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|04-08-2017, 12:02 PM||#1|
Location: Sydney, Australia
Join Date: Jan 2017
CLC Bio vs. Trinity for de novo transcriptome assembly
I have some questions regarding CLC Bio vs. Trinity for de novo RNA seq assembly. When I was told how to process my data by a postdoc in my lab, he insisted on using CLC Bio, on the default setting. I've looked into CLC Bio and I'm not sure if this is the correct way to go about things. But before I step away from a published methodology, I have to convince my supervisor too. That's where I hope you can help me.
1/ Eukaryotic, single celled algae - dinoflagellates. The phylum is particularly known for bizaare genetic elements:
- 0.5 to 40 x genetic content of human haploid genome
- mRNA frequently reinserted into genome, i.e.. a mine field of truncated paralogs. They are the hoarders of the genetic world.
- ancient lineage, they've had a long time to accumulate paralogs. Some rDNA genes have in excess of 2000 copies, most phylogenetic analyses of the order that I work with are rubbish because of this.
- they have a different, still unknown mode of gene regulation, appears to be post-transcriptional. I.e. mRNA seq data is massive and gives us a pretty good idea about the genome. We think.
- hence, no reference genomes or even transcriptomes available.
2/ Working with sequencing data from both public database (MMETSP) and my own work. Some of the former is really quite low quality.
- public: Illumina Hi-Seq 2000, PE, 50bp inserts
- mine: Nextseq500, PE, 75bp inserts, HO
- mine, second round of sequencing occurring now: Nextseq500, PE, 150bp inserts, HO
I've come across someone else's (Lisa Cohen, github - really cool project) usage of the publicly available data, using Trinity and then the same quality control assessment that I had run - BUSCO (looks for single copy genes via hmmer libraries, successor of CEGMA). So I have a direct comparison point between the BUSCO score of my CLC Bio assemblies vs. her Trinity assemblies using the same RNA seq libraries. Hers are better across the board for single copy hits. Some transcriptomes only by 2 genes, but in one or two transcriptomes the difference is 50 single copy genes out of the 450 tested.
- what is the general knowledge/feeling about CLC Bio and Trinity? Preferences or horror stories?
- is either of the assemblers known for making mistakes?
- more directly, is either of them partial to misassembly of paralogs - if one gives me more single copy genes, is that a 'true' result or are they actually a mash up of paralogs?
Last edited by nurgling; 04-08-2017 at 12:07 PM.
|04-12-2017, 07:09 PM||#2|
Location: Hobart, Australia
Join Date: May 2015
There is a difference
Yes, there is a difference in the quality/completeness of the assembled transcriptomes (Cegma and BUSCO). I would suggest to use Trinity and then follow you pipeline with/without CLC.
|04-13-2017, 12:17 AM||#3|
David Eccles (gringer)
Location: Wellington, New Zealand
Join Date: May 2011
Trinity: over 1000 citations, free and open source, a prescriptive published protocol for de-novo assembly and DE analysis. I hacked the code a little to get it to work on my desktop computer.
|04-14-2017, 04:01 PM||#4|
Join Date: Dec 2010
Trinity is the standard for de novo transcriptome assemblies. Thus also the artifacts it produces are relatively wellk nown.
Sorry, I have never used CLC for this purpose. I would suggest to contact CLC for suggested settings for transcriptomes (I can't imagine the defaults are optimal).
For genome assemblies CLC has the advantage that it will work with all kinds of data (all kinds of read lengths, paired or not paired, and even low quality data). In short it is extremely robust for this purpose.
|clc bio, de novo transcriptome, trinity|