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A toolkit for navigating and analyzing gene expression datasets

Project description


A toolkit for navigating and analyzing gene expression datasets

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Find documentation here

Development Notes:

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


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


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


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]   

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