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def series_matrix2csv(matrix_url, prefix=None):
    """
    matrix_url: gziped URL with GEO series matrix.
    """
    import gzip
    import pandas as pd

    os.system("wget {}".format(matrix_url))
    filename = matrix_url.split("/")[-1]

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from looper.models import Project
import argparse
import os
import pandas as pd
import re
import string
import textwrap


def get_colors(level, pallete="gist_rainbow", nan_color=[0.5, 0.5, 0.5]):

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# By Jörg Mensche

import matplotlib.pyplot as plt  # basic plot functionalities
import seaborn as sns
# more advanced plotting
import scipy.stats as sc
# random number generator
# generate the x-mas tree:
all_branches = []
balls_x = []

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from pipelines.models import Project
import os
import pandas as pd
import pysam


# Start project
prj = Project("metadata/project_config.yaml")
prj.add_sample_sheet()

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#! /usr/bin/env python

import argparse
import pandas as pd
import json
import requests


default_gene_set_libraries = [
    'GO_Biological_Process_2015',

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Introduction to linux command line/ipython/git/R for bioinformatics:

• https://github.com/biom262/biom262-2016
• https://github.com/ricket-sjtu/bi028
• https://github.com/YeoLab/single-cell-bioinformatics/
• https://github.com/YeoLab/single-cell-bioinformatics/tree/master/notebooks
• https://github.com/ltminty/Bioinformatics-and-R/blob/master/Rbioinformatics.ipynb

RNA-seq:

• https://github.com/Caroldm/RNA-Seq-Tutorial---Jupyter-notebook/blob/master/RNAseq%20tutorial.ipynb

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#!/usr/bin/env python
import csv
import sys

# usage:
# samtools view -h file.bam | shift_reads.py genome | samtools view -S -b - | samtools sort - file.shifted

def getChrSizes(chrmFile):
    """
    Reads tab-delimiter file with two rows describing the chromossomes and its lengths.

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def enrichr(dataframe, gene_set_libraries=None, kind="genes"):
    """
    Use Enrichr on a list of genes (currently only genes supported through the API).
    """
    import json
    import requests
    import pandas

    ENRICHR_ADD = 'http://amp.pharm.mssm.edu/Enrichr/addList'

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# I just need to have these somewhere to remember them later

for F in `find . | grep -e 'CM[0-9]\{2,\}s'`
do
    echo $F $(echo $F | sed 's/CM\([0-9]\{2,\}\)s/CM\1-/g')
    mv $F $(echo $F | sed 's/CM\([0-9]\{2,\}\)s/CM\1-/g')
done

for F in `find . | grep -e '_[1-2]_' | grep -v PBMC`
do

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import numpy as np
import pandas as pd


class DifferentialRegions(object):
    """
    Compute two-tailed empirical p-value for difference between values of two variables.
    """
    def __init__(self, df, a, b, permutations=100, alpha=0.05, correct=True):
        super(DifferentialRegions, self).__init__()