peterk87

from scipy.spatial.distance import *
from scipy.cluster.hierarchy import *
import pandas as pd
import numpy
import matplotlib as plt
from matplotlib.pylab import figure
import pylab as pl
import pp

def num_clusters(hc, d):

peterk87

## {{{ http://code.activestate.com/recipes/578175/ (r1)
### hierarchical_clustering.py
#Copyright 2005-2012 J. David Gladstone Institutes, San Francisco California
#Author Nathan Salomonis - [email protected]

#Permission is hereby granted, free of charge, to any person obtaining a copy 
#of this software and associated documentation files (the "Software"), to deal 
#in the Software without restriction, including without limitation the rights 
#to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 
#copies of the Software, and to permit persons to whom the Software is furnished 

peterk87

def chunk_seq(seq_name, sequence, chunk_size, chunk_increment):
    """
    Chunk up a sequence and return a list of tuples with the chunked up
    sequences and new sequence names with the position of the chunk in the
    original sequence.

    Args:
        seq_name: Sequence name.
        sequence: Nucleotide or amino acid sequence that is to be chunked up.
        chunk_size: Size of chunks (e.g. 30 bp)

peterk87

/*coursera dark CSS style*/
/*URL on domain: coursera.org*/
a {
	color: rgb(140, 178, 228) !important;
}
body,.row-fluid .span9,.row-fluid .span3,.row-fluid, div, li, ul, ol, .course-navbar-list .course-navbar-item.active a {
	background-color: rgb(31, 31, 31) !important;
	color: rgb(170,170,170) !important;
}

peterk87

/*feedly.com dark CSS theme*/
.placeholder{
  visibility: hidden !important;
 }
.area,.summary, div, .light {
 background-color: rgb(30,30,30) !important;
 color: rgb(200,200,200) !important;
}
a {
 color: #78B7F5 !important;

peterk87

<style type="text/css">body { padding-top: 25px;}</style>
<div class="navbar navbar-fixed-top navbar-inverse" id="tool" data-nav-value="dataview">
  <div class="navbar-inner">
    <div class="container-fluid">
      <a class="brand" href="#" data-value="dataview">Navigation bar title for whatever app!</a>
      <div class="nav-collapse">
        <ul class="nav">
          <li><a href="#" data-value="dataview">View</a></li>
          <li class="dropdown">
            <a href="#" class="dropdown-toggle" data-toggle="dropdown">EDAT<b class="caret"></b></a>

peterk87

# Printing stack trace and continuing after error occurs in R
# http://stackoverflow.com/questions/1975110/printing-stack-trace-and-continuing-after-error-occurs-in-r
# Bob Albright
# I wrote this code about a week ago to help me track down errors that come primarily from non-interactive R sessions. It's still a little rough, but it prints a stack trace and continues on. Let me know if this is useful, I'd be interested in how you would make this more informative. I'm also open into cleaner ways to get this information.

options(warn = 2, keep.source = TRUE, error = 
  quote({ 
    cat("Environment:\n", file=stderr()); 

    # TODO: setup option for dumping to a file (?)

peterk87

@article{olson_limited_2007,
	title = {Limited genetic diversity in \emph{{Salmonella enterica}} Serovar {Enteritidis} {PT13}},
	volume = {7},
	copyright = {2007 Olson et al; licensee {BioMed} Central Ltd.},
	issn = {1471-2180},
	url = {http://www.biomedcentral.com/1471-2180/7/87/abstract},
	doi = {10.1186/1471-2180-7-87},
	abstract = {Salmonella enterica serovar Enteritidis has emerged as a significant foodborne pathogen throughout the world and is commonly characterized by phage typing. In Canada phage types ({PT)} 4, 8 and 13 predominate and in 2005 a large foodborne {PT13} outbreak occurred in the province of Ontario. The ability to link strains during this outbreak was difficult due to the apparent clonality of {PT13} isolates in Canada, as there was a single dominant pulsed-field gel electrophoresis ({PFGE)} profile amongst epidemiologically linked human and food isolates as well as concurrent sporadic strains. The aim of this study was to perform comparative genomic hybridization ({CGH)}, {DNA} sequen

peterk87

@article{kruczkiewicz_mist,
	title = {{MIST}: a tool for rapid \emph{in silico} generation of molecular data from bacterial genome sequences},
	author = {Kruczkiewicz, Peter and Mutschall, Steven and Barker, Dillon and Thomas, James and Van Domselaar, Gary and  Gannon, Victor P.J. and Carrillo, Catherine D. and Taboada, Eduardo N.},
	year = {2013},
	location = {Barcelona, Spain},
	pages = {316--323},
	isbn = {978-989-8565-35-8},
	publisher = {SCITEPRESS},
	journal = {Proceedings of Bioinformatics 2013: 4th International Conference on Bioinformatics Models, Methods and Algorithms}
}

peterk87

/*dark theme CSS for NCIX.com*/
div, table, b, td, tr, form, h1, h2, h3, h4, h5, input, select, span {
background: none !important;
}

div, table, b, td, tr, form, h1, h2, h3, h4, h5, textarea, input, select, span {
  color: rgb(170,170,170) !important;
  background-color: rgb(30,30,30) !important;
  
}