Scripts and wrapper file for runing the Shiu Lab's pseduogene pipeline.

• Zou C, Lehti-Shiu, MD, Thibaud-Nissen F, Prakash Th, Buell CR, and Shiu SH (2009) Evolutionary and Expression Signatures of Pseudogenes in Arabidopsis thaliana and Rice. Plant Physiol. 151:3-15. pubmed
• Campbell M, Law MY, Holt C, Stein J, Moghe G, Hufnagel Du, Lei J, Achawanantakun R, Jiao D, Lawrence C, Ware D, Shiu SH, Childs K, Sun Y, Jiang N, Yandell M (2014) MAKER-P: a tool-kit for the rapid creation, management, and quality control of plant genome annotations. Plant Physiol164(2):513-24 pubmed
• Lloyd JP, Tsai ZTY, Sowers RPu, Panchy NL, Shiu SH (2018) A model-based approach for identifying functional intergenic transcribed regions and non-coding RNAs. Mol. Biol. Evol. 35(6):1422-1436 pubmed

• python 3 (https://www.python.org/downloads/)
• python scripts in the _scripts folder
• RepeatMaster (http://www.repeatmasker.org/)
  • A local installation of RepeatMasker is needed. Note that RepeatMasker has other dependencies.
• tfasty (part of the fasta36 package, version 36.0.0 or later; https://github.com/wrpearson/fasta36):
  • The GitHub version need to be compiled and installed. Please follow the instruction in the README for fasta36.

The pipline is run using:

python _scripts/PseudogenePipeline.py [parameter_file]

To invoke the help function, run:

python _scripts/PseudogenePipeline.py

This text file specifies how the pipeline should run and an example can found in in the _example_files folder.

Two test datasets are provided for you to gauge whether there is any issues.

1. _test25.tgz: This compressed file contains a test dataset of 25 proteins that takes ~1 minute to run. To use:

tar xvzf _test25.tgz
cd _test25

Then make sure the test_parameter_file in the folder is modified to specifiy:

• The location and name of tfasty program.
• The location of RepeatMasker.
• The location of PseudogenePipeline's _scripts folder.

Below we assume that you are in the _test25 folder is in the cloned PseudogenePipeline folder. Run the pipeline:

python ../_scripts/PseudogenePipeline.py test_parameter_file 

The _expected_results folder contains what you should be seeing.

2. _test27206.tgz: This is a test case that is more realistic with a larger Arabidopsis thaliana dataset that takes ~20-30 min to run.

The output of the pipeline is seperated into the following subfolder:

• _intermediate: Intermediate files used to generate final results.
• These may be removed following a successful run, however if you want a list of pseudogenes generated prior to high confidence filtering and/or RepatMasker filtering they will be here
• _logs: log files generated by the run
• _results: Output files for the final list of pseudogenes following high confidence and and RepeatMasker filtering
  1. hiConf.RMfilt/hiConf.RMfilt.cdnm - position information for pseudogenes
  2. fa.hiConf.RMfilt/fa.hiConf.RMfilt.cdnm - sequence information for pseudogenes
  3. hiConf.RMfilt.cdnm.gff - gff file with pseudogene annotations
  4. pseudogene_evidence_cod - information on the numbers of stop codons, stop condons near gaps, frameshits, framshifts near gaps. Because the gaps can simply be alignments between coding sequence and introns, any predicted stop and frameshift near them are of lower confidence.
• NOTE: cdnm versions of the output use simplified pseudogene names.

• Converted to Python 3.
• Some changes so the codes are PEP8-compliant.
• Added license.

• Implemented in Python 2.
• Included functionalities for checking parameter and input files.
• The version for the Campbell et al. (2014) Plant Physiol.
• Python 2-based.