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Related Concept Videos

RNA-seq03:21

RNA-seq

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. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...
Genome Annotation and Assembly03:36

Genome Annotation and Assembly

The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
Sanger Sequencing01:57

Sanger Sequencing

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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Related Experiment Video

Updated: May 19, 2026

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

SAP--a sequence mapping and analyzing program for long sequence reads alignment and accurate variants discovery.

Zheng Sun1, Weidong Tian

  • 1State Key Laboratory of Genetic Engineering, Institute of Biostatistics, School of Life Sciences, Fudan University, Shanghai, China.

Plos One
|August 11, 2012
PubMed
Summary
This summary is machine-generated.

A new Sequence mapping and Analyzing Program (SAP) efficiently maps long DNA sequence reads from third-generation sequencing. SAP improves speed and accuracy for analyzing genomic data, including single nucleotide polymorphisms (SNPs) and insertions/deletions (InDels).

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Identification of Alternative Splicing and Polyadenylation in RNA-seq Data
08:35

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data

Published on: June 24, 2021

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Third-generation sequencing technologies generate long DNA reads (≥1000 bp) rich in polymorphism data.
  • Existing sequence analysis tools are primarily designed for short reads, limiting the utility of long-read data.
  • The traditional Smith-Waterman (SW) algorithm is computationally intensive for mapping long reads.

Purpose of the Study:

  • To develop a novel bioinformatics tool for efficient analysis of long sequence reads.
  • To overcome the computational limitations of existing algorithms for third-generation sequencing data.
  • To improve the speed and accuracy of sequence mapping and variant detection.

Main Methods:

  • Development of a new Sequence mapping and Analyzing Program (SAP).
  • Implementation of a modified Smith-Waterman (SW) algorithm within SAP to enhance computational efficiency.
  • Benchmarking SAP against existing tools using simulated and real sequencing data, including exon and whole genome datasets.

Main Results:

  • SAP demonstrates superior performance in both speed and read capture proportion compared to current tools for short and long reads.
  • SAP achieves high accuracy in identifying single nucleotide polymorphisms (SNPs) and insertions/deletions (InDels) in simulated data.
  • The program effectively processes data from third-generation sequencing technologies.

Conclusions:

  • SAP offers a computationally feasible and efficient solution for analyzing long sequence reads from advanced sequencing platforms.
  • The tool enhances the ability to detect genetic variations like SNPs and InDels, crucial for genomic research.
  • SAP represents a significant advancement in bioinformatics tools for modern genomics.