API Overview¶

Quick overview of the Methods and Datasets available in ATHENA.

Methods¶

extract_centroids(so, spl[, mask_key, inplace])

Extract centroids from segementation masks.

build_graph(so, spl[, builder_type, …])

Build graph representation for a sample

`spatial`(so, spl, attr, *[, mode, node_size, …])	Visualisation of samples.
`napari_viewer`(so, spl, attrs[, censor, …])	Starts interactive Napari viewer to visualise raw images
`interactions`(so, spl, attr[, mode, …])	Visualise interaction results.
`ripleysK`(so, spl, attr, ids, *[, mode, …])	Plot results
`infiltration`(so, spl[, attr, step_size, …])	Visualises a heatmap of the featuer intensity.

`richness`(so, spl, attr, *[, local, …])	Computes the richness on the observation or the sample level
`abundance`(so, spl, attr, *[, mode, …])	Computes the abundance of species on the observation or the sample level.
`shannon`(so, spl, attr, *[, local, …])	Computes the Shannon Index on the observation or the sample level
`simpson`(so, spl, attr, *[, local, …])	Computes the Simpson Index on the observation or the sample level
`renyi_entropy`(so, spl, attr, q, *[, local, …])	Computes the Renyi-Entropy
`hill_number`(so, spl, attr, q, *[, local, …])	Computes the Hill Numbers on the observation or the sample level
`quadratic_entropy`(so, spl, attr, *[, …])	Computes the quadratic entropy, taking relative abundance and similarity between observations into account.

modularity(so, spl, community_id[, …])

Computes the modularity of the sample graph.

`interactions`(so, spl, attr[, mode, …])	Compute interaction strength between species.
`infiltration`(so, spl, attr, *[, …])	Compute infiltration score.
`ripleysK`(so, spl, attr, id, *[, mode, …])	Compute Ripley’s K as implemented by [1]_.

`imc`()	Pre-processed subset IMC dataset from *Jackson, H.W., Fischer, J.R., Zanotelli, V.R.T.
`mibi`()	Processed data from A Structured Tumor-Immune Microenvironment in Triple Negative Breast Cancer Revealed by Multiplexed Ion Beam Imaging. Cell.