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Which Denovo Assembler To Use For Meta-Transcriptomic Data

Hi,

I have couple of questions.

Firstly, I am looking for a denovo assembly tool that can assemble a meta-transcriptome data(paired-end sequence(insert size=300) **consists of mixed sequence reads of multiple species in a microbial community,sequenced using Illumina Genome analyser.I have few number of libraries each holds from ~700,00 to 17million reads.

And in search of that I came across a METAVELVET, a de novo metagenome assembly and I am not sure whether this works well with my data?

Secondly,I used SORTMERNA tool,to detect and remove rRNA's from the same data(whole library) mentioned above and the output was,

file1:- non-rRNA's

file2:- rRNA's

i.e., total percent of rRNA it could find is 54.65% and non-rRNA 45.35%,but when I checked file1(interested for my work) many rRNA's were detected which means the tool misclassified rRNA's as nonrRNA's(got to know by doing blastx)then I repeated the process again but this time not on the whole data library instead only on non-rRNA output (file1) generated after applying SORTMERNA on complete data library.This time it again classified data as 51.3% of rRNA and 48.7% nonrRNA only from the non-rRNA file.

Why the tool couldn't classify all rRNA's present in the data with the first run,but in the second run? (still few misclassifications)

It would be very helpful if someone could help me out.

Thanks in advance!

assembly

My gut feeling is that MetaVelvet is not the right tool. I think the uneven coverage from transcriptome rather than genome will confuse the k-mer binning step.

it is not a good idea to add two questions into a single post. It discourages contributions because on one likes to answer just a half the question. You'll just end up with neither question being answered.

You should post each question separately.

1 answer

metatranscriptome assembly is at very incipient stage and whatever results you get will probably be wild guesstimates

as for the second question, I suspect that you are not running the tool on the correct files,

the problem intrigued me so we tried the same that you describe but we find exactly what we expect (0 rrna in a non-rrna file)

Hi Istvan Albert,

Thanks for your suggestion,hereafter I post the questions separately.

SortmeRNA:the files I used for applying SORTMERNA were right and what you said is also true,because for instance I have 8 different large data files on which I applied the tool.Out of 8 files,the classification for 4 files is perfect i.e,there were well classified,whereas for the others I came across this issue(rrna's in nonrrna file) that's why I wonder how could this happen?

and thanks once again for your answer

frankly my guess would be to try again, it is very easy to use the wrong file, otherwise post an example of read that only gets found the second time around

ok.here are few FP reads,

HWI-ST365:262:C0RY1ACXX:6:1101:5058:2169 CAAGTAGCATGGAGCACGTGAAATTCCGTGTGAATCTGCGAGGACCACCTCGTAAGGCTAAATATTCCTGAATGACCGATAGTGAAACAGTACCGTGAGG

HWI-ST365:262:C0RY1ACXX:6:1101:2257:2147 CCCGAGTAGTATGGGACACGTGAAATCCCGTATGAATTTGCGAGGACCACCTCGTAAGGCTAAATACTCCTAGGTCACCGATAGCGAATAGTACCGCGAG

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