Efficient and Tidy Manipulation of Annotated Matrix Data with plyxp

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• High-dimensional omics data, like gene expression matrices, present manipulation challenges for bioinformaticians.
• Current matrix-centric tools often lack the intuitiveness of tidy data principles.

Purpose of the Study:

• To develop an expressive grammar and R package for intuitive manipulation of annotated omics matrices.
• To enhance accessibility and efficiency in bioinformatics data analysis.

Main Methods:

• Proposed an expressive grammar for annotated matrix data manipulation.
• Implemented the grammar in the R/Bioconductor package 'plyxp'.
• Utilized efficient abstractions for the SummarizedExperiment class.

Main Results:

• 'plyxp' provides intuitive syntax for accessing, modifying, and appending matrix data and metadata.
• The package supports row-wise and column-wise grouped operations across multiple contexts.
• Demonstrated 'plyxp's computational efficiency compared to alternative methods.

Conclusions:

• 'plyxp' offers a more intuitive and efficient approach to manipulating high-dimensional omics data.
• The package lowers the barrier for bioinformaticians to work with complex datasets.
• Facilitates advanced data analysis through streamlined matrix and metadata operations.