wdecoster

#!/usr/bin/Rscript

library('SKAT')

cat("WARNING: this script doesn't perform a sanity check on your data and therefore it's your own responsibility to provide correct input data.\n")
args = unlist(strsplit(commandArgs(trailingOnly = TRUE)," "))
basename = strsplit(basename(args), "\\.")[[1]][1]
dat <- read.table(args[1], header=TRUE, stringsAsFactors=FALSE) 
phen = ifelse(dat$PHENOTYPE == 2, 0, 1) #Convert affected = 2 to affected = 0
geno = as.matrix(dat[,-c(1:6)])

wdecoster

genderPlots <- function(genders, counts, samples) {
	# Making orthogonal gender-specific plot based on genes from https://www.ncbi.nlm.nih.gov/pubmed/23829492
    # coloured by expected gender (genders vector)
    # adding labels based on sample names (samples vector)
	maleGenes <- c('ENSG00000129824', 'ENSG00000198692', 'ENSG00000067048', 'ENSG00000012817')
	femaleGenes <- c('ENSG00000229807')
	if (any(maleGenes %in% rownames(counts))){
		maleCounts <- (rowSums(t(counts[rownames(counts) %in% maleGenes,])) / colSums(counts)) * 1000000
	} else {
		maleCounts <- rep(0, length(genders))

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genderPlots <- function(genders, counts, samples) {
	# Making orthogonal gender-specific plot based on genes from https://www.ncbi.nlm.nih.gov/pubmed/23829492
	maleGenes <- c('ENSG00000129824', 'ENSG00000198692', 'ENSG00000067048', 'ENSG00000012817')
	femaleGenes <- c('ENSG00000229807')
	if (any(maleGenes %in% rownames(counts))){
		maleCounts <- rowSums(t(counts[rownames(counts) %in% maleGenes,]))
	} else {
		maleCounts <- rep(0, length(genders))
	}
	if (any(femaleGenes %in% rownames(counts))){

wdecoster

# wdecoster

import sys
import pysam
import os
import concurrent.futures as cfutures
import glob
import matplotlib.pyplot as plt

wdecoster

"""
Modified and extended from https://stackoverflow.com/q/7479442/6631639
"""

from os import urandom
import random
import string
import pyperclip
from argparse import ArgumentParser

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# wdecoster
"""
Reads from stdin, writes to stdout.
"""

from __future__ import print_function
from Bio import SeqIO
from argparse import ArgumentParser
import sys

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"""
based on https://neuroscience.telenczuk.pl/?p=331
"""

import svgutils.transform as sg


class Svg(object):
    "svg files with a data object (the svg), width, height and coordinates"

wdecoster

"""
based on:
https://stackoverflow.com/a/451580/6631639
https://kanoki.org/2017/07/12/merge-images-with-python/
https://stackoverflow.com/a/16377244/6631639
https://stackoverflow.com/a/41887497/6631639
"""

import numpy as np
from PIL import Image, ImageFont, ImageDraw

wdecoster

from Bio import SeqIO
import sys


def codonize(seq):
    """Split a string in codons per 3 characters."""
    return [seq[i:i + 3] for i in range(0, len(seq), 3)]


def check_codon(fasta, codon="TTA"):

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def stream_fastq_full(fastq, threads):
    '''
    Extract from a fastq file:
    -readname
    -average and median quality
    -read_lenght
    '''
    with cfutures.ThreadPoolExecutor(max_workers=threads) as executor:
        for results in executor.map(extract_all_from_fastq, SeqIO.parse(fastq, "fastq")):
            yield results