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Old 05-17-2011, 03:10 AM   #1
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Default RNA-Seq: Full-length transcriptome assembly from RNA-Seq data without a reference gen

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Full-length transcriptome assembly from RNA-Seq data without a reference genome.

Nat Biotechnol. 2011 May 15;

Authors: Grabherr MG, Haas BJ, Yassour M, Levin JZ, Thompson DA, Amit I, Adiconis X, Fan L, Raychowdhury R, Zeng Q, Chen Z, Mauceli E, Hacohen N, Gnirke A, Rhind N, di Palma F, Birren BW, Nusbaum C, Lindblad-Toh K, Friedman N, Regev A

Massively parallel sequencing of cDNA has enabled deep and efficient probing of transcriptomes. Current approaches for transcript reconstruction from such data often rely on aligning reads to a reference genome, and are thus unsuitable for samples with a partial or missing reference genome. Here we present the Trinity method for de novo assembly of full-length transcripts and evaluate it on samples from fission yeast, mouse and whitefly, whose reference genome is not yet available. By efficiently constructing and analyzing sets of de Bruijn graphs, Trinity fully reconstructs a large fraction of transcripts, including alternatively spliced isoforms and transcripts from recently duplicated genes. Compared with other de novo transcriptome assemblers, Trinity recovers more full-length transcripts across a broad range of expression levels, with a sensitivity similar to methods that rely on genome alignments. Our approach provides a unified solution for transcriptome reconstruction in any sample, especially in the absence of a reference genome.

PMID: 21572440 [PubMed - as supplied by publisher]



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Old 05-26-2011, 01:51 PM   #2
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Has anybody tried this method/software?
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Old 07-28-2011, 06:58 PM   #3
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Yes, we tried the software extensively and found it to take much less RAM than Velvet+Oases.
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Old 08-03-2011, 01:09 PM   #4
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I am performing RNA-seq without a reference genome and just tried Trinity. A quick look at some of the stats on the assemblies is very promising, an increase in the number of contigs above 1000 relative to my merged ABYSS assemblies from multiple kmers.

Has anyone used their Trinity assemblies directly for gene expression analysis? If so I would be interested to hear the approach people are taking. If Trinity is preserving transcript diversity and the resulting assemblies include 'all' possible isoforms of a gene, then is it possible to directly use these contigs as a reference for mapping the raw reads against to perform expression analysis?
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Old 08-06-2011, 08:24 PM   #5
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I just did a comparison between Velvet/Oases, Abyss/Trans-Abyss and Trinity. While Trinity can't be used in on multi k-values, it seems to be more less short transcripts.
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Old 08-07-2011, 09:50 AM   #6
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Trinity has a default k-mer length of 25 but you can change it. I used the k-mer at default and got much better transcript length then Abyss. Longest contig in Abyss was 1157 bp the longest in trinity was 1455 bp.

The program does not take as much memory as Velvet/Oases. However if your reads are long (100bp) it takes a while for inchworm to complete. For my 41 million ~ 100 bp reads it took four days. I think this is because of the short k-mer length and my long reads. If your reads are shorter I am sure if will complete faster.

The authors of the trinity suggested that for expression analysis to use the trinity contigs as a reference and align the reads using Bowtie and then cufflinks for expression comparison.

I am currently trying that now and even though it should be possible to go directly from Bowtie to SAMtools to Cufflinks I am getting errors and no one has come with an answer why.

Also I should mention that if you have a zombie process problem that occurs during butterfly, like I did. Check out the FAQ the answer to the problem is there. http://trinityrnaseq.sourceforge.net/
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Old 10-18-2011, 11:08 PM   #7
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Hi jdjax

Quote:
Originally Posted by jdjax View Post

The program does not take as much memory as Velvet/Oases. However if your reads are long (100bp) it takes a while for inchworm to complete. For my 41 million ~ 100 bp reads it took four days. I think this is because of the short k-mer length and my long reads. If your reads are shorter I am sure if will complete faster.
http://trinityrnaseq.sourceforge.net/
What were your computer specs when you ran this analysis, and were your reads paired end?
Thanks
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Old 10-26-2011, 06:37 AM   #8
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Quote:
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Hi jdjax



What were your computer specs when you ran this analysis, and were your reads paired end?
Thanks
I would recommend looking over this website for your answer:
http://sourceforge.net/mailarchive/f...tyrnaseq-users

This website going give you the answer you are looking for. If it is not in the website join the mailing list and then you can ask the manager of the program.
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