predectorutils 0.7.0

Utility scripts for the predector pipeline.

predector-utils

Utilities for running the predector pipeline.

This is where the models and more extensive utility scripts are developed.

All command line tools are accessible under the main command predutils.

predutils r2js

Convert the output of one of the analyses into a common line delimited JSON format. The json records retain all information from the original output files, but are much easier to parse because each line is just JSON.

Basic usage:

predutils r2js \
  -o outfile.ldjson \
  --pipeline-version 0.0.1 \
  signalp3_nn \
  signalp3_nn_results.txt \
  in.fasta

Analyses available to parse in place of signalp3_nn are: signalp3_nn, signalp3_hmm, signalp4, signalp5, deepsig, phobius, tmhmm, deeploc, targetp_plant (v2), targetp_non_plant (v2), effectorp1, effectorp2, apoplastp, localizer, pfamscan, dbcan (HMMER3 domtab output), phibase *, pepstats.

* assumes search with MMseqs with tab delimited output format columns: query, target, qstart, qend, qlen, tstart, tend, tlen, evalue, gapopen, pident, alnlen, raw, bits, cigar, mismatch, qcov, tcov.

predutils encode

Preprocess some fasta files.

1. Strips trailing * amino acids from sequences, replaces internal *s and other redundant amino acids with X, and converts sequences to uppercase.
2. removes duplicate sequence using a checksum, saving the mapping table to recover the duplicates at the end of the analysis.
3. Replace the names of the deduplicated sequences with a short simple one.

Basic usage:

predutils encode \
  output.fasta \
  output_mapping.tsv \
  input_fastas/*

Note that it can take multiple input fasta files, and the filename is saved alongside the sequences in the output mapping table to recover that information.

By default, the temporary names will be SR[A-Z0-9]5 e.g. SR003AB. You can change the prefix (default SR) with the --prefix flag, and the number of id characters (default 5) with the --length parameter.

predutils split_fasta

Splits a fasta files into several files each with a maximum of n sequences.

Basic usage:

predutils split_fasta --template 'chunk{index}.fasta' --size 100 in.fasta

The --template parameter accepts python .format style string formatting, and is provided the variables fname (the input filename) and index (the chunk number starting at 1). To pad the numbers with zeros for visual ordering in directories, use the something like --template '{fname}.{index:0>4}.fasta'. Directories in the template will be created for you if they don't exist.

predutils decode

The other end of predutils encode. Takes the common line delimited format from analyses and separates them back out into the original filenames.

predutils decode \
  --template 'decoded/{filename}.ldjson' \
  output_mapping.tsv \
  results.ldjson

We use the template flag to indicate what the filename output should be, using python format style replacement. Available values to --template are filename and filename_noext. The latter is just filename without the last extension.

predutils tables

Take the common line delimited output from predutils r2js and recover a tabular version of the raw data. Output filenames are controlled by the --template parameter, which uses python format style replacement. Currently, analysis is the only value available to the template parameter. Directories in the template will be created automatically.

predutils tables \
  --template "my_sample-{analysis}.tsv" \
  results.ldjson

predutils gff

Take the common line-delimited json output from predutils r2js and get a GFF3 formatted set of results for analyses with a positional component (e.g. signal peptides, transmembrane domains, alignment results).

predutils gff \
  --outfile "my_sample.gff3" \
  results.ldjson

By default, mmseqs and HMMER search results will be filtered by the built in significance thresholds. To include all matches in the output (and possibly filter by your own criterion) supply the flag --keep-all.

predutils rank

Take the common line-delimited json output from predutils r2js and get a summary table that includes all of the information commonly used for effector prediction, as well as a scoring column to prioritise candidates.

predutils rank \
  --outfile my_samples-ranked.tsv \
  results.ldjson

To change that Pfam or dbCAN domains that you consider to be predictive of effectors, supply a text file with each pfam or dbcan entry on a new line (do not include pfam version number or .hmm in the ids) to the parameters --dbcan or --pfam.

You can also change the weights for how the score columns are calculated. See predutils rank --help for a full list of parameters.