This is a snapshot of all the programs written in the Jonikas lab that were used in the paper An indexed, mapped mutant library enables reverse genetics studies of biological processes in Chlamydomonas reinhardtii by Xiaobo Li, Ru Zhang, Weronika Patena, Spencer S. Gang, Sean R. Blum, Nina Ivanova, Rebecca Yue, Paul A. Lefebvre, Sorel T. Fitz-Gibbon, Arthur R. Grossman and Martin C. Jonikas (journal, year), as of the final paper submission date - the code in this repository will never be updated.

Updated versions of the code, along with full git logs, functional test cases, and other programs not included here, can be found in our non-snapshot repositories: http://github.com/Jonikas-Lab/mutant-pools, http://github.com/Jonikas-Lab/combinatorial-deconvolution, http://github.com/Jonikas-Lab/combinatorial-pooling, http://github.com/Jonikas-Lab/basic-bioinf-utilities, and http://github.com/Jonikas-Lab/deepseq-processing.

All code was written by Weronika Patena.

File information

Command-line utilities used in the main data processing pipeline. Run them on the command-line with a single "--help" argument to see detailed description of functionality, input, output and options.

• robotic_plate_transfer.py - generate the robot instruction files for combinatorial pooling.
• deepseq_preprocessing_wrapper.py - remove the expected adapter and cassette sequence from the reads, optionally split into reads from the 5' and 3' cassette ends, optionally collapse reads to unique sequences.
• deepseq_alignment_wrapper.py - align the pre-processed reads against the genome and cassette, parse both results, categorize all reads as unaligned, cassette, genomic-unique or genomic-multiple.
• mutant_count_alignments.py - Group aligned reads into insertions based on position, add gene information and annotations, optionally merge adjacent insertions, optionally remove some insertions, generate final insertion file with details and summary of the data.

Major modules used for insertion position analysis - imported by the command-line programs above, and/or used for custom analysis in the interactive python shell (should not be run directly). See class/function docstrings for details.

• mutant_analysis_classes.py - the main module describing the classes used for insertions, insertion positions, and insertion datasets derived from ChlaMmeSeq data, along with methods used for creating, describing and manipulating them.
• mutant_Carette.py - the main module describing the classes used for insertions, insertion positions, and insertion datasets derived from LEAP-Seq data (previously called Carette or RISCC), along with methods used for creating, describing and manipulating them.
• mutant_simulations.py - dealing with genome mappability, mutant simulations, and finding hot/coldspots.
• mutant_plotting_utilities.py - used to generate most of the plots used in the paper, and some of the statistics.
• mutant_utilities.py - various functions: data conversions, replicate reproducibility, and minor utilities.

Major modules used for combinatorial pooling and deconvolution - imported by the command-line programs above, and/or used for custom analysis in the interactive python shell (should not be run directly). See class/function docstrings for details.

• binary_code_utilities.py - utilities for reading, modifying and analyzing binary error-correcting codes used for combinatorial pooling.
• deconvolution_utilities.py - functions for combinatorial deconvolution (i.e. analyzing the deep-sequencing datasets from each super-pool to find the original plate/colony location corresponding to each detected flanking sequence), as well as some additional utilities for analyzing and annotating the resulting deconvolution tables.

Smaller utility programs that can be run from the command-line but were also imported as modules in the analysis.

• seq_count_and_lengths.py - simple utility for checking sequence counts/lengths in fasta/fastq files - used in deepseq_preprocessing_wrapper.py.
• gff_examine_file.py - functions for parsing and examining GFF files describing gene positions (mostly GFF3 files from Phytozome, with some very basic functions for GFF2 files from JGI) - used to determine gene positions for insertions.

General utility modules that were imported by the command-line programs above, and/or used for custom analysis in the interactive python shell (should not be run directly). See class/function docstrings for details. These were mostly not written specifically for this paper, and not all the functions were used in the analysis for the paper, but I didn't want to modify the files by removing unused functions.

• plotting_utilities.py - matplotlib convenience functions, defining custom colormaps, etc
• basic_seq_utilities.py - basic functions for dealing with fasta/fastq files, sequence length, GC-content, motif-finding, etc.
• statistics_utilities.py - convenience functions for quick running of chi-square goodness-of-fit and independence tests (using scipy.stats.chisquare), and for false-discovery-rate adjustment (using the R p.adjust function through rpy2)
• deepseq_utilities.py - parsing SAM-format file fields to get numbers of alignment mismatches.
• general_utilities.py - convenience functions for manipulating numbers and standard data structures, file reading/writing, running command-line processes, etc.
• testing_utilities.py - convenience functions used for running functional tests of the three main command-line programs at the beginnin of this section (this folder doesn't include the input/output files for running functional tests - see the full repository links at the top for that).
• parse_annotation_file.py - parse Phytozome gene annotation files.
• plate_utilities.py - simple utility for dealing with plate/well/mutant numbers.

Minor programs that were not actually used in the analysis, but are imported by some of the modules that were, and thus are included here for completeness and to make it easier to get everything to run.

• parse_fasta.py
• reverse_complement.py
• reverse.py
• complement.py
• transform_sequence_input.py
• read_input.py

Note that most of this is continued in-progress work. I tried to keep the files reasonably documented, cleaned up and tested, but some will be better than others. Please let me know if you have any questions or find any errors.

Dependencies

python 2.7 (http://www.python.org)

Python packages (imported in one or more of the files):

• numpy (http://www.numpy.org/)
• matplotlib (http://matplotlib.org/)
• scipy (and scipy.stats) (http://www.scipy.org/)
• rpy2 (for a few statistical functions) (http://rpy.sourceforge.net)
• Bio (Biopython; mostly only minor functions) (http://biopython.org)
• HTSeq (for parsing sam files) (http://pypi.python.org/pypi/HTSeq)
• BCBio.GFF (for parsing gff3 files) (http://github.com/chapmanb/bcbb/tree/master/gff)
• bitstring (for combinatorial pooling codes) (http://pypi.python.org/pypi/bitstring)

Standalone command-line programs (called via subprocess or another method in one or more of the files):

• bowtie (used in deepseq_alignment_wrapper.py) (http://bowtie-bio.sourceforge.net)
• cutadapt (used in deepseq_preprocessing_wrapper.py) (http://pypi.python.org/pypi/cutadapt/1.2.1)
• fastx_collapser (used in deepseq_preprocessing_wrapper.py) (part of FastX_Toolkit - http://github.com/lianos/fastx-toolkit)
• R (used via rpy2 for a few statistical functions) (http://www.r-project.org/)

License

All of this code is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

The full text of the GNU General Public License, version 3, can be found here: http://www.gnu.org/licenses/gpl-3.0.html