Entering edit mode
7.5 years ago
seta
★
1.9k
Hi all,
I did de novo transcriptome assembly using paired-end reads from Illumina Hiseq 2000 for a non-model organism. I mapped back reads to transcriptome assembly. If I'm not wrong, the average of mapping coverage shows the read number (in average) that mapped to each reconstructed transcript (contig). Could you please let me know if this number is important and why? and how I can calculate it?
Thank you for your answer
From Biostar Handbook. Genome/Chromosome size in your case will be the size of the contigs.
Are you sure? As I found on the net, the people used bedtools for it, however, I'm not sure about mapping read to de novo assembled transcriptome? Any suggestion
If the newly assembled transcriptome is your "reference" then that is what you have. You would expect a large % of the original reads to map to this new reference/transcriptome (if they don't then you probably have a bad assembly or some other issue). So unless you have a real reference available you can calculate coverage taking into account the contigs you now have in the new assembly.
Thank you. I found this paper enter link description here and more confused with reading the "Transcript quantitation, coverage and depth analysis" section. Sorry, could you please kindly tell me what is the story and the importance of this calculation (coverage and depth analysis)?
How to calculate can be easily found in the manual @genomax2 post,
more can be found here
How To Calculate Coverage
Tools To Calculate Average Coverage For A Bam File?
regarding why if you have wrong assembly they will not map right
Thank you. I read the post that you mentioned before posting the question here, however, there were lots of options so I'm confused as this is my first experience. Regarding why, I know high mapping percentage, especially proper read mapping for PE reads, is indicative of a good assembly, but, my mean is which concept can be extracted from this number (average of mapping coverage)?
I think for me bedtools or GATK DepthOfCoverage will do the job for you