# De novo transcriptome assembly with Trinity¶

This tutorial will use mRNAseq reads from a small subset of data from Nematostella vectensis (Tulin et al., 2013).

Original RNAseq workflow protocol here, more updated protocol here.

## Installation¶

On a Jetstream instance, run the following commands to update the base software:

sudo apt-get update && \
sudo apt-get -y install screen git curl gcc make g++ python-dev unzip \
default-jre pkg-config libncurses5-dev r-base-core r-cran-gplots \
python-matplotlib python-pip python-virtualenv sysstat fastqc \
trimmomatic bowtie samtools blast2 wget bowtie2 openjdk-8-jre \
hmmer ruby


Install khmer from its source code.

cd ~/
python2.7 -m virtualenv pondenv
source pondenv/bin/activate
cd pondenv
pip install -U setuptools
git clone --branch v2.0 https://github.com/dib-lab/khmer.git
cd khmer
make install


The use of virtualenv allows us to install Python software without having root access. If you come back to this protocol in a different terminal session you will need to run

source ~/pondenv/bin/activate


Install Trinity:

cd ${HOME} wget https://github.com/trinityrnaseq/trinityrnaseq/archive/Trinity-v2.3.2.tar.gz \ -O trinity.tar.gz tar xzf trinity.tar.gz cd trinityrnaseq*/ make |& tee trinity-build.log  Assuming it succeeds, modify the path appropriately in your virtualenv activation setup: echo export PATH=$PATH:$(pwd) >> ~/pondenv/bin/activate source ~/pondenv/bin/activate  You will also need to set the default Java version to 1.8 sudo update-alternatives --set java /usr/lib/jvm/java-8-openjdk-amd64/jre/bin/java  ## Then, let’s check we still have our reads from yesterday’s QC lesson¶ set -u printf "\nMy trimmed data is in$PROJECT/quality/, and consists of $(ls -1${PROJECT}/quality/*.qc.fq.gz | wc -l) files\n\n"
set +u


where set -u should let you know if you have any unset variables, i.e. if the $PROJECT variable is not defined. If you see -bash: PROJECT: unbound variable, then you need to set the$PROJECT variable.

export PROJECT=/mnt/work


and then re-run the printf code block.

NOTE: if you do not have files, please rerun quality trimming steps here

## Let’s do digital normalization with khmer¶

### First, interleave the sequences¶

Next, we need to take these R1 and R2 sequences and convert them into interleaved form, for the next step. To do this, we’ll use scripts from the khmer package <http://khmer.readthedocs.org>__, which we installed above.

Now let’s use a for loop again - you might notice this is only a minor modification of the previous for loop...

cd ${PROJECT}/quality for filename in *_R1_*.qc.fq.gz do # first, make the base by removing .extract.fastq.gz base=$(basename $filename .qc.fq.gz) echo$base

# now, construct the R2 filename by replacing R1 with R2
baseR2=${base/_R1/_R2} echo$baseR2

# construct the output filename
output=${base/_R1/}.pe.qc.fq.gz (interleave-reads.py${base}.qc.fq.gz ${baseR2}.qc.fq.gz | \ gzip >$output)
done


The final product of this is now a set of files named *.pe.qc.fq.gz that are paired-end / interleaved and quality filtered sequences, together with the file orphans.qc.fq.gz that contains orphaned sequences.

Make the end product files read-only!

chmod u-w *.pe.qc.fq.gz orphans.qc.fq.gz


to make sure you don’t accidentally delete them.

Since you linked your original data files into the quality directory, you can now do:

rm *.fastq.gz


to remove them from this location; you don’t need them for any future steps.

Note that the filenames, while ugly, are conveniently structured with the history of what you’ve done to them. This is a good strategy to keep in mind.

## Applying Digital Normalization¶

In this section, we’ll apply digital normalization and variable-coverage k-mer abundance trimming to the reads prior to assembly. This has the effect of reducing the computational cost of assembly without negatively affecting the quality of the assembly.

cd ${PROJECT} mkdir -p diginorm cd diginorm ln -s ../quality/*.qc.fq.gz .  Apply digital normalization to the paired-end reads normalize-by-median.py -p -k 20 -C 20 -M 4e9 \ --savegraph normC20k20.ct -u orphans.qc.fq.gz \ *.pe.qc.fq.gz  Note the -p in the normalize-by-median command – when run on PE data, that ensures that no paired ends are orphaned. The -u tells noralize-by-median that the following filename is unpaired. Also note the -M parameter. This specifies how much memory diginorm should use, and should be less than the total memory on the computer you’re using. (See choosing hash sizes for khmer for more information.) ### Trim off likely erroneous k-mers¶ Now, run through all the reads and trim off low-abundance parts of high-coverage reads filter-abund.py -V -Z 18 normC20k20.ct *.keep && \ rm *.keep normC20k20.ct  This will turn some reads into orphans when their partner read is removed by the trimming. ### Rename files¶ You’ll have a bunch of keep.abundfilt files. Let’s make things prettier: First, let’s break out the orphaned and still-paired reads: for file in *.pe.*.abundfilt do extract-paired-reads.py${file} && \
rm ${file} done  We can combine all of the orphaned reads into a single file gzip -9c orphans.qc.fq.gz.keep.abundfilt > orphans.keep.abundfilt.fq.gz && \ rm orphans.qc.fq.gz.keep.abundfilt for file in *.pe.*.abundfilt.se do gzip -9c${file} >> orphans.keep.abundfilt.fq.gz && \
rm ${file} done  We can also rename the remaining PE reads & compress those files for file in *.abundfilt.pe do newfile=${file%%.fq.gz.keep.abundfilt.pe}.keep.abundfilt.fq
mv ${file}${newfile}
gzip ${newfile} done  This leaves you with a bunch of files named *.keep.abundfilt.fq.gz, which represent the paired-end/interleaved reads that remain after both digital normalization and error trimming, together with orphans.keep.abundfilt.fq.gz. ## Running the Actual Assembly!¶ Let’s make another working directory for the assembly cd${PROJECT}
mkdir -p assembly
cd assembly


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. :

for file in ../diginorm/*.pe.qc.keep.abundfilt.fq.gz
do