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 nonrrna 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 appying 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!!
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 nonrrna 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 appying 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!!