"""

Command line interface tool for cell-free DNA fragment trace analysis with DNAvi.

Author: Anja Hess

Date: 2023-AUG-01

"""

logo=r"""Welcome to

____ _ _ _ _

| _ | \ | | / \__ _(_)

| | | | \| | / _ \ \ / / |

| |_| | |\ |/ ___ \ V /| |

|____/|_| \_/_/ \_\_/ |_|

"""

print(logo)

import os

import glob

import argparse

import logging

import datetime

from src.data_checks import (check_input, check_ladder, check_meta, check_name,

check_marker_lane, check_config, check_interval,

generate_meta_dict)

from src.analyze_electrophero import epg_analysis, merge_tables

from src.constants import ACCEPTED_FORMATS, NUC_DICT, LOGFILE_NAME

from src.analyze_gel import analyze_gel

#########################################################################

# Initiate Logging (save to working dir)

#########################################################################

logging.basicConfig(level=logging.INFO,

format='%(asctime)s %(name)-12s %(levelname)-8s %(message)s',

datefmt='%m-%d %H:%M',

filename=f'{os.getcwd()}/{LOGFILE_NAME}',

filemode='w', force=True)

logging.info(f"--- RUN STARTED, {datetime.datetime.now()}")

version = "0.0.0.0.3"

#########################################################################

# Initiate Parser

#########################################################################

parser = argparse.ArgumentParser(description=

'Analyse Electropherogram data '

'e.g. for cell-free DNA from liquid biopsies',

epilog=f"""Version:{version}, created by

Anja Hess <github.com/anjahess>.""")

#########################################################################

# Add arguments

#########################################################################

parser.add_argument('-i', '--input',

type=check_input,

metavar='<input-file-or-folder>',

nargs='?', #single file

help='Path to electropherogram table file or image '

'file OR directory containing those files. '

'Accepted formats: .csv/.png/.jpeg/.jpg '

'or directory containing those.')

parser.add_argument('-l', '--ladder',

type=check_ladder,

metavar='<ladder-file>',

nargs='?', #single file

help='Path to ladder table file. Accepted format: '

'.csv',

required=True)

parser.add_argument('-m', '--meta',

type=check_meta,

metavar='<metadata-file>',

nargs='?', #single file

help='Path to metadata table file containing grouping '

'information for input file (e.g. age, sex, '

'disease). Accepted format: .csv',

required=False)

parser.add_argument('-n', '--name',

type=check_name,

metavar='<run-name>',

nargs='?', #single file

help='Name of your run/experiment. '

'Will define output folder name',

required=False)

parser.add_argument('-c', '--config',

type=check_config,

metavar='<config-file>',

nargs='?', # single file

help='Define nucleosomal fractions with this path to a configuration file containing custom '

'(nucleosome) intervals for statistics. '

'Accepted format: tab-separated text files (.txt)',

required=False)

parser.add_argument('-iv', '--interval',

type=check_interval,

metavar='<(start,step)>',

nargs='?', # single file

help='Auto-generate nucleosomal size intervals by providing (start,step), e.g. start at 100 and increase by 200 bp',

required=False)

parser.add_argument('-p', '--paired',

action="store_true",

default=False,

help='Perform paired statistical testing')

parser.add_argument('-un', '--unnormalized',

action="store_true",

default=False,

help='Do not perform min/max normalization. '

'ATTENTION: will be DNA-concentration sensitive.',

required=False)

parser.add_argument('-nt', '--normalize_to',

type=check_name,

metavar='<sample_name>',

nargs='?',

help='Name of the sample to normalize all values to. '

'ATTENTION: will be DNA-concentration sensitive.',

required=False)

parser.add_argument('-ml', '--marker_lane',

type=check_marker_lane,

metavar='<int>',

default=1,

help='Change the lane selected as the DNA marker/ladder, '

'default is first lane (1). Using this will force to use the '

'specified column even if other columns are called Ladder already.',

required=False)

parser.add_argument('-incl', '--include',

action="store_true",

default=False,

help='Include marker bands into analysis and plotting.',

required=False)

parser.add_argument('-cor', '--correct',

action="store_true",

default=False,

help='Perform advanced automatic marker lane detection in samples with '

