DOI: 10.25349/d9t02r
title: Kinetic sequencing (k-Seq) as a massively parallel assay for ribozyme kinetics: utility and critical parameters

description: Characterizing genotype-phenotype relationships of biomolecules (e.g.,
 ribozymes) requires accurate ways to measure activity for a large set of
 molecules. Kinetic measurement using high-throughput sequencing (e.g.,
 k-Seq) is an emerging assay applicable in various domains that potentially
 scales up measurement throughput to over 106 unique nucleic acid
 sequences. However, maximizing the return of such assays requires
 understanding the technical challenges introduced by sequence
 heterogeneity and DNA sequencing. We characterized the k-Seq method in
 terms of model identifiability, effects of sequencing error, accuracy and
 precision using simulated datasets and experimental data from a variant
 pool constructed from previously identified ribozymes. Relative abundance,
 kinetic coefficients, and measurement noise were found to affect the
 measurement of each sequence. We introduced bootstrapping to robustly
 quantify the uncertainty in estimating model parameters and proposed
 interpretable metrics to quantify model identifiability. These efforts
 enabled the rigorous reporting of data quality for individual sequences in
 k-Seq experiments. Here we present detailed protocols, define critical
 experimental factors, and identify general guidelines to maximize the
 number of sequences and their measurement accuracy from k-Seq data.
 Analogous practices could be applied to improve the rigor of other
 sequencing-based assays.
description: DNA sequencing data (FASTQ) were collected from a
 kinetic sequencing (<em>k</em>-Seq) experiment on a variant
 RNA pool constructed from previously identified ribozymes. FASTQ
 files were processed using EasyDIVER (https://github.com/ichen-lab-ucsb/EasyDIVER) to sequence counts for the quantification of sequences in <em>k</em>-Seq samples. Reacted fractions were further calculated and fit into a pseudo-first-order kinetic model to estimate the kinetic coefficients for each sequence, using the k-seq package (https://github.com/ichen-lab-ucsb/k-seq). Additional simulation datasets were synthesized to study the utility of the <em>k</em>-Seq method. Please see the paper "Kinetic sequencing (k-Seq) as a massively parallel assay for ribozyme kinetics: utility and critical parameters" for details.
description: This dataset is for the paper "Kinetic sequencing (k-Seq) as
 a massively parallel assay for ribozyme kinetics: utility and critical
 parameters". It contains the following
 files:<br>   - core-data.tar.gz: data/results/code necessary to
 repeat paper's analysis and generate figures.<br>     It
 contains the following folders:<br>       - data: preprocessed k-Seq
 data and data for qPCR standard curve<br>       - results: results
 for experimental and simulation studies<br>       - code: the
 codebase including a snapshot of k-seq package, scripts to repeat data
 analysis, and notebooks to generate figures in the paper<br>   -
 raw-data.tar.gz: raw or large data including sequencing FASTQ files and
 deduplicated reads Please see the README files under
 each archive (.tar.gz) for details.