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<p>High-throughput sequencing (HTseq) characterizes complex entities at the level of nucleic acid sequences, e. g. the transcriptome in a biopsy at cellular resolution, or an immune-receptor-repertoire. The complexity of HTseq data makes analysis challenging. Suitable methods are often missing. We therefore develop computational tools for <i>quantitative visualization</i> (quantitative modelling of data, then visualization of meaningful summaries) as illustrated with two examples, scBubble-tree and ClustIRR.</p>

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Quantitative Visualisierung von HTseq-Daten

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年2月21日

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  • Simo Kitanovski,
  • Kai Wollek,
  • Daniel Hoffmann

摘要

High-throughput sequencing (HTseq) characterizes complex entities at the level of nucleic acid sequences, e. g. the transcriptome in a biopsy at cellular resolution, or an immune-receptor-repertoire. The complexity of HTseq data makes analysis challenging. Suitable methods are often missing. We therefore develop computational tools for quantitative visualization (quantitative modelling of data, then visualization of meaningful summaries) as illustrated with two examples, scBubble-tree and ClustIRR.