SEQanswers

Go Back   SEQanswers > Literature Watch



Similar Threads
Thread Thread Starter Forum Replies Last Post
Two Studies Comparing SeqMan NGen to Other Assemblers DNASTAR Vendor Forum 0 10-26-2011 08:07 AM
Transcriptome assemblers - Oases, Trinity samanta General 0 10-04-2011 11:48 AM
Assembling De Novo 454 Transcriptome Contigs and Singletons with Illumina Short Reads Vickenstein Bioinformatics 7 03-05-2011 01:43 AM
Problems with de novo transcriptome assembly using 454 Titanium series ankitgupta.iitg Bioinformatics 1 10-30-2009 12:15 PM
De-Novo transcriptome with 454 Titanium yvan.wenger RNA Sequencing 3 10-29-2009 01:19 AM

Reply
 
Thread Tools
Old 10-19-2010, 04:31 AM   #1
strob
Member
 
Location: Belgium

Join Date: Nov 2008
Posts: 79
Default Comparing de novo assemblers for 454 transcriptome data

Comparing de novo assemblers for 454 transcriptome data
Sujai Kumar and Mark L Blaxter

BMC Genomics 2010, 11:571doi:10.1186/1471-2164-11-571

Published: 16 October 2010
Abstract (provisional)

Background
Roche 454 pyrosequencing has become a method of choice for generating transcriptome data from non-model organisms. Once the tens to hundreds of thousands of short (250-450 base) reads have been produced, it is important to correctly assemble these to estimate the sequence of all the transcripts. Most transcriptome assembly projects use only one program for assembling 454 pyrosequencing reads, but there is no evidence that the programs used to date are optimal. We have carried out a systematic comparison of five assemblers (CAP3, MIRA, Newbler, SeqMan and CLC) to establish best practices for transcriptome assemblies, using a new dataset from the parasitic nematode Litomosoides sigmodontis.

Results
Although no single assembler performed best on all our criteria, Newbler 2.5 gave longer contigs, better alignments to some reference sequences, and was fast and easy to use. SeqMan assemblies performed best on the criterion of recapitulating known transcripts, and had more novel sequence than the other assemblers, but generated an excess of small, redundant contigs. The remaining assemblers all performed almost as well, with the exception of Newbler 2.3 (the version currently used by most assembly projects), which generated assemblies that had significantly lower total length. As different assemblers use different underlying algorithms to generate contigs, we also explored merging of assemblies and found that the merged datasets not only aligned better to reference sequences than individual assemblies, but were also more consistent in the number and size of contigs.

Conclusions
Transcriptome assemblies are smaller than genome assemblies and thus should be more computationally tractable, but are often harder because individual contigs can have highly variable read coverage. Comparing single assemblers, Newbler 2.5 performed best on our trial data set, but other assemblers were closely comparable. Combining differently optimal assemblies from different programs however gave a more credible final product, and this strategy is recommended.

http://www.biomedcentral.com/1471-2164/11/571
strob is offline   Reply With Quote
Reply

Thread Tools

Posting Rules
You may not post new threads
You may not post replies
You may not post attachments
You may not edit your posts

BB code is On
Smilies are On
[IMG] code is On
HTML code is Off




All times are GMT -8. The time now is 03:28 AM.


Powered by vBulletin® Version 3.8.9
Copyright ©2000 - 2018, vBulletin Solutions, Inc.
Single Sign On provided by vBSSO