plyranges

plyranges provides a tidy grammar for manipulating genomic interval data in Bioconductor by defining domain-specific verbs to operate on Ranges, GenomicRanges, and GRanges objects and to support analyses such as overlap detection and coverage computation.

Key Features:

• Tidy grammar: Implements a "tidy" representation for genomic intervals where each row is an interval and each column is a feature.
• Data model support: Operates directly on Ranges, GenomicRanges, and GRanges objects.
• Domain-specific verbs: Provides verbs for filtering, transforming, summarizing, joining, and reshaping genomic intervals.
• Overlap and interval joins: Supports overlapping-range operations and interval joins across datasets.
• Coverage computation: Includes functionality for computing coverage over genomic intervals.
• Anchoring and resizing: Offers anchoring and resizing operations for interval manipulation.
• Interval aggregation: Enables aggregation of interval-level summaries.
• dplyr/tidyverse style chaining: Adopts dplyr-inspired, chainable expressions for composing operations.
• Bioconductor integration: Acts as a high-level layer over existing Bioconductor infrastructure.

Scientific Applications:

• Overlap detection and interval joining: Identifying and joining overlapping genomic intervals between datasets.
• Coverage analysis: Computing and summarizing coverage across genomic regions.
• Interval manipulation: Anchoring, resizing, and transforming genomic intervals for downstream analyses.
• Interval-level summarization: Aggregating summaries of interval-associated measurements.
• Integration within Bioconductor workflows: Using GRanges-based, tidy operations to connect with Bioconductor data structures and analyses.

Methodology:

Implements domain-specific verbs (filter, transform, summarize, join, reshape) inspired by dplyr and uses chainable expressions to manipulate Ranges, GenomicRanges, and GRanges objects as a high-level layer on Bioconductor infrastructure.