zero323

#! /usr/bin/env python
import glob
from collections import Counter
prefix = 'gene_'

def get_files_names(glob_pattern = '*.txt'):
    return(glob.glob(glob_pattern))

def get_jaspar_bits(files_names):
    files_refs = map(lambda x: open(x), files_names)

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library("biomaRt")

getPromoterSequence <- function(geneID, flankLeft, mart) {
    return(getBM(
      attributes = c("ensembl_gene_id",'coding_transcript_flank'),
      checkFilters=FALSE, filters = c('ensembl_gene_id','upstream_flank'),
      values=list(geneID, flankLeft),
      mart=mart, verbose=FALSE))
}

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# -*- coding: utf-8 -*-
import os
import json
import urllib2

DATA_URL = 'https://dl.dropboxusercontent.com/s/blq0xxvx5asfnkl/combined.json?token_hash=AAGZxGLemmo09Ib-_P6kyjnzEoTzTMcIVjJ5b95zdb0Eqw&dl=1'
DATA_FILE = 'combined_sample.json'


class ChemblStatsClient:

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set encoding=utf8
set nocompatible
set paste
set expandtab
set textwidth=0
set tabstop=4
set softtabstop=4
set shiftwidth=4
set autoindent
set backspace=indent,eol,start

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__author__ = 'zero323'

from rdkit import DataStructs
from rdkit.Chem.Fingerprints import FingerprintMols
from rdkit import Chem
from indigo import Indigo
import pybel
import time
import cPickle
import numpy as np

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killall mongod
killall mongos
rm -R s0 s1 cfg logs
mkdir -p s0/a s0/b s0/c s1/a s1/b s1/c
mkdir -p cfg/a cfg/b cfg/c
mkdir logs

mongod  --shardsvr --replSet rs0 --dbpath s0/a --port 27001 --smallfiles --oplogSize 50 --fork --logpath logs/s0a.log
mongod  --shardsvr --replSet rs0 --dbpath s0/b --port 27002 --smallfiles --oplogSize 50 --fork --logpath logs/s0b.log
mongod  --shardsvr --replSet rs0 --dbpath s0/c --port 27003 --smallfiles --oplogSize 50 --fork --logpath logs/s0c.log

zero323

library(GenomicRanges)

gr1 <- GRanges(
    "chr1",  strand="+",
    IRanges(start = c(100, 200), end =c(200, 300))
)

gr2 <- GRanges(
    "chr1",  strand="+",
    IRanges(start = 0, end = 250)

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library(GenomicRanges)

interactions <- GRanges()

# GRanges with 0 ranges and 0 metadata columns:
#   seqnames    ranges strand
#      <Rle> <IRanges>  <Rle>
#  ---
#  seqlengths:

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#' @param datain expression data with gene id in the first column
#' @param ncontrol number of samples from control
#' @param ntreatment number of samples from treatment
#' @param control indices of control samples
#' @param treatment indices of treatment samples
#'
random_chdir <- function(datain, ncontrol, ntreatment, control, treatment, randomize_gamma=FALSE) {
    # Take ncontrol samples form control
    control <- sample(control, ncontrol)
    # and ntreatment from treatment

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library(shiny)

predict <- function(foo_or_bar) { ifelse(foo_or_bar, 'Foo', 'Bar') } 

runApp(shinyApp(
    
    ui = shinyUI(fluidPage(
        fluidRow(
            column(12, checkboxInput('foo_or_bar', 'Foo or bar?'), textOutput('text'))
        )