LCT

LCT analyzes low complexity regions (LCRs) in protein sequences by computing local repeatability with the RES algorithm and the local fraction of the most frequent amino acid to map sequence regions into a low complexity triangle for characterization and proteome comparison.

Key Features:

• Low Complexity Triangle Representation: Constructs a graphical low complexity triangle based on two local measures to visualize and analyze sequence complexity.
• Repeatability (RES algorithm): Computes a local repeatability score using the RES algorithm to quantify the propensity of sequence regions to form repeats.
• Fraction of Most Frequent Amino Acid: Calculates the local fraction of the most frequent amino acid to capture compositional bias within regions.
• Distinct Proteome Signatures: Produces proteome- and dataset-specific signatures in the low complexity triangle that correlate with inherent sequence complexity features.
• Characterization of Protein Regions: Identifies and positions homorepeats, direpeats, compositionally biased regions, and globular regions within characteristic zones of the triangle.

Scientific Applications:

• Proteome Analysis: Comparing proteomes and datasets by their low complexity triangle signatures to reveal differences in sequence complexity distribution.
• Characterization of Specific Protein Features: Detecting and characterizing homorepeats, direpeats, and compositionally biased regions based on their triangle coordinates.
• Quantification of Degenerated Tandem Repeats: Assessing the content and distribution of degenerated tandem repeats through repeatability and composition metrics.

Methodology:

LCT computes local repeatability via the RES algorithm and the local fraction of the most frequent amino acid, then maps these two measures into a low complexity triangle graphical representation.