Data classes

RNA structure data can come from databases, experimental measurements, and computational analyses or predictions. RNAvigate will accept text files or python objects (usually a pandas.DataFrame) as inputs.

See `/dev/data_sources`_ for methods, databases, and software that supply RNA structure information.

RNA structure data can be analyzed with RNAvigate if it falls into one of these five categories. More information on these categories is provided below.

Annotations

RNAvigate data class: rnav.data.Annotations

Annotations define a set of related RNA features. These can be individual nucleotides, regions, or discontinuous groups.

Types of features:

  • individual sites:

    • modified nucleotides

      • m6A, Pseudouridine, m7G, and others

    • nucleotides with measurements above a threshold value

    • SNPs and riboSNitches

  • regions:

    • protein binding sites, such as eCLIP peaks

    • UTRs, ORFs and codons

    • introns and exons

    • sequence motifs

    • primer binding sites

    • structural features

      • pseudoknots, kissing loops, G-quadruplexes and others

  • discontinuous groups:

    • nucleotides proximal to a protein, ligand, or pocket

Profiles

RNAvigate data class: rnav.data.Profile

Profiles define per-nucleotide measurements.

Types of measurements:

  • chemical reactivity, such as mutational profiles (MaP) and RT stop signals

  • read counts or enrichment scores, such as CLIP or RIP based methods

  • sequence conservation

  • shannon entropy and pairing probability

  • structural proximity to some other feature or molecule

Secondary structures

RNAvigate data class: rnav.data.SecondaryStructure

Secondary structures define a pattern of base-pairing. Additionally, these may contain secondary structure diagram layout coordinates for each nucleotide.

Types of secondary structures:

  • Experimentally determined from CryoEM or crystal structures

  • computationally modeled de novo or informed by chemical probing data

  • Secondary structure drawing layouts, such as from VARNA, XRNA, R2DT, etc.

Interactions

RNAvigate data class: rnav.data.Interactions

Interactions define inter-nucleotide measurements. These can be between individual nucleotides or uniform windows of nucleotides.

Types of interactions:

  • Single molecule correlated events

  • Interactions data from proximity ligation, SHARC, SHAPE-JuMP, etc.

  • Base-pairing probabilities

  • Sequence covariation

3D structures

RNAvigate data class: rnav.data.PDB

3D structures define the atomic coordinates of residues in an RNA.

Types of 3D structures:

  • Experimentally determined from CryoEM or crystal structures

  • computationally modeled de novo or informed by chemical probing data