For this, we have used two sets of contrasts- control.contrasts <- makeContrasts( Ctrl_2vs1 = (Ctrl_D2 - Ctrl_D1), Ctrl_3vs2 = (Ctrl_D3- Ctrl_D2), Ctrl_3vs1 = (Ctrl_D3- Ctrl_D1), levels = design) si.contrasts <- makeContrasts( si_2vs1 = (si_D2 - si_D1), si_3vs12 = (si_D3 - 0.5*si_D2 - 0.5*si_D1), levels = design) # idea taken from contr.helmert lrt.Ctrl <- glmLRT(fit, contrast = control.contrasts) lrt.si <- glmLRT(fit, contrast = si.contrasts) We have taken genes that were not significant in lrt.Ctrl, but significant in lrt.si. Further filtered the genes based on fold changes from si.contrasts to get genes with upward/downward trends. Are we doing it correctly? Is there an easy way of doing it that we are missing. Please let me know your suggestions. Thanks Sandhya ________________________________ This e-mail contains PRIVILEGED AND CONFIDENTIAL INFORMATION intended solely for the use of the addressee(s). If you are not the intended recipient, please notify the sender by e-mail and delete the original message. Further, you are not to copy, disclose, or distribute this e-mail or its contents to any other person and any such actions that are unlawful. This e-mail may contain viruses. Ocimum Biosolutions has taken every reasonable precaution to minimize this risk, but is not liable for any damage you may sustain as a result of any virus in this e-mail. You should carry out your own virus checks before opening the e-mail or attachment. The information contained in this email and any attachments is confidential and may be subject to copyright or other intellectual property protection. If you are not the intended recipient, you are not authorized to use or disclose this information, and we request that you notify us by reply mail or telephone and delete the original message from your mail system. OCIMUMBIO SOLUTIONS (P) LTD [[alternative HTML version deleted]]
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