XPRESStools 0.0.4b0

A toolkit for navigating and analyzing gene expression datasets

A toolkit for navigating and analyzing gene expression datasets

Find documentation here

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Development Notes:

XPRESStools is still in beta production
Interactive scatter plotting functions are not currently tested
XPRESStools supports Python 2.7 and >=3.5

Citation:

Berg, JA (2019). XPRESSyourself suite: Gene expression processing and analysis made easy. https://github.com/XPRESSyourself. DOI: 10.5281/zenodo.2581692.

Installation:

pip install xpresstools

Other Requirements:

• Tested on 64-bit Linux, compatible with Mac OS X
• Python3 is recommended
  • Current test cases build to:
    • Python2.7
    • Python3.5
    • Python3.6
    • Python3.7
• If PyPi and Conda are not already installed, these should be installed
• If using this package to perform batch effect normalization or differential expression analysis, you must install R
• If using the interactive notebook provided, Jupyter needs to be installed if not already

QuickStart:

Download the repository and modify the interactive Jupyter notebook to get started quick!
Read the instructions as you navigate through the code blocks for a guide on how to use the example code
Code blocks are run by selecting the block and pressing Shift + Enter
See documentation for more detailed instructions

Important Notes:

• If working with XPRESStools within an interactive notebook (i.e. Jupyter Notebook, Atom Hydrogen, etc), you must include the following line of code after importing XPRESStools

import XPRESStools as xp
%matplotlib inline

• Assumes all dataframes are columns=samples and rows=genes (except in certain cases, see documentation for help)

>>> geo.head()
name       GSM523242  GSM523243  GSM523244  GSM523245  GSM523246  GSM523247    ...     
1007_s_at    8.98104    8.59941    8.25395    8.72981    8.70794    8.10693    ...       
1053_at      5.84313    6.59168    8.27881    6.64005    4.65107    7.19090    ...       
121_at       6.17189    5.73603    5.55673    5.69374    6.77618    5.84524    ...       
1294_at      6.97009    6.80003    5.56620    7.43816    7.36375    5.85687    ...       
1405_i_at   10.24611   10.13807    8.84743    9.72365   10.42940    9.17510    ...   

[5 rows x 145 columns]