Literature DB >> 29727584

Single-Cell (Multi)omics Technologies.

Lia Chappell1, Andrew J C Russell1, Thierry Voet1,2.   

Abstract

Single-cell multiomics technologies typically measure multiple types of molecule from the same individual cell, enabling more profound biological insight than can be inferred by analyzing each molecular layer from separate cells. These single-cell multiomics technologies can reveal cellular heterogeneity at multiple molecular layers within a population of cells and reveal how this variation is coupled or uncoupled between the captured omic layers. The data sets generated by these techniques have the potential to enable a deeper understanding of the key biological processes and mechanisms driving cellular heterogeneity and how they are linked with normal development and aging as well as disease etiology. This review details both established and novel single-cell mono- and multiomics technologies and considers their limitations, applications, and likely future developments.

Keywords:  cellular heterogeneity; multiomics; omics; single cell

Mesh:

Year:  2018        PMID: 29727584     DOI: 10.1146/annurev-genom-091416-035324

Source DB:  PubMed          Journal:  Annu Rev Genomics Hum Genet        ISSN: 1527-8204            Impact factor:   8.929


  55 in total

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Review 2.  Kidney and organoid single-cell transcriptomics: the end of the beginning.

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Journal:  Pediatr Nephrol       Date:  2019-01-04       Impact factor: 3.714

3.  Deep-joint-learning analysis model of single cell transcriptome and open chromatin accessibility data.

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Journal:  Brief Bioinform       Date:  2021-07-20       Impact factor: 11.622

Review 4.  Clinical value of DNA methylation markers in autoimmune rheumatic diseases.

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Review 5.  Systems genetics applications in metabolism research.

Authors:  Marcus Seldin; Xia Yang; Aldons J Lusis
Journal:  Nat Metab       Date:  2019-10-21

Review 6.  Computational methods and next-generation sequencing approaches to analyze epigenetics data: Profiling of methods and applications.

Authors:  Itika Arora; Trygve O Tollefsbol
Journal:  Methods       Date:  2020-09-14       Impact factor: 3.608

Review 7.  Pro-biomics: Omics Technologies To Unravel the Role of Probiotics in Health and Disease.

Authors:  Despoina Eugenia Kiousi; Marina Rathosi; Margaritis Tsifintaris; Pelagia Chondrou; Alex Galanis
Journal:  Adv Nutr       Date:  2021-10-01       Impact factor: 8.701

Review 8.  Drivers of dynamic intratumor heterogeneity and phenotypic plasticity.

Authors:  Antara Biswas; Subhajyoti De
Journal:  Am J Physiol Cell Physiol       Date:  2021-03-03       Impact factor: 4.249

Review 9.  A road map for understanding molecular and genetic determinants of osteoporosis.

Authors:  Tie-Lin Yang; Hui Shen; Anqi Liu; Shan-Shan Dong; Lei Zhang; Fei-Yan Deng; Qi Zhao; Hong-Wen Deng
Journal:  Nat Rev Endocrinol       Date:  2019-12-02       Impact factor: 43.330

Review 10.  Evolution and Diversity of Immune Responses during Acute HIV Infection.

Authors:  Samuel W Kazer; Bruce D Walker; Alex K Shalek
Journal:  Immunity       Date:  2020-11-17       Impact factor: 31.745

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