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Related Concept Videos

Next-generation Sequencing03:00

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The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
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DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...
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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
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Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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Rapid Amplification of cDNA Ends, or RACE, is one of the most effective methods to obtain a full-length cDNA from an mRNA sequence between a known internal region to the unknown sequence at the 5’ or 3’ end. The unknown region is cloned in the cDNA by a gene-specific primer that binds the known end, and a hybrid primer that attaches a predefined anchor sequence to the unknown end of the cDNA. The sequence in between is amplified by PCR with an anchor primer and a gene-specific...
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Detection of Rare Mutations in CtDNA Using Next Generation Sequencing
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Accelerated long-read variant calling with Clair3 for whole-genome sequencing.

Zhenxian Zheng1, Minggao He1, Xian Yu1

  • 1School of Computing and Data Science, The University of Hong Kong, Hong Kong, China.

Bioinformatics (Oxford, England)
|April 12, 2026
PubMed
Summary

We developed an accelerated variant calling framework, Clair3, that significantly reduces computational time for genomic analysis. This deep learning-based method achieves high accuracy and supports large-scale genomic studies.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Genomic data is rapidly expanding, driving the need for efficient variant calling.
  • Long-read sequencing technologies increase computational demands in genomic analysis.
  • Deep learning methods offer superior accuracy but are computationally intensive.

Purpose of the Study:

  • To develop a computationally efficient framework for accelerated variant calling.
  • To improve the speed of deep learning-based variant calling without sacrificing accuracy.
  • To support large-cohort genomic studies and time-sensitive clinical applications.

Main Methods:

  • Integrated parallelized feature generation, enhanced variant phasing, and in-memory read haplotagging.
  • Utilized GPU-accelerated neural network inference for variant calling.
  • Dynamically optimized GPU and CPU resource utilization.

Main Results:

  • Achieved a 10-20 fold speedup in variant calling for 30× whole-genome sequences.
  • Completed variant calling in 12-20 minutes on standard hardware and 12-15 minutes on Apple Mac Studio.
  • Maintained state-of-the-art accuracy with SNP F1-scores of 99.32% (ONT) and 99.70% (PacBio).

Conclusions:

  • The Clair3 framework provides a rapid, accurate, and scalable solution for variant calling.
  • The optimized pipeline addresses the computational challenges of large-scale genomic data analysis.
  • This advancement facilitates efficient genomic studies and clinical applications.