PRECISION.array

'PRECISION.array' is an R package designed for the evaluation of data normalization methods in the context of sample classification, with a focus on microRNA microarray datasets. This package is particularly useful for researchers working with microarray data who want to assess the performance of various data normalization techniques.
Key features of 'PRECISION.array' include:
Simulated Paired Datasets: The package provides a re-sampling-based algorithm that can generate additional paired datasets. These simulated datasets are created under different experimental designs for sample-to-array assignment and various levels of signal-to-noise ratios.
Performance Assessment Tools: 'PRECISION.array' offers a collection of both numerical and graphical tools that enable users to assess the performance of data normalization and classification methods. This assessment is valuable for comparing different approaches and selecting the most appropriate methods for a given dataset.
Custom Methods: Users have the flexibility to specify their own methods for data normalization and classification, allowing for a tailored analysis that suits their specific research needs.
Normalization and Classification Methods: The package provides a comprehensive set of built-in methods for data normalization and classification. This includes three methods for training data normalization, seven methods for test data normalization, seven methods for classifier training, and two methods for classifier validation.
Objective Evaluation: 'PRECISION.array' facilitates an objective and systematic evaluation of the performance of normalization and classification methods in the context of microRNA microarrays. This is essential for ensuring the robustness and reliability of data analysis results.