Scholarlink

<p>Metagenomic Next-Generation Sequencing (mNGS) enables simultaneous sequencing of both microbial and host nucleic acids in clinical samples. However, analytical approaches for interpreting complex mNGS datasets are seldom disclosed, limiting advancements in multimodal analysis and omics-driven research models built upon mNGS results. We present 402 high-quality bronchoalveolar lavage fluid mNGS DNA and RNA sequencing datasets for developing combined microbial-host metagenomic diagnostic approaches. Only the microbial (non-host) sequence reads have been deposited. We provide comprehensive descriptions of methods, tools, and pipelines used for mining microbial features (DNA/RNA microbial composition and bacteriophage abundances) and host response features (differential expression genes, transposable elements, cell-type composition, and copy number variation). These data processing pipelines set a standard for future multimodal omics diagnostic research, promoting the adoption of standardized practices in omics-based studies that integrate clinical data.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Bronchoalveolar lavage fluid metagenomic datasets: a multidimensional clinical biomolecular resource

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月5日

查看全文
  • Hui Tang,
  • Huifang Liu,
  • Lingjun Yuan,
  • Mengxiao Xie,
  • Jieyuan Zheng,
  • Jingchao Wang,
  • Jieting Zhou,
  • Bin Yang,
  • Bin Lou,
  • Dongsheng Han

摘要

Metagenomic Next-Generation Sequencing (mNGS) enables simultaneous sequencing of both microbial and host nucleic acids in clinical samples. However, analytical approaches for interpreting complex mNGS datasets are seldom disclosed, limiting advancements in multimodal analysis and omics-driven research models built upon mNGS results. We present 402 high-quality bronchoalveolar lavage fluid mNGS DNA and RNA sequencing datasets for developing combined microbial-host metagenomic diagnostic approaches. Only the microbial (non-host) sequence reads have been deposited. We provide comprehensive descriptions of methods, tools, and pipelines used for mining microbial features (DNA/RNA microbial composition and bacteriophage abundances) and host response features (differential expression genes, transposable elements, cell-type composition, and copy number variation). These data processing pipelines set a standard for future multimodal omics diagnostic research, promoting the adoption of standardized practices in omics-based studies that integrate clinical data.