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With any RNA-seq data, you're almost always going to get rRNA contamination. It makes subsequent mapping quicker if you filter out the rRNA reads first (i.e. prior to any other mapping that is done). -
To all,
I discovered my problem with my RNA-seq data. It looks like there was some rRNA contamination in my sample which accounted for 5% of the total reads in the sample. The rRNA genes are located on chromosome 9. There are also some regions on chromosome 2 that show high homology to the rRNA genes on chromosome 9. This is the cause of the reads overloading chromosomes 9 and 2.
The latest version of Tophat works fine.
If other people are having problems with reads overloading a chromosome, check to see if there is rRNA contamination.
Thanks all.Leave a comment:
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More problems with Tophat (v1.3.2)
I ran tophat version 1.3.2 to align my deep sequencing data to my reference genome via the following command
tophat --solexa1.3-quals –p 6 –o /control/8905X1/tophat /rice_index/rice_index /8905X1/8905X1.txt
It generated a file called accepted_hits.bam.
I converted the file to a bed file using the bamToBed tool.
Then split the file up based on chromosomes. Here are the results:
331723028 May 11 09:26 accepted_hits_bed_Chr1
119325730 May 11 09:26 accepted_hits_bed_Chr10
123994839 May 11 09:26 accepted_hits_bed_Chr11
121898474 May 11 09:27 accepted_hits_bed_Chr12
416137943 May 11 09:27 accepted_hits_bed_Chr2
334052893 May 11 09:27 accepted_hits_bed_Chr3
161529836 May 11 09:27 accepted_hits_bed_Chr4
347228298 May 11 09:28 accepted_hits_bed_Chr5
189465060 May 11 09:28 accepted_hits_bed_Chr6
200695493 May 11 09:28 accepted_hits_bed_Chr7
171194241 May 11 09:28 accepted_hits_bed_Chr8
759976461 May 11 09:29 accepted_hits_bed_Chr9
2184791 May 11 09:29 accepted_hits_bed_ChrSy
539606 May 11 09:29 accepted_hits_bed_ChrUn
Tophat overloaded chromosome 9 which is one of the smaller chromosomes.
Unless this can be resolved, I recommend not using Tophat.
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