Summarize results and determine zygosity of your CRIS.py analysed clones.
This Matlab script allows to extract and join relevant data from the results files (.csv and .txt) generated by CRIS.py (Connelly J., Pruett-Miller S., Scientific Reports, 2019) (https://github.com/patrickc01/CRIS.py/).
MATLAB ver. R2017b or greater. CSV and TXT results files generated by CRIS.py (https://github.com/patrickc01/CRIS.py/).
Copy the CRISPYparser.m in your folder containing CRIS.py results. Then open the script in a MATLAB workspace. Ensure that your current folder in MATLAB workspace corresponds to your CRIS.py results folder. Introduce your input data in editor and press RUN into EDITOR menu. Alternatively, type CRISPYparser and press enter.
The script will estract the next data from the txt results file generated by CRIS.py:
The fastq file identifier. The number of total reads from each fastq file. The exact sequence and number of reads corresponding to the 2 top reads from each fastq file. This sequences will be referred as Allele 1 and Allele 2.
Then, the script calculates the next data:
The percentage of the 2 top reads from each fastq file. These data will be referred as Alleles percentages. Determine the genotype compatible with the reads pattern of each fastq file. Genotype determination is based on Alleles percentages and the introduced Purity_Percentage.
Finally, the script attachs these data to the CSV result file and generates an excel file (.xlsx) in the working directory.
The excel file generated by CRISPYparser.m allows easier visualization of data coming from CRIS.py analysis. Furthermore, CRISPYparser.m identifies pure clones and determines their zygosity. Concurrent visualization of alleles and CRIS.py analysed sequences percentages allows the identification of more detailed genotypes by conditional formulations in excel.