HC StratoMineR

HC StratoMineR is a powerful web-based data analytics platform that guides the user through a well-validated, data mining workflow. The intuitive decision-supportive software gives scientists the ability to mine multi-well plate-derived multi-parametric data sets, even if they have limited experience with bioinformatics or biostatistics.

The platform gives the user the ability to leverage the power of high content data analysis for the phenotypic identification and classification of hits from high content chemical and functional genomics screens. It is also suitable for the analysis of traditional high throughput screening data. HC StratoMineR has been described in the journal Assay and Drug Development Technologies.

Cost effective subscription plans are available for Personal use and Academic groups. Core facilities and SME’s can benefit with HC StratoMineR Professional. HC StratoMineR Enterprise is the power solution for large organizations that have many users or wish to process larger, high resolution data sets.

Subscribers access our services to a private, dedicated cloud deployment at mycompany.stratominer.com, with options for enhanced security measures such as IP address whitelists.

Register now for a free 30-day trial subscription to HC StratoMineR

The HC StratoMineR workflow

Data Upload

Upload numeric data in text files in a standard format. A choice of delimiters is possible.

Meta Settings

Separate analytical features from metadata such as plate and well identifiers. Both numeric and alphabetic well identifiers can be used.

Variable Selection

Decision supported elimination of features that are not useful, including those that are non-numeric, discrete, have no variation across the data set; or those that contain excessive amounts of missing data.

Quality Control

Define an experimental plate map and perform quality control on the raw data using a wide variety of data visualizations.

Plate Normalization

Carry out data normalization using one of a variety of methods. Data transformation and standardization, can also be performed.

Data Reduction

Account for missing data with multiple imputation methods, and perform principal component analysis or common factor analysis to reduce the data complexity. This gives insight into the biological meaning of the features.

Hit Identication

Phenotypic hit selection using multiple selected features, common factors or principal components. Selection can be carried out using unsupervised methods or in a supervised fashion using artificial intelligence based on controls wells or user defined sample wells.

Data Clustering

Hits are grouped using hierarchical clustering and phenotypic similarity analysis. Visualizations and processed data can then be exported.

Reporting

All important settings and visualizations generated, are presented in an easy-to-export format.

Omta, Wienand A., Roy G. van Heesbeen, Romina J. Pagliero, Lieke M. van der Velden, Daphne Lelieveld, Mehdi Nellen, Maik Kramer et al. "HC StratoMineR: A Web-Based Tool for the Rapid Analysis of High-Content Datasets." ASSAY and Drug Development Technologies 14, no. 8 (2016): 439-452.

Read the paper

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