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The RaggedExperiment R/Bioconductor package offers a new way to represent and analyze genomic range data from multiple samples. It simplifies complex data for various downstream analyses, including cancer genomics.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Genomic data, such as copy number and mutation data, often present as "ragged" ranges across different genomic coordinates per sample.
  • This ragged format poses informatics challenges for standard downstream statistical analyses, which typically require rectangular or matrix-like data structures.

Purpose of the Study:

  • To introduce the RaggedExperiment R/Bioconductor data structure for lossless representation of ragged genomic data.
  • To provide tools for reshaping ragged data into tabular formats suitable for statistical analysis.

Main Methods:

  • Development of the RaggedExperiment data structure in R/Bioconductor.
  • Implementation of reshaping tools for transforming ragged genomic data.
  • Application of the data structure to copy number and somatic mutation data from The Cancer Genome Atlas (TCGA).

Main Results:

  • RaggedExperiment enables lossless representation of disparate genomic ranges.
  • Efficient and flexible calculation of rectangular summaries for downstream analysis is achieved.
  • Demonstrated applicability to copy number and somatic mutation data across 33 TCGA cancer datasets.

Conclusions:

  • RaggedExperiment simplifies data representation and transformation for genomic analyses.
  • The package is compatible with multimodal data analysis within MultiAssayExperiment objects.
  • It supports a wide range of downstream statistical analyses for genomic attributes.