Presentation is loading. Please wait.

Presentation is loading. Please wait.

Bioconductor in R with a expectation free dataset Transcriptomics - practical 2012.

Similar presentations


Presentation on theme: "Bioconductor in R with a expectation free dataset Transcriptomics - practical 2012."— Presentation transcript:

1 Bioconductor in R with a expectation free dataset Transcriptomics - practical 2012

2 Please close unnecessary programs. On Choose the ‘Introduction to R/Bioconductor Practical 5’ link Open the Free Transcriptomic Practical link and download the pptx to your DESKTOP **we will fill out this pptx TOGETHER** Download the data files zip folder Unzip to your DESKTOP Download the All Packages zip folder Unzip to your DESKTOP open the pptx

3 Experimental setup Equivalency? - fair representatives? (G/E) Replicates? - ease, cost Suitability of samples? -which tissue? Degradation? - is the tissue normal? - how has it been stored? All determine the TYPE of experiment you are doing While you are doing this analysis – think.. What am I finding out? Why?

4 Installing R / bioconductor This is easy from home, but can be a little tricky from UoN – WAIT FOR THE DEMONSTRATION To save time we are using pre-installed R Start> All Program's> UoN software> Statistical & Mathematical> R - At home – follow the notes below.

5 Expression Probes on a GeneChip Probes Sequence Perfect Match Mismatch Chip 5’ 3’

6 Procedures for Target Preparation cDNA Wash & Stain Scan Hybridise (16 hours) RNA AAAA BBBB Biotin-labeled transcripts Fragment (heat, Mg 2+ ) Fragmented cRNA B B B B IVT (Biotin-UTP Biotin-CTP)

7 GeneChip ® Expression Analysis Hybridization and Staining Array cRNA Target Hybridized Array Ab detection

8 Installing Bioconductor / oneChannelGUI normally WAIT FOR THE DEMONSTRATION DON’T DO THIS NOW

9 Experimental design and RNA tables Biological replicates from separate tissue samples

10 Box plots & normalisation

11 RMA uses Quantile normalisation at the probe level Chip 1 Chip 2 Chip Order by ranks PA PB PC PD PE Chip 1 Chip 2 Chip Average the intensities at each rank Chip 1 Chip 2 Chip PA PB PC PD PE Chip 1 Chip 2 Chip Reorder by probe

12 PCA – does my data look good in that?

13 Contrasts, top tables & differentials

14 If time permits: Venn diagrams


Download ppt "Bioconductor in R with a expectation free dataset Transcriptomics - practical 2012."

Similar presentations


Ads by Google