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This chapter delves into the foundational aspects of genomic dataGenomic data and computational methods that are essential for modern genomic analysisGenomic analysis. It explores the transformation of biology into a data-driven discipline, driven by advancements in nucleotide sequencing technologies and the exponential decrease in sequencing costs. The chapter categorizes genomic dataGenomic data into DNA sequencingDNA sequencing, transcriptomicsTranscriptomics, epigenomicsEpigenomics, metagenomicsMetagenomics, and multi-omicsMulti-omics, highlighting their unique properties, applications, and challenges. ​ It provides a detailed overview of key data formats such as FASTQFASTQ, SAM/BAM/CRAMSAM/BAM/CRAM, VCFVariant Call Format (VCF), and interval formats, emphasizing their structure, encoding, and importance for data interoperability. Additionally, it discusses data cleaningData cleaning, normalization, and quality controlQuality control processes, as well as feature representation methods like k-mer representationsK-mer representations, DNA2VecDNA2Vec embeddings, and genomic foundation modelsGenomic foundation models. Advanced concepts such as pangenomicsPangenomics and graph genomesGraph genomes are introduced to address population diversity and reference bias. The chapter concludes with insights into scalable genomic dataGenomic data pipelines, workflow management systemsWorkflow management systems, and the role of high-performance and cloud computingCloud computing in handling large-scale genomicGenomics datasets.

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Genomic Data and Computational Foundations

  • 章节

  • 发表日期：

    2026年

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  • Khalid Shaikh,
  • Rohit Thanki,
  • Sejal Shah

摘要

This chapter delves into the foundational aspects of genomic dataGenomic data and computational methods that are essential for modern genomic analysisGenomic analysis. It explores the transformation of biology into a data-driven discipline, driven by advancements in nucleotide sequencing technologies and the exponential decrease in sequencing costs. The chapter categorizes genomic dataGenomic data into DNA sequencingDNA sequencing, transcriptomicsTranscriptomics, epigenomicsEpigenomics, metagenomicsMetagenomics, and multi-omicsMulti-omics, highlighting their unique properties, applications, and challenges. ​ It provides a detailed overview of key data formats such as FASTQFASTQ, SAM/BAM/CRAMSAM/BAM/CRAM, VCFVariant Call Format (VCF), and interval formats, emphasizing their structure, encoding, and importance for data interoperability. Additionally, it discusses data cleaningData cleaning, normalization, and quality controlQuality control processes, as well as feature representation methods like k-mer representationsK-mer representations, DNA2VecDNA2Vec embeddings, and genomic foundation modelsGenomic foundation models. Advanced concepts such as pangenomicsPangenomics and graph genomesGraph genomes are introduced to address population diversity and reference bias. The chapter concludes with insights into scalable genomic dataGenomic data pipelines, workflow management systemsWorkflow management systems, and the role of high-performance and cloud computingCloud computing in handling large-scale genomicGenomics datasets.