"NeuroPath2Path: Classification and elastic morphing between neuronal arbors using path-wise similarity" - Tamal Batabyal, Barry Condron, Scott T. Acton.
This tool computes morphological similarity between a pair of neurons, provides a visualization framework of contnuous morphing between neurons.
_________________________ NeuroPath2Path ________________________
- Set the Directory of data.
Open neuroClassifyInterclass.m (similarly neuroClassifyIntraclass.m for intraclass classification). Set the newpath as the path where the directory containing the dataset is present.
- Run jobClassifyInter.slurm (similarly jobClassifyIntra.slurm). The default parameter values are given. User can choose different parameters by opening the .slurm file and changing the arguments of neuroClassifyInterclass().
Ex: neuroClassifyInterclass(0.2,15,5,3,9) indicates that this instance of experiment tests on the 20% perclass-randomly sampled data, while rest of the data are used to represent all classes. As mentioned in the paper, we use the number of paths, which is a global feature, of a test neuron (from 20% data) to find the candidates of neurons (from 80% data) to perform majority voting. The binwidth of perclass-path distribution is 15. For a test neuron, the closest candidates are searched through step length 5 (search space reduction) and continue till +/- (95) paths from the number of paths of the test neuron. For example, if a test neuron has 60 rooted paths, we searched the possible candidates from 80% of data, which have numbers of paths ranging from 60-(95)=15 to 60+(9*5)=105. Majority vote is performed on 3 nearest neighbors.
For details, please follow the paper.
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Once the job is completed, open OUTPUT.log
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The python version is under preparation
% __________File descriptions
% classification readinput : Read swc files from directory computenP2P : Compute path features (User can add more features)
computeDSTInter & Intra : Path alignment + distance between paths
munkres + distanceNeuronNew : Distance between a pair of neurons and path correspondence
jobClassifyInter and jobClassifyIntra : job script files to run in cluster
neuroClassifyInterclass and neuroClassifyIntraclass: main files
% importance weights jobIW : jobscript to get the importance weights
getFeatureWeights : Obtain the importance weights