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Updated: May 12, 2026

Single Cell Multiplex Reverse Transcription Polymerase Chain Reaction After Patch-clamp
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Single Cell Multiplex Reverse Transcription Polymerase Chain Reaction After Patch-clamp

Published on: June 20, 2018

LSCluster, a large-scale sequence clustering and aligning software for use in partial identity mapping and

Holger Husi1, Richard J Skipworth, Kenneth C H Fearon

  • 1Biomarkers and Systems Medicine Group, University of Glasgow, Glasgow, UK.

Journal of Proteomics
|April 17, 2013
PubMed
Summary

A new software, LSCluster, enables large-scale proteome analysis for identifying splice variants. It clusters tens of thousands of sequences, highlighting differences for biological research.

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Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
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Published on: June 23, 2012

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Last Updated: May 12, 2026

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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

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Existing sequence analysis tools struggle with large-scale proteome-wide analysis.
  • Identifying splice variants and clustering sequence differences is computationally challenging.
  • A need exists for a dedicated, stand-alone engine for high-throughput sequence analysis.

Purpose of the Study:

  • To introduce LSCluster, a novel software for large-scale sequence clustering.
  • To enable efficient identification of splice variants and sequence differences.
  • To provide a user-friendly tool for grouping tens of thousands of biological sequences.

Main Methods:

  • Development of LSCluster (Large-Scale CLUSTERing) software.
  • Utilizing sequence alignments and partial identity mapping for clustering.
  • Implementing a unique feature to display alignment output as a deprecated string.

Main Results:

  • LSCluster successfully groups tens of thousands of sequences.
  • The software facilitates the detection of splicing variants.
  • Alignment output is presented as a deprecated string, showing only sequence differences.

Conclusions:

  • LSCluster addresses the limitations of existing tools for large-scale proteome analysis.
  • The software is valuable for identifying splice variants and analyzing sequence diversity.
  • LSCluster (version 2.0) is freely available via the Proteomic Analysis DataBase (PADB).