核糖核酸
计算生物学
RNA序列
RNA剪接
计算机科学
范围(计算机科学)
生物
基因
转录组
遗传学
基因表达
程序设计语言
作者
Amarinder Singh Thind,Isha Monga,Prasoon Thakur,Pallawi Kumari,Kiran Dindhoria,Monika Krzak,Marie Ranson,Bruce Ashford
摘要
Significant innovations in next-generation sequencing techniques and bioinformatics tools have impacted our appreciation and understanding of RNA. Practical RNA sequencing (RNA-Seq) applications have evolved in conjunction with sequence technology and bioinformatic tools advances. In most projects, bulk RNA-Seq data is used to measure gene expression patterns, isoform expression, alternative splicing and single-nucleotide polymorphisms. However, RNA-Seq holds far more hidden biological information including details of copy number alteration, microbial contamination, transposable elements, cell type (deconvolution) and the presence of neoantigens. Recent novel and advanced bioinformatic algorithms developed the capacity to retrieve this information from bulk RNA-Seq data, thus broadening its scope. The focus of this review is to comprehend the emerging bulk RNA-Seq-based analyses, emphasizing less familiar and underused applications. In doing so, we highlight the power of bulk RNA-Seq in providing biological insights.
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