plot_chimeras

Generate combined chimeric protein sequence maps from an MSA.

The segments are inferred by Dynamic Programming (Viterbi algorithm) to find the sequence of parental origins that minimizes the total number of segment switches (crossovers).

Inputs

• A multiple sequence alignment (MSA) in FASTA format (no star symbol for stop codons) containing the target chimeric protein and the parental sequences (required).
• An annotation file (in CSV) format containing general, or target specific annotations (optional).

Output

A PNG file containing the annotated sequence maps of the targets.

Installation

As a python script you can just run the plot_chimeras.py file, or put a symbolic link in any directory of your PATH. The script depends on the following Python libraries:

• argparse
• os
• matplotlib

Usage

plot_chimeras [-h] -i FASTA -t TARGETS [TARGETS ...] -p PARENTALS [PARENTALS ...] [-f FEATURES] [-o OUTPUT] [-v]

options:
  -h, --help            show this help message and exit
  -i, --fasta FASTA     Input MSA FASTA file
  -t, --targets TARGETS [TARGETS ...]
                        List of target sequence IDs (space-separated)
  -p, --parentals PARENTALS [PARENTALS ...]
                        List of parental sequence IDs (space-separated)
  -f, --features FEATURES
                        Optional CSV file with features
  -o, --output OUTPUT   Output PNG file path
  -v, --version         Show program's version number and exit

Example

The example directory contain an MSA of multiple EGF sequences, with two mock chimeras.

Move to the example directory and run:

plot_chimeras.py -i sequence_alignment.fasta -f annotations.csv -p EGF_HUMAN EGF_CAT EGF_PIG EGF_HORSE EGF_MOUSE EGF_DOG -t EGF_CHIMERA1 EGF_CHIMERA2 -o EGF_CHIMERA_sequence_maps.png

The map will be created for the specified targets using the given parental sequences. All other sequences in the MSA are ignored.

You can create sequence specific or common annotations (see annotation.csv example).