orange-bioinformatics / docs / reference / obiProb.htm

<html>

<head>
<title>obiProb: Probability distributions and corrections</title>
<link rel=stylesheet href="style.css" type="text/css">
<link rel=stylesheet href="style-print.css" type="text/css" media=print>
</head>

<body>
<h1>obiProb Probability distributions and corrections</h1>
<p>obiProb provides the functionality to calculate probability distributions and corrections for multiple hypothesis testing.</p>

<h2>Binomial</h2>
<index name="Binomial">
<p>A class for computing binomial distribution probabilities. <a href="http://en.wikipedia.org/wiki/Binomial_distribution">Binomial distribution</a> is the discrete probability distribution of the number of successes in a sequence of n independent yes/no experiments, each of which yields success with probability p</p>
<p class=section>Methods</p>
<dl class=attributes>
	<dt>__call__(k, N, m, n)</dt>
	<dd>if m out of N experiments are positive return the probability that k out of n experiments are positive using the binomial distribution.
	(i.e. if p = m/N then return bin(n,k)*(p**k + (1-p)**(n-k)) where bin is the binomial coefficient)</dd>
	<dt>p_value(k, N, m, n)</dt>
	<dd>the probability that k or more tests are positive using the binomial distribution</dd>
</dl>

<h2>Hypergeometric</h2>
<index name="Hypergeometric">
<p>A class for computing hypergeometric distribution probabilities. <a href="http://en.wikipedia.org/wiki/Hypergeometric_distribution">Hypergeometric distribution</a> is a discrete probability distribution that describes the number of successes in a sequence of n draws from a finite population without replacement</p>
<p class=section>Methods</p>
<dl class=attributes>
	<dt>__call__(k, N, m, n)</dt>
	<dd>if m out of N experiments are positive return the probability that k out of n experiments are positive using the hypergeometric distribution.
	(i.e. return bin(m, k)*bin(N-m, n-k)/bin(N,n) where bin is the binomial coefficient)</dd>
	<dt>p_value(k, N, m, n)</dt>
	<dd>the probability that k or more tests are positive using the hypergeometric distribution</dd>
</dl>

<h2>FDR</h2>
<index name="FDR">
<p>A function for preforming <a href="http://en.wikipedia.org/wiki/False_discovery_rate">False Discovery Rate</a> correction on a ordered list of p-values</p>
<p class=section>Arguments</p>
<dl class=attributes>
	<dt>p_values</dt>
	<dd>an ordered list of p-values</dd>
	<dt>dependent (default False)</dd>
	<dd>use correction for dependent hypotheses</dd>
	<dt>m (default len(p_values))</dt>
	<dd>number of hypotheses tested</dd>
</dl>

<h2>Bonferroni</h2>
<index name="Bonferroni">
<p>A function for performing <a href="http://en.wikipedia.org/wiki/Bonferroni_correction">Bonferroni correction</a> on a list of p-values</p>
<p class=section>Arguments</p>
<dl class=attributes>
	<dt>p_values</dt>
	<dd>a list of p-values</dd>
	<dt>m (default len(p_values))</dt>
	<dd>number of hypotheses tested</dd>
</dl>
Tip: Filter by directory path e.g. /media app.js to search for public/media/app.js.
Tip: Use camelCasing e.g. ProjME to search for ProjectModifiedEvent.java.
Tip: Filter by extension type e.g. /repo .js to search for all .js files in the /repo directory.
Tip: Separate your search with spaces e.g. /ssh pom.xml to search for src/ssh/pom.xml.
Tip: Use ↑ and ↓ arrow keys to navigate and return to view the file.
Tip: You can also navigate files with Ctrl+j (next) and Ctrl+k (previous) and view the file with Ctrl+o.
Tip: You can also navigate files with Alt+j (next) and Alt+k (previous) and view the file with Alt+o.