FASTAptameR 2.0

FASTAptameR 2.0 performs analysis of combinatorial sequence selections to identify and quantify biopolymers from high-throughput sequencing data.

Key Features:

• R-based reimplementation: Computational backend implemented in R as a reimplementation of the original FASTAptamer codebase.
• Clustering performance: Clustering capabilities reported up to 100-fold faster than the previous version.
• Expanded module set: Includes an expanded set of analytical modules for sequence-encoded selection analysis.
• Support for diverse polymers: Accepts diverse input polymer types (biopolymers) for analysis.
• Sequence- and population-level analyses: Implements both sequence-level and population-level analyses of selection outcomes.
• High-throughput sequencing input: Processes high-throughput sequencing (HTS) data from combinatorial selection experiments.

Scientific Applications:

• Biological research: Investigating biopolymers with specific biological functions or sequence-encoded properties.
• Biomedical studies: Identifying sequences relevant to diagnostics, therapeutics, and drug-discovery workflows.
• Chemical analysis: Exploring chemical properties encoded within biopolymer sequences from selection experiments.

Methodology:

Analysis of high-throughput sequencing data from combinatorial selection experiments using R-based processing, sequence clustering, and sequence-level and population-level analytical modules.