Data Analysis

Data analysis toolbox for Multi-electrode patch clamp recordings. It is designed to supports both online and offline analysis by using shared libraries and data structure.

1. Data Curator

> openCurator()

2. Analysis Pipeline

%% Create the analysis project
% --------------------------------------------
clear;
[project, offlineAnalysisManager] = createAnalysisProject('Example-Analysis_01',...
    'experiments', {'101217Dc*Amp2'},...
    'override', true);
% open the project file
open(project.file)

%% Create a simple search tree definition
% --------------------------------------------
analysisFilter = struct();
analysisFilter.type = 'LightStepAnalysis';
analysisFilter.buildTreeBy = {'displayName', 'intensity', 'stimTime'};
analysisFilter.displayName.splitValue = {'Light Step'};
analysisFilter.stimTime.featureExtractor = {@(analysis, epochGroup, analysisParameter)...
     sa_labs.analysis.common.extractors.psthExtractor(...
     analysis,...
     epochGroup,...
     analysisParameter)...
    };

%% Build the tree based on the tree definition
% --------------------------------------------
buildAnalysis('Example-Analysis_01', analysisFilter)

3. Tree Browser

> openTreeBrowser('Example-Analysis_01')

Usage

GitBook doc

• Introduction
• Getting Started
• Parsing your data
  • Data curator features
• Building analysis pipeline
  • Creating feature extractor
• Visualizing your results
• Dependency

Folder organization

• The core analysis framework lives in sa-labs-analysis-core and facilitates the data storage and sharing.
• The common analysis functions will be in sa-labs-util
• The master configuration for managing cell class, cell types, etc are present in sa-labs-analysis-preference
• It follows maven style source code organization
• All the dependency will be present in toolbox folder

MIT License

Copyright (c) 2017 Schwartz-AlaLaurila-Labs