8. De novo assembly with Velvet

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Velvet is an assembly algorithm developed for genomic assembly, but it can be applied to transcriptome assembly as well. A more recent algorithm from the same authors, called Oases, was developed specifically for un-guided transcriptome reconstruction, but for our purposes the original velvet is enough. Other de novo transcriptome reconstruction algorithms exist, for example Trinity, which is generally more accurate but has very large computational requirements, especially for memory. Trinity offers also modules for gene expression and differential expression estimation, while velvet is limited to transcript reconstruction. We will make a similar usage guide for Trinity in another session.

Velvet is composed by two modules, velveth and velvetg, that need to be run one after the other. The first module analyzes the reads, decomposes them in sub-sequences of fixed length k (called k-mers) and builds an index of all k-mers. The second module takes as input the output of velveth and builds structures in which reads overlap, called contigs, corresponding to transcripts when the input contains RNA-seq reads. Let’s open a script for running velvet, and write the header, load the modules and point to the working directory:

#$ -S /bin/sh
#$ -cwd
#$ -q amd.q,large.q,intel.q
#$ -l h_vmem=16G
#$ -e velveth.e
#$ -N velveth
#$ -o velveth.o
module load velvet/1.2.10
cd /ibers/ernie/scratch/vpl/zebra_fish

The general usage of the velveth module is:


./velveth directory hash_length {[-file_format][-read_type][- separate|-interleaved] filename1 [filename2 ...]} {...} [options]

where directory is the name of the output folder and hash_length is the size of the k-mers in which reads are decomposed (must be an even number). Now let’s write the velveth command to assemble reads from the 6 hours zebrafish embryo (all in one line):

velveth velvet_out 29 -fastq data/6h_1.trim.fastq data/6h_2.trim.fastq

The parameters are:

velvet_out: the output folder

29: the value of k

-fastq: the input format

The second module, velvetg, has many options, but can also simply run just specifying the folder with the velveth output. Let’s now add the velvetg command in the file that you are writing:

velvetg velvet_out

Now save and close the file and run with qsub. When it is finished, have a look at the output folder (using for example ls –l velvet_out). Some files (e.g. Roadmaps, Sequences) report the reads decomposition and indexing. The file with the reconstructed transcript is contigs.txt. Open it, and you will see the sequence of all transcripts in fasta format.

Let’s now see if velvet was able to correctly assemble zebrafish transcripts. Open contigs.fa, choose one transcript sufficiently long and copy it. Now open your browser and go to: [1]

Click on nucleotide blast on the left size of the screen. Paste the chosen sequence from the velvet output into the text box, select Nucleotide collection (nr/nt) from Choose Search Set, then click the BLAST button and wait until completion. Verify that the best match in the BLAST output is a zebrafish gene. If you want, try again with other reconstructed transcripts, trying some large ones and some small ones. Do all of them have a good match with zebrafish genes?