All of the below should be run in screen, probably... You will want at least 15 GB of RAM, maybe more.
(If you start up a new machine, you’ll need to go to 1. Quality Trimming and Filtering Your Sequences and install khmer and screed.)
Note
You can start this tutorial with the contents of EC2/EBS snapshot snap-7b0b872e.
To install Trinity:
cd /root
curl -L http://sourceforge.net/projects/trinityrnaseq/files/latest/download?source=files > trinity.tar.gz
tar xzf trinity.tar.gz
cd trinityrnaseq*/
export FORCE_UNSAFE_CONFIGURE=1
make
Download and install bowtie:
cd /root
curl -O -L http://sourceforge.net/projects/bowtie-bio/files/bowtie/0.12.7/bowtie-0.12.7-linux-x86_64.zip
unzip bowtie-0.12.7-linux-x86_64.zip
cd bowtie-0.12.7
cp bowtie bowtie-build bowtie-inspect /usr/local/bin
Download and install samtools:
cd /root
curl -L http://sourceforge.net/projects/samtools/files/latest/download?source=files >samtools.tar.bz2
tar xjf samtools.tar.bz2
mv samtools-* samtools-latest
cd samtools-latest/
make
cp samtools bcftools/bcftools misc/* /usr/local/bin
For paired-end data, Trinity expects two files, ‘left’ and ‘right’; there can be orphan sequences present, however. So, below, we split all of our interleaved pair files in two, and then add the single-ended seqs to one of ‘em.
cd /mnt/work
for i in *.pe.qc.keep.abundfilt.fq.gz
do
python /usr/local/share/khmer/scripts/split-paired-reads.py $i
done
cat *.1 > left.fq
cat *.2 > right.fq
gunzip -c *.se.qc.keep.abundfilt.fq.gz >> left.fq
Run the assembler!
/root/trinityrnaseq*/Trinity.pl --left left.fq --right right.fq --seqType fq -JM 10G
Note that this last bit (10G) is the maximum amount of memory to use. You can increase (or decrease) it based on what machine you rented. This size works for the m1.xlarge machines.
Once this completes (on the Nematostella data it might take about 12 hours), you’ll have an assembled transcriptome in trinity_out_dir/Trinity.fasta.
You can now copy it over via Dropbox, or set it up for BLAST (see 4. BLASTing your assembled data).
Next: 5. Building transcript families (or 4. BLASTing your assembled data).