Kernel: Python 3 (Anaconda)

pods in Anaconda's Python 3

In [1]:

import pandas as pd
import sys
sys.path.append('/usr/local/lib/python3.5/dist-packages/')

In [2]:

import pods
pods.datasets.overide_manual_authorize = True # dont ask to authorize
data = pods.datasets.singlecell() # get the data
data.keys()

dict_keys(['labels', 'size', 'urls', 'details', 'Y', 'genes', 'citation', 'license', 'files', 'info'])

In [3]:

print(data['citation'])
print(data['details'])

Guoji Guo, Mikael Huss, Guo Qing Tong, Chaoyang Wang, Li Li Sun, Neil D. Clarke, Paul Robson, Resolution of Cell Fate Decisions Revealed by Single-Cell Gene Expression Analysis from Zygote to Blastocyst, Developmental Cell, Volume 18, Issue 4, 20 April 2010, Pages 675-685, ISSN 1534-5807, http://dx.doi.org/10.1016/j.devcel.2010.02.012. (http://www.sciencedirect.com/science/article/pii/S1534580710001103) Keywords: DEVBIO
qPCR TaqMan array single cell experiment in mouse. The data is taken from the early stages of development when the Blastocyst is forming. At the 32 cell stage the data is already separated into the trophectoderm (TE) which goes onto form the placenta and the inner cellular mass (ICM). The ICM further differentiates into the epiblast (EPI)---which gives rise to the endoderm, mesoderm and ectoderm---and the primitive endoderm (PE) which develops into the amniotic sack. Guo et al selected 48 genes for expression measurement. They labelled the resulting cells and their labels are included as an aide to visualization.

In [4]:

data['Y'].Actb.plot()

<matplotlib.axes._subplots.AxesSubplot at 0x7fbc74b89518>

In [0]: