![]() |
|
![]() |
||||
Thread | Thread Starter | Forum | Replies | Last Post |
Oases: De novo transcriptome assembly of very short reads | lcollado | De novo discovery | 58 | 02-07-2017 09:48 AM |
de novo assembly using Trinity versus Velvet-Oases | Nol | De novo discovery | 8 | 10-26-2013 12:56 PM |
need your knowledge: can an oases assembly run be resumed? | Kennels | Bioinformatics | 1 | 05-02-2013 05:05 PM |
Denovo RNA-Seq assembly using Velvet/Oases | AdrianP | RNA Sequencing | 5 | 01-03-2013 03:04 AM |
Error when running Oases for transcriptome assembly | yjx1217 | Bioinformatics | 5 | 10-31-2012 09:49 AM |
![]() |
|
Thread Tools |
![]() |
#1 |
Junior Member
Location: New York Join Date: Oct 2012
Posts: 9
|
![]()
Hi,
I have run velvet-oases on k-mers 21 thru 55, and I am trying to merge the assemblies now. I tried using the velveth --> velvetg --> oases approach from the "Assembly Merging" section of the manual, but velvetg runs for an abnormally long duration (>48 hours), and the cluster on which I'm running the script times out. I have tried providing 244 GB of RAM, but it makes no difference - the "Log" file from velveth is written to once when the script starts running, and no other file(including the redirected stderr/stdout) is touched for the entire duration of the run. Any idea how I could tackle this? -- Thanks, Ram
__________________
Ram |
![]() |
![]() |
![]() |
#2 |
Senior Member
Location: Worcester, MA Join Date: Oct 2009
Posts: 133
|
![]()
Small K-mer assemblies are pretty computationally heavy. How many reads are you working with? Have you done any quality filtering on your reads?
If you are using a massive amount of reads, you may want to consider implementing some sort of digital normalization (Trinity can do this independent of assembly and Titus Brown has a version of digital normalization as well http://arxiv.org/abs/1203.4802). Reducing reads and reads with errors will greatly reduce memory and run time. |
![]() |
![]() |
![]() |
#3 | |
Junior Member
Location: New York Join Date: Oct 2012
Posts: 9
|
![]()
Hi,
Thank you so much for the response! I'm working with Titus Brown's version of digital normalization right now - that brought the reads down from around 289 mil to 12 mil (6X2) PE reads and 7 mil SE reads (after a strip-and-split ). I asked my sequencing provider - the only QC step was the pass filter run on raw reads. Is there a specific QC filter I can use for transcriptome reads? Quote:
__________________
Ram |
|
![]() |
![]() |
![]() |
#4 |
Senior Member
Location: Worcester, MA Join Date: Oct 2009
Posts: 133
|
![]()
No problem.
One thing you may want to try BEFORE digital normalization is trimming reads based on quality score. There are quite a few pieces of software that can do this (trimmomatic and trim galore to name a couple). |
![]() |
![]() |
![]() |
Tags |
abnormally long run time, merging assemblies, velvetg |
Thread Tools | |
|
|