Even looking at single exons which are very large (6kb), I can see there is a bit of 3' bias. Is this something to be concerned about for downstream quantitation? I have seen several papers where they look at coverage across entire transcripts and it appears to be mostly-uniform-- not so here. I attached an image of the probe trend plot for all exons > 6kb.
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Directional RNA-Seq for bacterial transcriptome analysis...
Hi guys,
I am particularly interested on directional RNA-seq to be determined by means of RNA-seq and Illumina HiSeq 2000. Same authors (like N.Croucher of Sanger) already mentioned few approaches but I am wondering if anyone already tested them with bacterial totRNA. In particular I am looking at protocols suggested for ribosomal RNA depletion, RNA fragmentation and retro-transcription. Could you be so gentle to help me?
Thanks in advance
Best
SC
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This type of bias (as well as sequence-specific bias) is corrected for in Cufflinks. The importance of doing this correction is detailed in our paper here: http://genomebiology.com/2011/12/3/R22/
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Originally posted by kalidaemon View PostI'm also trying to visualize/correct for potential 3' bias in my RNA-Seq data-set and want to try Seqmonk. The problem is that I can't get it to run off my PC which has a Windows XP operating system. Have other people run into this problem? What have you done to fix it?
- You don't have java installed (or it's not been added to your path)
- You have less than 2GB RAM in your machine
If you don't have java installed then just get the latest version from java.com and install it.
If you have less than 2GB RAM in your machine then you'll need to lower the default memory allocation in the configuration which is shipped with SeqMonk. Instructions for how to do this can be found here.
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Originally posted by censinis View PostHi guys,
I am particularly interested on directional RNA-seq to be determined by means of RNA-seq and Illumina HiSeq 2000. Same authors (like N.Croucher of Sanger) already mentioned few approaches but I am wondering if anyone already tested them with bacterial totRNA. In particular I am looking at protocols suggested for ribosomal RNA depletion, RNA fragmentation and retro-transcription. Could you be so gentle to help me?
Thanks in advance
Best
SC
- a paper
- a guide
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Originally posted by simonandrews View PostRory - glad to hear you're liking SeqMonk!
If you've put probes over mRNA features and then done a trend plot then the peak you see at the end might not be due to true 3' bias.
Different transcripts will have exons at different places along their length. Therefore the trend plot for any individual transcript will go up and down as you pass in and out of an exon. If you average over all transcripts then you'll see the combined signals from all of the transcripts doing this which will even itself out for the most part - however the only places you're guaranteed to be in an exon are at the beginning and end of each transcript, so a trend plot over all transcripts will probably show a peak at each end because of the higher probability of being in an exon. Since 3' exons are generally larger than 5' exons you'll probably also see a bigger peak at the 3' end.
What you'd need for a true view of the trend over a spliced transcript would be to concatenate the exons for each transcript together and do a trend plot over those - missing out the introns. This could actually be a good addition to the program so I'll look at adding that in the a future release.
This same problem wouldn't apply to trend plots over exons where you would expect the signal from the reads to be continuous.
hi, has this option been added yet? I'd also be interested in using it... or would it be possible to have the transcriptome instead of the genome as a reference to remove the up and downs?
or can anyone else help me on how to visualize a 3'/5' bias in my data?
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Originally posted by NeleZ View Post@simonandrews
hi, has this option been added yet? I'd also be interested in using it... or would it be possible to have the transcriptome instead of the genome as a reference to remove the up and downs?
or can anyone else help me on how to visualize a 3'/5' bias in my data?
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