title: Bioinformatics analysis of circulating cell-free DNA sequencing data.
abstract: The discovery of cell-free DNA molecules in plasma has opened up numerous opportunities in noninvasive diagnosis. Cell-free DNA molecules have become increasingly recognized as promising biomarkers for detection and management of many diseases. The advent of next generation sequencing has provided unprecedented opportunities to scrutinize the characteristics of cell-free DNA molecules in plasma in a genome-wide fashion and at single-base resolution. Consequently, clinical applications of circulating cell-free DNA analysis have not only revolutionized noninvasive prenatal diagnosis but also facilitated cancer detection and monitoring toward an era of blood-based personalized medicine. With the remarkably increasing throughput and lowering cost of next generation sequencing, bioinformatics analysis becomes increasingly demanding to understand the large amount of data generated by these sequencing platforms. In this Review, we highlight the major bioinformatics algorithms involved in the analysis of cell-free DNA sequencing data. Firstly, we briefly describe the biological properties of these molecules and provide an overview of the general bioinformatics approach for the analysis of cell-free DNA. Then, we discuss the specific upstream bioinformatics considerations concerning the analysis of sequencing data of circulating cell-free DNA, followed by further detailed elaboration on each key clinical situation in noninvasive prenatal diagnosis and cancer management where downstream bioinformatics analysis is heavily involved. We also discuss bioinformatics analysis as well as clinical applications of the newly developed massively parallel bisulfite sequencing of cell-free DNA. Finally, we offer our perspectives on the future development of bioinformatics in noninvasive diagnosis.
authors.affiliation: Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China; Department of Chemical Pathology, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong, China.
authors.forename: Landon L
authors.initials: LL
authors.lastname: Chan
authors.affiliation: Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China; Department of Chemical Pathology, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong, China. Electronic address: jiangpeiyong@cuhk.edu.hk.
authors.forename: Peiyong
authors.initials: P
authors.lastname: Jiang
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods* / Q000639:trends; D004247:DNA / Q000097:blood* / Q000737:chemistry / Q000378:metabolism; D019175:DNA Methylation; D055088:Early Detection of Cancer / Q000639:trends; D044127:Epigenesis, Genetic; D057890:Epigenomics / Q000379:methods* / Q000639:trends; D005260:Female; D005820:Genetic Testing / Q000639:trends; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D019656:Loss of Heterozygosity; D008297:Male; D025202:Molecular Diagnostic Techniques / Q000639:trends; D009154:Mutation; D010949:Plasma / Q000737:chemistry; D057285:Precision Medicine / Q000639:trends; D011247:Pregnancy; D011296:Prenatal Diagnosis / Q000639:trends; D017422:Sequence Analysis, DNA / Q000639:trends
chemical_list: D004247:DNA
keywords: Bioinformatics analysis; Cancer diagnosis; Next generation sequencing; Prenatal diagnosis