heliy

BTs

• http://bt.xfsub.com/
• http://anisource.net/
• http://enbt.org/
• http://share.popgo.org/
• http://www.fmscg.com/
• https://share.dmhy.org/
• http://www.torrentdownloads.me/
• http://kat.cr/
• http://www.subtitlea.xyz/

heliy

import numpy as np
import cv2  #3.0.0-dev 
import math

r1 = 70
r2 = 30

ang = 60

d = 170

heliy

"""
7万个SNP的hw平横检验MAF的过滤

纯 python ver：
pypy 约 20s
python 约 25s

用 ctypes 调用 c ver:
pypy 约 18s
python 约 12s <- 比pypy还要好 

heliy

# coding:utf-8

"""
构建最大简约法进化系统发育树
使用 sh:
python sysevatree data > eva-tree.txt
"""

import sys

heliy

import sys
import re

id="id"
ns="namespace"
ia="is-a"
nps="node-ptrs"

def get_terms_namespaces(go_file):
    terms={}

heliy

import matplotlib.pyplot as plt
import numpy as np
import sys

def get_features(gb):
    context=open(gb,"r").read().split("FEATURES")[1].split("ORIGIN")[0].splitlines()
    dc={}
    for line in context:
        if line[5]==' ':
            continue

heliy

import sys

def putin(name,other,peers):
    if name in peers.keys():
        peers[name].append(other)
    else:
        peers[name]=[other]

def take_peers(filename,split_sign="\t"):
    inters=open(filename,'r').read().splitlines()

heliy

#coding:UTF-8
#!/usr/bin/python

import networkx as nx
import matplotlib.pyplot as plt

def cancergenes(filename="cancer_gene_census.tsv"):
    doms,recs=[],[]
    for line in open(filename,'r').read().split('\r'):
        cons=line.split("\t")

heliy

#coding:utf-8

import sys

#处理permutaion的阈值 返回SNPlist
def promusnp(mperm,p=0.001):
    f=open(mperm,"r")
    res=[]
    total=[]
    line=f.readline()

heliy

#coding:UTF-8
#!/usr/bin/python

#使用方法：
#python seqcutloc.py  fasta文件 序列 输出文件
#./seqcutloc.py fasta文件 序列 输出文件

#算法是通过将长序列按碱基切开 在拼接回原序列
#eg seq:ATAATCGGCGATTAATCGAAT  cut:AAT  
#切完后得到子序列 AT CGGCGATT CG 长度为2 8 2