Hi all,

Further to my last email, I've published a workflow (Bristol workflow ....) 
which does what I described below - hope this helps in understanding what I'm 
on about (!).

Best Wishes,
David.



On 23 Feb 2011, at 14:41, David Matthews wrote:

> Hi Jeremy,
> 
> I thought I'd write to get a discussion of a workflow for people doing RNA 
> seq that I have found very useful and addresses some issues in mapping mRNA 
> derived RNA-seq paired end data to the genome using tophat. Here is the 
> approach I use (I have a human mRNA sample deep sequenced with a 56bp paired 
> end read on an illumina generating 29 million reads):
> 
> 1. Align to hg19 (in my case) using tophat and allowing up to 40 hits for 
> each sequence read
> 2. In samtools filter for "read is unmapped", "mate is mapped" and "mate is 
> mapped in a proper pair"
> 3. Use "group" to group the filtered sam file on c1 (which is the 
> "bio-sequencer" read number) and set an operation to count on c1 as well. 
> This provides a list of the reads and how many times they map to the human 
> genome, because you have filtered the set for reads that have a mate pair 
> there will be an even number for each read. For most of the reads the number 
> will be 2 (indicating the forward read maps once and the reverse read maps 
> once and in a proper pair) but for reads that map ambiguously the number will 
> be multiples of 2. If you count these up I find that 18 million reads map 
> once, 1.3 million map twice, 400,000 reads map 3 times and so on until you 
> get down to 1 read mapping 30 times, 1 read mapping 31 times and so on...
> 4. Filter the reads to remove any reads that map more than 2 times.
> 5. Use "compare two datasets" to compare your new list of reads that map only 
> twice to pull out all the reads in your sam file that only map twice (i.e. 
> the mate pairs).
> 6. You'll need to sort the sam file before you can use it with other 
> applications like IGV.
> 
> What you end up with is a sam file where all the reads map to one site only 
> and all the reads map as a proper pair. This may seem similar to setting 
> tophat to ignore non-unique reads. However, it is not. This approach gives 
> you 10-15% more reads. I think it is because if tophat finds (for example) 
> that the forward read maps to one site but the reverse read maps to two sites 
> it throws away the whole read. By filtering the sam file to restrict it to 
> only those mappings that make sense you increase the number of unique reads 
> by getting rid of irrational mappings.
> 
> Has anyone else found this? Does this make sense to anyone else? Am I making 
> a huge mistake somewhere?
> 
> A nice aspect of this (or at least I think so!) is that by filtering in this 
> manner you can also create a sam file of non-unique mappings which you can 
> monitor. This can be useful if one or more genes has a problem of generating 
> a lot of non-unique maps which may give problems accurately estimating its 
> expression. Also, you also get a list of how many multi hits you have in your 
> data so you know the scale of the problem.
> 
> Best Wishes,
> David.
> 
> __________________________________
> Dr David A. Matthews
> 
> Senior Lecturer in Virology
> Room E49
> Department of Cellular and Molecular Medicine,
> School of Medical Sciences
> University Walk,
> University of Bristol
> Bristol.
> BS8 1TD
> U.K.
> 
> Tel. +44 117 3312058
> Fax. +44 117 3312091
> 
> d.a.matth...@bristol.ac.uk
> 
> 
> 
> 
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