Nelle Varoquaux NelleV
NelleV
/ R - named matrix with gene_id and go_terms to list mapping gene_id to GO_term
Created
March 1, 2019 23:43
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| genes = structure(list(go_id = c("GO:0016787", "GO:0005634", "GO:0016798", | |
| "GO:0008152", "GO:0005737", "GO:0004553", "GO:0005975", "GO:1903561", | |
| "GO:0015929", "GO:0004563", "GO:0102148", "GO:0001934", "GO:0004672", | |
| "GO:0005524", "GO:0006468", "GO:0016020", "GO:0016021", "GO:0016740", | |
| "GO:0005886", "GO:0005634"), refseq_mrna = c("NM_001001333", | |
| "NM_001001333", "NM_001001333", "NM_001001333", "NM_001001333", | |
| "NM_001001333", "NM_001001333", "NM_001001333", "NM_001001333", | |
| "NM_001001333", "NM_001001333", "NM_001003817", "NM_001003817", | |
| "NM_001003817", "NM_001003817", "NM_001003817", "NM_001003817", | |
| "NM_001003817", "NM_001003817", "NM_001003817")), row.names = c(NA, |
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| { | |
| "metadata": { | |
| "name": "Lecture-1-Introduction-to-Python-Programming" | |
| }, | |
| "nbformat": 3, | |
| "nbformat_minor": 0, | |
| "worksheets": [ | |
| { | |
| "cells": [ | |
| { |
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| { | |
| "metadata": { | |
| "name": "Lecture-0-Scientific-Computing-with-Python" | |
| }, | |
| "nbformat": 3, | |
| "nbformat_minor": 0, | |
| "worksheets": [ | |
| { | |
| "cells": [ | |
| { |
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| ENG_PREFIXES = { | |
| -24: "y", | |
| -21: "z", | |
| -18: "a", | |
| -15: "f", | |
| -12: "p", | |
| -9: "n", | |
| -6: u"\u03bc", # Greek letter mu | |
| -3: "m", | |
| 0: "", |
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| import numpy as np | |
| import matplotlib | |
| from matplotlib import pyplot as plt | |
| from matplotlib.collections import PatchCollection | |
| from matplotlib import patches | |
| """ | |
| This code is meant to analyse where telomeres and centromers are most often |
NelleV
/ gist:969044
Created
May 12, 2011 17:45
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| """ | |
| ===================================================== | |
| A demo of the K Means clustering algorithm | |
| ===================================================== | |
| """ | |
| print __doc__ | |
| import numpy as np | |
| from scikits.learn.cluster import MiniBatchKMeans, KMeans |