Bioconductor in R with a expectation free dataset Transcriptomics - practical 2014.

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Presentation transcript:

Bioconductor in R with a expectation free dataset Transcriptomics - practical 2014

Please close unnecessary programs. On please go to practical 5. Analysing Transcriptome Data. 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 open the pptx

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?

Installing R / bioconductor This is easy from home or anywhere. – WAIT FOR THE DEMONSTRATION We will show you how to install as if you are in your own lab / house / coffee shop. All you need is a network connection

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

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)

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Box plots & normalisation

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

PCA – does my data look good in that?

Contrasts, top tables & differentials

If time permits: Venn diagrams