hiconet 0.5.1

Hierachical Community Network, data driven omics integration

Hieracrchical Community Network

for integration of multiple data types collected from a common group of subjects.

Terminology:

Study: Same as ImmPort "Study"

Project: a collection of data of one or more types. For multiple data types, common samples/subjects are expected.
    This is the unit HiCoNet works on - HiCoNet integrates DataMatrices within a DataSet
    A DataSet should have at least one Society of data


Society: one data type
at least one of each DataMatrix, FeatureAnnotation, ObservationAnnotation

DataMatrix: a data matrix of continuous values that represent a biological state or concentration, of the same data type.
    This can include different time points or treatments.
    This is the unit community detection is based on.

ObservationAnnotation: meta data on samples. This may include TimePoints and Treatments, often in biosample table from ImmPort DB
FeatureAnnotation: meta data on features

Key annotation variables: time point and treatment.
TimePoint:
Treatment:


Graph: a graph/network for relationships in the data (e.g. used in loom format, loompy.org).
Community: a group of features within a society that share a similar pattern.



Reusing
-------
The data structure is aligned with anndata (https://github.com/theislab/anndata) but transposed.
For future consideration, e.g. in loom format, one loom file = a Society; as meta data can differ for different data types.
Same goes for anndata.

requires

'PyYAML'
'numpy',
'scipy',
'pandas',
'sklearn',
'leidenalg',
'scanpy',
'igraph',
'fuzzywuzzy',

Note: python-igraph requires the C library igraph  
https://stackoverflow.com/questions/45667147/install-python-igraph-on-mac
I did pip3 install ~/Downloads/python-igraph-0.7.1-1.tar.gz
For a Docker or new install, both igraph and python-igraph are needed.

Test run

hiconet python3 -m hiconet.HiCoNet hiconet/datasets/SDY80