Literature DB >> 28094102

Single-Cell Genomics: Approaches and Utility in Immunology.

Karlynn E Neu1, Qingming Tang2, Patrick C Wilson1, Aly A Khan3.   

Abstract

Single-cell genomics offers powerful tools for studying immune cells, which make it possible to observe rare and intermediate cell states that cannot be resolved at the population level. Advances in computer science and single-cell sequencing technology have created a data-driven revolution in immunology. The challenge for immunologists is to harness computing and turn an avalanche of quantitative data into meaningful discovery of immunological principles, predictive models, and strategies for therapeutics. Here, we review the current literature on computational analysis of single-cell RNA-sequencing data and discuss underlying assumptions, methods, and applications in immunology, and highlight important directions for future research.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  dimensionality reduction; immune repertoire; single-cell RNA-sequencing; visualization

Mesh:

Year:  2017        PMID: 28094102      PMCID: PMC5479322          DOI: 10.1016/j.it.2016.12.001

Source DB:  PubMed          Journal:  Trends Immunol        ISSN: 1471-4906            Impact factor:   16.687


  64 in total

1.  Counting absolute numbers of molecules using unique molecular identifiers.

Authors:  Teemu Kivioja; Anna Vähärautio; Kasper Karlsson; Martin Bonke; Martin Enge; Sten Linnarsson; Jussi Taipale
Journal:  Nat Methods       Date:  2011-11-20       Impact factor: 28.547

Review 2.  Design and Analysis of Single-Cell Sequencing Experiments.

Authors:  Dominic Grün; Alexander van Oudenaarden
Journal:  Cell       Date:  2015-11-05       Impact factor: 41.582

3.  Linking the T cell receptor to the single cell transcriptome in antigen-specific human T cells.

Authors:  Auda A Eltahla; Simone Rizzetto; Mehdi R Pirozyan; Brigid D Betz-Stablein; Vanessa Venturi; Katherine Kedzierska; Andrew R Lloyd; Rowena A Bull; Fabio Luciani
Journal:  Immunol Cell Biol       Date:  2016-02-10       Impact factor: 5.126

4.  Single-cell trajectory detection uncovers progression and regulatory coordination in human B cell development.

Authors:  Sean C Bendall; Kara L Davis; El-Ad David Amir; Michelle D Tadmor; Erin F Simonds; Tiffany J Chen; Daniel K Shenfeld; Garry P Nolan; Dana Pe'er
Journal:  Cell       Date:  2014-04-24       Impact factor: 41.582

5.  Bifurcation analysis of single-cell gene expression data reveals epigenetic landscape.

Authors:  Eugenio Marco; Robert L Karp; Guoji Guo; Paul Robson; Adam H Hart; Lorenzo Trippa; Guo-Cheng Yuan
Journal:  Proc Natl Acad Sci U S A       Date:  2014-12-15       Impact factor: 11.205

6.  Fast gapped-read alignment with Bowtie 2.

Authors:  Ben Langmead; Steven L Salzberg
Journal:  Nat Methods       Date:  2012-03-04       Impact factor: 28.547

7.  Near-optimal probabilistic RNA-seq quantification.

Authors:  Nicolas L Bray; Harold Pimentel; Páll Melsted; Lior Pachter
Journal:  Nat Biotechnol       Date:  2016-04-04       Impact factor: 54.908

8.  RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome.

Authors:  Bo Li; Colin N Dewey
Journal:  BMC Bioinformatics       Date:  2011-08-04       Impact factor: 3.307

9.  Bayesian approach to single-cell differential expression analysis.

Authors:  Peter V Kharchenko; Lev Silberstein; David T Scadden
Journal:  Nat Methods       Date:  2014-05-18       Impact factor: 28.547

10.  Batch effects and the effective design of single-cell gene expression studies.

Authors:  Po-Yuan Tung; John D Blischak; Chiaowen Joyce Hsiao; David A Knowles; Jonathan E Burnett; Jonathan K Pritchard; Yoav Gilad
Journal:  Sci Rep       Date:  2017-01-03       Impact factor: 4.379

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  25 in total

Review 1.  Clinical promise of next-generation complement therapeutics.

