annotate lifelines_tool/plotlykm.py @ 0:dd49a7040643 draft

Initial commit

# script for a lifelines ToolFactory KM/CPH tool for Galaxy
# km models for https://github.com/galaxyproject/tools-iuc/issues/5393
# test as
# python plotlykm.py --input_tab rossi.tab --htmlout "testfoo" --time "week" --status "arrest" --title "test" --image_dir images --cphcol="prio,age,race,paro,mar,fin"

import argparse
import os
import sys

import lifelines

from matplotlib import pyplot as plt

import pandas as pd

# Ross Lazarus July 2023


kmf = lifelines.KaplanMeierFitter()
cph = lifelines.CoxPHFitter()

parser = argparse.ArgumentParser()
a = parser.add_argument
a('--input_tab', default='', required=True)
a('--header', default='')
a('--htmlout', default="test_run.html")
a('--group', default='')
a('--time', default='', required=True)
a('--status',default='', required=True)
a('--cphcols',default='')
a('--title', default='Default plot title')
a('--image_type', default='png')
a('--image_dir', default='images')
a('--readme', default='run_log.txt')
args = parser.parse_args()
sys.stdout = open(args.readme, 'w')
df = pd.read_csv(args.input_tab, sep='\t')
NCOLS = df.columns.size
NROWS = len(df.index)
defaultcols = ['col%d' % (x+1) for x in range(NCOLS)]
testcols = df.columns
if len(args.header.strip()) > 0:
    newcols = args.header.split(',')
    if len(newcols) == NCOLS:
        if (args.time in newcols) and (args.status in newcols):
            df.columns = newcols
        else:
            sys.stderr.write('## CRITICAL USAGE ERROR (not a bug!): time %s and/or status %s not found in supplied header parameter %s' % (args.time, args.status, args.header))
            sys.exit(4)
    else:
        sys.stderr.write('## CRITICAL USAGE ERROR (not a bug!): Supplied header %s has %d comma delimited header names - does not match the input tabular file %d columns' % (args.header, len(newcols), NCOLS))
        sys.exit(5)
else: # no header supplied - check for a real one that matches the x and y axis column names
    colsok = (args.time in testcols) and (args.status in testcols) # if they match, probably ok...should use more code and logic..
    if colsok:
        df.columns = testcols # use actual header
    else:
        colsok = (args.time in defaultcols) and (args.status in defaultcols)
        if colsok:
            sys.stderr.write('replacing first row of data derived header %s with %s' % (testcols, defaultcols))
            df.columns = defaultcols
        else:
            sys.stderr.write('## CRITICAL USAGE ERROR (not a bug!): time %s and status %s do not match anything in the file header, supplied header or automatic default column names %s' % (args.time, args.status, defaultcols))
print('## Lifelines tool starting.\nUsing data header =', df.columns, 'time column =', args.time, 'status column =', args.status)
os.makedirs(args.image_dir, exist_ok=True)
fig, ax = plt.subplots()
if args.group > '':
    names = []
    times = []
    events = []
    rmst = []
    for name, grouped_df in df.groupby(args.group):
        T = grouped_df[args.time]
        E = grouped_df[args.status]
        gfit = kmf.fit(T, E, label=name)
        kmf.plot_survival_function(ax=ax)
        rst = lifelines.utils.restricted_mean_survival_time(gfit)
        rmst.append(rst)
        names.append(str(name))
        times.append(T)
        events.append(E)
    ngroup = len(names)
    if  ngroup == 2: # run logrank test if 2 groups
        results = lifelines.statistics.logrank_test(times[0], times[1], events[0], events[1], alpha=.99)
        print(' vs '.join(names), results)
        results.print_summary()
    elif ngroup > 1:
        fig, ax = plt.subplots(nrows=ngroup, ncols=1, sharex=True)
        for i, rst in rmst:
            lifelines.plotting.rmst_plot(rst, ax=ax)
        fig.savefig(os.path.join(args.image_dir,'RMST_%s.png' % args.title))
else:
    kmf.fit(df[args.time], df[args.status])
    kmf.plot_survival_function(ax=ax)
fig.savefig(os.path.join(args.image_dir,'KM_%s.png' % args.title))
if len(args.cphcols) > 0:
    fig, ax = plt.subplots()
    cphcols = args.cphcols.strip().split(',')
    cphcols = [x.strip() for x in cphcols]
    notfound = sum([(x not in df.columns) for x in cphcols])
    if notfound > 0:
        sys.stderr.write('## CRITICAL USAGE ERROR (not a bug!): One or more requested Cox PH columns %s not found in supplied column header %s' % (args.cphcols, df.columns))
        sys.exit(6)
    print('### Lifelines test of Proportional Hazards results with %s as covariates on %s' % (', '.join(cphcols), args.title))
    cphcols += [args.time, args.status]
    cphdf = df[cphcols]
    cph.fit(cphdf, duration_col=args.time, event_col=args.status)
    cph.print_summary()
    cphaxes = cph.check_assumptions(cphdf, p_value_threshold=0.01, show_plots=True)
    for i, ax in enumerate(cphaxes):
        figr = ax[0].get_figure()
        titl = figr._suptitle.get_text().replace(' ','_').replace("'","")
        oname = os.path.join(args.image_dir,'CPH%s.%s' % (titl, args.image_type))
        figr.savefig(oname)