'highly variant concentrations (e.g., dilution series), so that the marker borders will be determined '

'for each sample individually')

parser.add_argument('-cut', '--cut',

action="store_true",

default=False,

help='Limit violin plots to data range')

parser.add_argument("--verbose", help="increase output verbosity",

action="store_true")

parser.add_argument('-v', '--version', action='version', version=version)

#########################################################################

# Args to variables

#########################################################################

args = parser.parse_args()

save_dir = None

files_to_check = None

meta_dict = False

paired = False

normalize = True

normalize_to = False

correct = False

cut = False

nuc_dict = NUC_DICT

csv_path, ladder_path, meta_path, run_id, marker_lane \

= args.input, args.ladder, args.meta, args.name, args.marker_lane

marker_lane = marker_lane - 1 # transfer to 0-based format

if args.verbose:

logger = logging.getLogger()

logger.setLevel(logging.DEBUG)

if args.interval and args.config:

print("Cannot use both interval and nuc_dict arguments.")

exit(1)

if args.unnormalized and args.normalize_to:

print("Cannot use both --unnormalized and --normalize_to.")

exit(1)

if args.interval:

nuc_dict = args.interval

if args.config:

nuc_dict = args.config

if args.paired:

paired = True

if args.unnormalized:

normalize = False

if args.normalize_to:

normalize_to = args.normalize_to

if args.correct:

correct = args.correct

if args.correct and args.include:

print("Cannot use both --include and --correct.")

exit(1)

if args.cut:

cut = True

#########################################################################

# Decide: folder or single file processing

#########################################################################

if os.path.isdir(csv_path):

if not csv_path.endswith("/"):

csv_path = f"{csv_path}/"

print(f"--- Checking folder {csv_path}")

files_to_check = [f"{csv_path}{e}" for e in os.listdir(csv_path) if

e.endswith(tuple(ACCEPTED_FORMATS))]

######################################################################

# Multi-file metadata handling

######################################################################

meta_dict = generate_meta_dict(meta_path, files=files_to_check)

elif os.path.isfile(csv_path):

files_to_check = [e for e in [csv_path] if

e.endswith(tuple(ACCEPTED_FORMATS))]

if not files_to_check:

print(f"--- No valid file(s), only {ACCEPTED_FORMATS} accepted: "

f"{csv_path}")

exit(1)

#########################################################################

# Start the analysis

#########################################################################

for file in files_to_check:

# Optional: transform from image

if not file.endswith(".csv"):

# IMAGES GO HERE, then defines save_dir

signal_table, save_dir = analyze_gel(file, run_id=run_id,

marker_lane=marker_lane)

image_input = True

else:

# FILE ALREADY IN SIGNAL TABLE FORMAT

signal_table = file

image_input = False

if meta_dict:

meta_path = meta_dict[file]

# Start analysis

epg_analysis(signal_table, ladder_path, meta_path, run_id=run_id,

include_marker=args.include, image_input=image_input,

save_dir=save_dir, marker_lane=marker_lane,

nuc_dict=nuc_dict, paired=paired, normalize=normalize,

normalize_to=normalize_to, correct=correct, cut=cut)

#########################################################################

# Merge the results (for multi-file processing)

#########################################################################

if len(files_to_check) > 1:

# Get the all signal tables

signal_tables = [file for file in glob.glob(csv_path+"/*/signal_table.csv")]

merge_file = merge_tables(signal_tables, save_dir=csv_path+"merged.csv", meta_dict=meta_dict)

# And analyze all together

print("--- Multiple files - collecting & merging all results")

epg_analysis(merge_file, ladder_path, meta_path, run_id=run_id,

include_marker=args.include, image_input=False,

save_dir=save_dir, marker_lane=marker_lane,

nuc_dict=nuc_dict, paired=paired, normalize=normalize,

normalize_to=normalize_to, correct=correct, cut=cut)

# END OF SCRIPT