k-Seq

k-Seq analyzes DNA sequencing data from kinetic assays to quantify kinetic parameters across large libraries of nucleic acid sequences and characterize genotype–phenotype relationships of biomolecules such as ribozymes.

Key Features:

• High-Throughput Capability: Processes high-throughput DNA sequencing data to quantify activity across libraries potentially exceeding 10^6 unique nucleic acid sequences.
• Technical Challenges Addressed: Accounts for sequence heterogeneity and DNA sequencing errors to improve reliability of kinetic measurements.
• Model Identifiability and Error Analysis: Evaluates model identifiability and the impact of sequencing errors using simulated datasets and experimental data from variant pools constructed from previously identified ribozymes.
• Quantification of Uncertainty: Implements bootstrapping techniques to quantify uncertainty in estimated kinetic parameters.
• Interpretable Metrics: Provides interpretable metrics to quantify model identifiability.
• Protocols and Guidelines: Includes protocols and guidelines that define critical experimental factors and aim to maximize the number of sequences analyzed and enhance measurement accuracy.

Scientific Applications:

• Genotype–Phenotype Mapping: Characterizes genotype–phenotype relationships for biomolecules such as ribozymes by measuring kinetic activity across sequence libraries.
• Ribozyme Variant Pool Studies: Analyzes extensive variant pools from ribozyme studies to assess activity and distributions of kinetic parameters.
• Sequencing-based Kinetic Assays: Supports high-throughput sequencing-based kinetic assays relevant to genomics, molecular biology, and related fields.

Methodology:

Uses simulated datasets and experimental data from variant pools to evaluate model identifiability and sequencing error effects, applies bootstrapping to estimate uncertainty, and computes interpretable identifiability metrics.