Authors:  Dimitrios C Mastellos; Daniel Ricklin; John D Lambris
Journal:  Nat Rev Drug Discov       Date:  2019-07-19       Impact factor: 84.694

2.  Simulation, power evaluation and sample size recommendation for single-cell RNA-seq.

Authors:  Kenong Su; Zhijin Wu; Hao Wu
Journal:  Bioinformatics       Date:  2020-12-08       Impact factor: 6.937

3.  Single-Cell RNA Sequencing Analysis: A Step-by-Step Overview.

Authors:  Shaked Slovin; Annamaria Carissimo; Francesco Panariello; Antonio Grimaldi; Valentina Bouché; Gennaro Gambardella; Davide Cacchiarelli
Journal:  Methods Mol Biol       Date:  2021

4.  Identification of innate lymphoid cells in single-cell RNA-Seq data.

Authors:  Madeleine Suffiotti; Santiago J Carmona; Camilla Jandus; David Gfeller
Journal:  Immunogenetics       Date:  2017-05-22       Impact factor: 2.846

5.  Early adaptive immune activation detected in monozygotic twins with prodromal multiple sclerosis.

Authors:  Eduardo Beltrán; Lisa Ann Gerdes; Julia Hansen; Andrea Flierl-Hecht; Stefan Krebs; Helmut Blum; Birgit Ertl-Wagner; Frederik Barkhof; Tania Kümpfel; Reinhard Hohlfeld; Klaus Dornmair
Journal:  J Clin Invest       Date:  2019-11-01       Impact factor: 14.808

6.  Integration of tumor extrinsic and intrinsic features associates with immunotherapy response in non-small cell lung cancer.

Authors:  Denise Lau; Sonal Khare; Michelle M Stein; Prerna Jain; Yinjie Gao; Aicha BenTaieb; Tim A Rand; Ameen A Salahudeen; Aly A Khan
Journal:  Nat Commun       Date:  2022-07-13       Impact factor: 17.694

7.  Resident Breast T Cells: The Troops Are Already There.

Authors:  Aislyn Schalck; Chantale Bernatchez; Nicholas Navin
Journal:  Trends Mol Med       Date:  2018-08-01       Impact factor: 11.951

Review 8.  Epigenomic Views of Innate Lymphoid Cells.

Authors:  Giuseppe Sciumè; Han-Yu Shih; Yohei Mikami; John J O'Shea
Journal:  Front Immunol       Date:  2017-11-13       Impact factor: 7.561

9.  Mixed-effects association of single cells identifies an expanded effector CD4+ T cell subset in rheumatoid arthritis.

Authors:  Chamith Y Fonseka; Deepak A Rao; Nikola C Teslovich; Ilya Korsunsky; Susan K Hannes; Kamil Slowikowski; Michael F Gurish; Laura T Donlin; James A Lederer; Michael E Weinblatt; Elena M Massarotti; Jonathan S Coblyn; Simon M Helfgott; Derrick J Todd; Vivian P Bykerk; Elizabeth W Karlson; Joerg Ermann; Yvonne C Lee; Michael B Brenner; Soumya Raychaudhuri
Journal:  Sci Transl Med       Date:  2018-10-17       Impact factor: 19.319

10.  A multitask clustering approach for single-cell RNA-seq analysis in Recessive Dystrophic Epidermolysis Bullosa.

Authors:  Huanan Zhang; Catherine A A Lee; Zhuliu Li; John R Garbe; Cindy R Eide; Raphael Petegrosso; Rui Kuang; Jakub Tolar
Journal:  PLoS Comput Biol       Date:  2018-04-09       Impact factor: 4.475

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