xiucz xiucz

## python argparse subcommand subparsers.py
import argparse
from mock import Mock

m = Mock()

parser = argparse.ArgumentParser()
subparsers = parser.add_subparsers()

query_group = subparsers.add_parser('query')
add_group = subparsers.add_parser('add')

## ensembl_vep_86_with_offline_cache.md

      
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                ckandoth
                / ensembl_vep_86_with_offline_cache.md
            
            
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              July 15, 2021 16:26
            
              
                Install Ensembl's VEP v86 with various caches for running offline
              
          
    Ensembl's VEP (Variant Effect Predictor) is popular for how it picks a single effect per gene as detailed here, its CLIA-compliant HGVS variant format, and Sequence Ontology nomenclature for variant effects.
To follow these instructions, we'll assume you have these packaged essentials installed:
## For Debian/Ubuntu system admins ##
sudo apt-get install -y build-essential git libncurses-dev

## For RHEL/CentOS system admins ##
sudo yum groupinstall -y 'Development Tools'
sudo yum install -y git ncurses-devel

  
## new_gist_file.md

      
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                hongyangqin
                / new_gist_file.md
            
            
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              March 11, 2021 08:05
            
              
                震惊！原来命令行还可以这么玩？！
              
          
引言
 你是否：

好奇过命令行里那些花里胡哨的进度条是如何实现的？
好奇过Spring Boot为什么能够打印五颜六色的日志？
好奇过Python或者PHP等脚本语言的交互式命令行是如何实现的？
好奇过Vim或者Emacs等在Terminal中的编辑器是怎么实现的？

如果你曾经好奇过，或者被这段话勾起了你的好奇心，那么你绝对不能错过这篇文章！
背景通过本文你可以学到：

  
## vepvcf_to_pandas.py
# -*- coding: utf-8 -*-
"""
Created on Mon Mar  5 14:21:42 2018

@author: nilesh-tawari
email: tawari.nilesh@gmail.com
GitHub: https://github.com/nilesh-tawari
"""
from __future__ import print_function
import os

## coverage_tests.md

      
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                cmdcolin
                / coverage_tests.md
            
            
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              November 23, 2023 02:43
            
              
                coverage comparisons
              
          
    Coverage tests for different bioinformatics tools

this document looks at the depth at a particular position in a BAM file a user sent me, at position 14712.
I discuss in the comments what settings might be related to the coverage differents
High level summary

The major variables between tools and the scores they report for coverage are related to the filters that are by default applied. Tools that report a lower score generally include duplicate and qc vendor fail filters by default. In this test at a particular position, these tools reported 74 reads.
Scores that are higher have no filters applied. In this test at a particular position, these tools reported 423.

  
## sub-sub-command.py
"""
Example of using sub-parser, sub-commands and sub-sub-commands :-)
"""

import argparse


def main(args):
    """
    Just do something

## inspect-claims.sh
#!/usr/bin/env bash

set -o errexit
set -o nounset
set -o pipefail

# Constants
RESET='\033[0m'
GREEN='\033[38;5;2m'
RED='\033[38;5;1m'
	import argparse
	from mock import Mock

	m = Mock()

	parser = argparse.ArgumentParser()
	subparsers = parser.add_subparsers()

	query_group = subparsers.add_parser('query')
	add_group = subparsers.add_parser('add')
	# -- coding: utf-8 --
	"""
	Created on Mon Mar 5 14:21:42 2018

	@author: nilesh-tawari
	email: tawari.nilesh@gmail.com
	GitHub: https://github.com/nilesh-tawari
	"""
	from __future__ import print_function
	import os
	"""
	Example of using sub-parser, sub-commands and sub-sub-commands :-)
	"""

	import argparse


	def main(args):
	"""
	Just do something
	#!/usr/bin/env bash

	set -o errexit
	set -o nounset
	set -o pipefail

	# Constants
	RESET='\033[0m'
	GREEN='\033[38;5;2m'
	RED='\033[38;5;1m'