Utility scripts for the predector pipeline.
Project description
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
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.
- Strips trailing
*
amino acids from sequences, replaces internal*
s and other redundant amino acids withX
, and converts sequences to uppercase. - removes duplicate sequence using a checksum, saving the mapping table to recover the duplicates at the end of the analysis.
- 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.
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