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from multiprocessing import Pool

DEFAULT_VALUE = thing

class MapRunner(object):
  def __init__(self):
    p = pool(i,init_globals)

  def init_globals():
    global g1

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BASE_URL = 'http://access.alchemyapi.com/calls'
SENTIMENT_URL = "/text/TextGetTargetedSentiment"
API_KEY = "add it here"

try:
    from urllib.request import urlopen
    from urllib.parse import urlparse
    from urllib.parse import urlencode
except ImportError:
    from urlparse import urlparse

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#! /usr/bin/python
##############################################################################
#
#    a deployment assistent for projects with more then one deployment target
#
###############################################################################

import os
import sys

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@staticmethod
def timezoneDiffFromGMT(lat, lon):
    lon_degrees_per_timezone_hour = 360/24
    utc_centeral_lon_degrees = lon_degrees_per_timezone_hour * 12
    lon_degrees_from_utc = lon - utc_centeral_lon_degrees
    return lon_degrees_from_utc / lon_degrees_per_timezone_hour

def isNight(lat,  lon):
    hour_at_location = time.gmtime().tm_hour + timezoneDiffFromGMT(lat, lon)
    return not 5 < hour_at_location < 22 #set aprox day start and day end times as you like

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from elasticsearch import Elasticsearch
import json
from datetime import datetime

class ElasticsearchLogger(object):
    def __init__(self, index_name='my_index',elasticsearch_host='my_es_host'):
        #connect to our cluster
        self._es = Elasticsearch([{'host': elasticsearch_host, 'port': 9200}])
        self._index_name = index_name

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language: c
compiler: gcc
sudo: required
install: make clean && make
before_script:
  - git clone https://github.com/antirez/redis.git
  - cd redis
  - make
  - sudo pip install redis
  - cd ..

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Sentieon script for basic DNAseq (FastQ to VCF) as instructed on https://support.sentieon.com/manual/DNAseq_usage/dnaseq/

How To Use This Script

• Put it wherever, it's all based on absolute paths
• Open it in an editor of your choosing
• Fill in all the in the exports section
• Change (or leave as is) the bwt_max_mem and NUMBER_THREADS env vars to suite your needs
• Make sure to raise file descriptor limits to the allowed max by running ulimit -n unlimited
• Run it

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#! /bin/sh

export SENTIEON_PROJECT_HOME=/home/ubuntu/sentieon 
export SENTIEON_LICENSE=$SENTIEON_PROJECT_HOME/emedgene_eval.lic
export SENTIEON_BIN=$SENTIEON_PROJECT_HOME/sentieon-genomics-201808.03/bin/sentieon

export REFERENCE=/opt/data/ref/Human/Hg19/genome_ref/hg19.fa #$SENTION_DATA_DIR/reference/hg19/hg19.fa

export BED_FILE=/opt/data/input/UNIQUE_Agilent_130_5.bed

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#! /usr/bin/python3
from github import Github, GithubException
from prettytable import PrettyTable
import sys

def printProgressBar (iteration, total, prefix = 'Progress:', suffix = 'Complete', total_length = 78, fill = '█'):
    percent = 100 * (iteration / float(total))
    percent_str = ("{0:.1f}").format(percent)
    length = total_length - len(prefix) - len(suffix) - len (percent_str)
    filledLength = int(length * iteration // total)

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VARCALLER Statistics Package

• This directory contains tools and scripts for automated, local analysis and evaluation of varcaller change to a pipeline.
• As time progresses, these tools should allow R&D departments add, remove, perform parameter searches and develop quality functions without needing their scientific department.

Usage

• run GIAB son sample through the varcaller
• get the bam.bed file from the mapper
• get the current output vcf of the pipeline