AUC calculation for pDNA -- Library distribution

This script plots the sgRNA ranks vs. their read fractions. It also calculates and displays the AUC
Author: Mudra Hegde
Email: mhegde@broadinstitute.org

Version: 2.1

Required packages

1. pandas <= 0.16.2
2. numpy
3. matplotlib
4. scikit-learn

Inputs

1. Input file: .txt file with raw read counts; First and second columns may have perturbation sequence and perturbation ID. Raw read counts should be in Column 3 and after
2. Threshold: Fraction of cumulative reads threshold; Default: 0.9, Allowed range: 0.0-1.0
3. Output folder: Folder name for output files storage

To run this script, type the following on the terminal: python calc_read_frac.py --input-file <Path to input file> --thr <Threshold> --outputfolder <Outputfolder name>

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Version: 1.0

Required packages

1. pandas
2. numpy
3. matplotlib
4. scikit-learn

Inputs

1. Input file: .txt file with raw read counts.
2. Column: Column number of column with read counts to be plotted.
3. Title: Title for final plot.
4. Output file

To run this script, type the following on the terminal: python calc_read_frac_v1.0.py --input-file <Path to input file> --column <Column number> --title <Plot title> --outputfile <Path to outputfile>