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multivis is a data visualisation package that produces both static and interactive visualisations targeted towards the Omics community.

Project description

<img src=”cimcb_logo.png” alt=”drawing” width=”400”/>

# multivis multivis package containing the necessary tools for the visualisation of correlated data.

## Installation

### Dependencies multivis requires: - Python (>=3.5) - NumPy (>=1.12) - Pandas - Matplotlib - Seaborn - Networkx - SciPy - Scikit-learn - tqdm

### User installation The recommend way to install cimcb_vis and dependencies is to using conda: `console conda install -c brett.chapman multivis ` or pip: `console pip install multivis ` Alternatively, to install directly from github: `console pip install https://github.com/brettChapman/multivis/archive/master.zip `

### API For further detail on the usage refer to the docstring.

#### multivis - [Edge](https://github.com/brettChapman/multivis/blob/master/multivis/Edge.py): Generates dataframe of edges prior to visualisation. - [Network](https://github.com/brettChapman/multivis/blob/master/multivis/Network.py) Generates dataframe of edges, with network parameters and a networkx graph prior to visualisation. - [edgeBundle](https://github.com/brettChapman/multivis/blob/master/multivis/edgeBundle.py): Generates necessary Json structure and produces Hierarchical edge bundle plot. - [plotNetwork](https://github.com/brettChapman/multivis/blob/master/multivis/plotNetwork.py): Static spring plot using pygraphviz and networkx. - [forceNetwork](https://github.com/brettChapman/multivis/blob/master/multivis/forceNetwork.py): Interactive force-directed network which inherits data from the networkx graph - [clustermap](https://github.com/brettChapman//multivis/blob/master/multivis/clustermap.py): Clustered heatmap with dendrograms. - [polarDendrogram](https://github.com/brettChapman/multivis/blob/master/multivis/polarDendrogram.py): Polar dendrogram

#### multivis.utils - [mergeBlocks](https://github.com/brettChapman/multivis/blob/master/multivis/utils/mergeBlocks.py): Merges multiply diffent blocks into a single peak table and data table. - [range_scale](https://github.com/brettChapman/multivis/blob/master/multivis/utils/range_scale.py): Scales a range of values between user chosen values. - [corrAnalysis](https://github.com/brettChapman/multivis/blob/master/multivis/corrAnalysis.py): Correlation analysis with Pearson, Spearman or Kendall’s Tau. - [cluster](https://github.com/brettChapman/multivis/blob/master/multivis/utils/spatialClustering.py): Clusters data using a linkage cluster method. If the data is correlated the correlations are first preprocessed, then clustered, otherwise a distance metric is applied to non-correlated data before clustering.

### License multivis is licensed under the ___ license.

### Authors - Brett Chapman - https://scholar.google.com.au/citations?user=A_wYNAQAAAAJ&hl=en

### Correspondence Dr. Brett Chapman, Post-doctoral Research Fellow at the Centre for Integrative Metabolomics & Computational Biology at Edith Cowan University. E-mail: brett.chapman@ecu.edu.au

### Citation If you would cite cimcb_vis in a scientific publication, you can use the following: ___

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0.1.4

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