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Protein Assembly with PLASS

The basic idea with any transcriptome or metatranscriptome assembly is you feed in your reads and you get out a bunch of contigs that represent transcripts, or stretches of RNA present in the reads. You run a transcriptome assembly program using the adapter & k-mer trimmed reads as input and get out a pile of assembled RNA.

Most assemblers work in nucleotide space. This means that they find direct overlaps between the As, Ts, Cs, and Gs in the reads and use information about those overlaps to make contigs. Although this is a powerful method, it often fails when:

  • There is sequencing errors
  • There are repetitive regions
  • There is strain variation

When assembly fails, contigs either break or don't assemble at all.

Given that nucleotide sequences are far more variable than protein sequences (third base pair wobble in strain variation in particular), assembling in amino acid space can overcome a lot of the difficulties encountered when assembling in nucleotide space.

PLASS is a new assembler that assembles in amino acid space. Unlike many other assemblers, including Trinity, it does not have built in error correction and so it is best to adapter and k-mer trim the reads before using it. It sometimes performs better than nucleotide assemblers and so is good to test on samples to see what type of improvement it can give.

Quickstart

Run PLASS via the Protein Assembly workflow or via the plass_assemble subworkflow. These workflows will run preprocessing and kmer-trimming for you prior to assembly, and may run additional downstream steps. To run PLASS as a standalone program, see "Advanced Usage" section below.

elvers examples/nema.yaml plass_assemble

PLASS Command

On the command line, the command elvers runs is approximately:

plass assemble input_1.fq input_2.fq \
  outputi_plass.fasta --threads snakemake.threads extra_params

Output files:

Your main output directory will be determined by your config file: by default it is BASENAME_out (you specify BASENAME).

PLASS will output files in the assembly subdirectory of this output directory. The fasta file will be BASENAME_plass.fasta.

Modifying Params for PLASS:

Be sure to set up your sample info and build a configfile first (see Understanding and Configuring Workflows).

To see the available parameters for the plass rule, run

elvers config plass --print_params

This will print the following:

  ####################  plass  ####################
plass:
  input_kmer_trimmed: true
  input_trimmomatic_trimmed: false
  add_single_to_paired: false # would you like to add the orphaned reads to the plass assembly?
  extra: '' 
  #####################################################

Within the Protein Assembly workflow or the plass_assemble subworkflow, these options enable you to choose kmer-trimmed, quality-trimmed, or raw sequencing data as input. We recommend using kmer-trimmed reads as input. If both input_kmer_trimmed and input_trimmomatic_trimmed are False, we will just use raw reads from the samples.tsv file.

In addition to changing parameters we've specifically enabled, you can modify the extra param to pass any extra plass parameters, e.g.:

  extra: '--someflag someparam --someotherflag thatotherparam'

See the PLASS documentation to learn more about the parameters you can pass to PLASS.

Be sure the modified lines go into the config file you're using to run elvers (see Understanding and Configuring Workflows).

Advanced Usage: Running PLASS as a standalone rule

You can run plass as a standalone rule, instead of withing a larger elvers workflow. However, to do this, you need to make sure the input files are available.

For plass, the default input files are kmer-trimmed input data (e.g. output of khmer).

If you've already done this, you can run:

elvers my_config plass

If not, you can run the prior steps at the same time to make sure khmer can find these input files:

elvers my_config get_data trimmomatic khmer plass

Snakemake Rules

We wrote a PLASS snakemake wrapper to run PLASS via snakemake. This wrapper has not yet been submitted to the snakemake-wrappers repository, but feel free to use it as needed.

For snakemake afficionados, see our PLASS rule on github.