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Old 06-15-2014, 04:28 AM   #1
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Location: Australia

Join Date: Jun 2014
Posts: 3
Default Trouble with EdgeR


A bit of background info. I am using the Trinity/ RSEM/EdgeR pipeline. I have 9 samples in total (3 conditions over 3 time points -NO REPLICATES - I know it's not been ideal).

I have ran the following pipeline:

(I ran the No reps option for EdgeR).

Now I am all rather new to this so please be as explanative as possible.

I have carried out D.E.G expression between all of the samples and produced heat maps and output files ".DE.results" for all the comparisons I deemed suitable. I now want to be able to produce an MDSplot using EdgeR to compare the similarities between all 9 samples to see the similarity.

I have R studio with all the much needed modules loaded. My data looks like this when loaded( see attachment image). Can someone please,please tell me how to create a suitable MDS plot.. I have attached my data file, however when I type "plotMDS(y)" it says 'too few many rows'... as you have guessed..I am a newbie with R too. How do I go about producing a suitable plot? Can someone please get me started? I have looked at the EdgeR manual,but I can't make much sense as i have completed the process automated, I am only wanting to produce graphical plots. It seems the only plot that came from EdgeR was the heatmap.pdf, is this normal?

One more question, I have done genes as well as isoforms. I couldn't carry out GO annotation etc on the genes themselves,but for the isoforms I can carry this out. Is it fine to go with the isoforms for D.G.E and functional annotation? I can only extract the isoforms(transcripts) from the Trinity.fasta file produced from the transcriptome assemblage. Is this method correct?

Many thanks.

Last edited by PAD25; 06-18-2014 at 09:19 PM.
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Old 06-15-2014, 04:46 AM   #2
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Location: Australia

Join Date: Jun 2014
Posts: 3


OK, bit of an update... me being a newbie :/ I removed the ID column in Excel and saved the file and entered it back into R, I've attached and now can do the MDSplot function. I want to now ask, What is the best statistical principle to apply to the data?

Bear in mind I have NO REPLICATES...
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