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Related Experiment Video

Updated: May 12, 2026

Cost-Efficient Transcriptomic-Based Drug Screening

Cost-Efficient Transcriptomic-Based Drug Screening

Published on: February 23, 2024

Base calling for high-throughput short-read sequencing: dynamic programming solutions.

Shreepriya Das¹, Haris Vikalo

¹Electrical and Computer Engineering Department, The University of Texas at Austin, Austin, Texas 78712, USA. shreedas@utexas.edu

BMC Bioinformatics

|April 17, 2013

Summary

This summary is machine-generated.

We developed fast and accurate statistical methods for base calling in next-generation DNA sequencing. Our model-based approach improves read accuracy and efficiency, benefiting downstream genomic applications.

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High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture (4C-seq)

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture (4C-seq)

Published on: October 5, 2018

Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

Next-generation sequencing (NGS) platforms generate vast amounts of data but face challenges with read accuracy due to biochemical and signal acquisition imperfections.
Developing computationally efficient and scalable base calling algorithms is crucial for improving NGS performance.

Purpose of the Study:

To develop model-based statistical methods for fast and accurate base calling in Illumina's NGS platforms.
To address the ongoing challenge of creating high-performing, efficient, and scalable base calling algorithms.

Main Methods:

Proposed a computationally tractable parametric model for base calling.
Formulated the base calling problem using dynamic programming.
Developed and analyzed forward-backward and soft-output Viterbi algorithms.

Main Results:

Demonstrated high accuracy and speed of the proposed methods on Illumina Genome Analyzer II and HiSeq2000 data.
Compared the performance and complexity of developed algorithms with existing state-of-the-art methods.
Developed a C code implementation named Softy, available for download.

Conclusions:

The developed statistical methods provide reliable and fast base calling for NGS data.
Algorithms allow for the incorporation of prior knowledge, aiding parameter estimation.
These advancements offer potential benefits for various downstream genomic applications.