Please use this identifier to cite or link to this item: https://doi.org/10.3389/fimmu.2018.02425
DC FieldValue
dc.titleA single-cell sequencing guide for immunologists
dc.contributor.authorSee, P
dc.contributor.authorLum, J
dc.contributor.authorChen, J
dc.contributor.authorGinhoux, F
dc.date.accessioned2020-10-20T04:59:00Z
dc.date.available2020-10-20T04:59:00Z
dc.date.issued2018
dc.identifier.citationSee, P, Lum, J, Chen, J, Ginhoux, F (2018). A single-cell sequencing guide for immunologists. Frontiers in Immunology 9 (OCT) : 2425. ScholarBank@NUS Repository. https://doi.org/10.3389/fimmu.2018.02425
dc.identifier.issn16643224
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/178063
dc.description.abstractIn recent years there has been a rapid increase in the use of single-cell sequencing (scRNA-seq) approaches in the field of immunology. With the wide range of technologies available, it is becoming harder for users to select the best scRNA-seq protocol/platform to address their biological questions of interest. Here, we compared the advantages and limitations of four commonly used scRNA-seq platforms in order to clarify their suitability for different experimental applications. We also address how the datasets generated by different scRNA-seq platforms can be integrated, and how to identify unknown populations of single cells using unbiased bioinformatics methods. Copyright © 2018 See, Lum, Chen and Ginhoux.
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceUnpaywall 20201031
dc.subjectcomplementary DNA
dc.subjectmessenger RNA
dc.subjecttranscriptome
dc.subjectanimal cell
dc.subjectbiological variation
dc.subjectchromatin immunoprecipitation
dc.subjectcomputer model
dc.subjectcytolysis
dc.subjectdendritic cell
dc.subjectfluorescence activated cell sorting
dc.subjectgene expression
dc.subjectgenomics
dc.subjecthuman
dc.subjecthuman cell
dc.subjectimmunologist
dc.subjectimmunology
dc.subjectmethodology
dc.subjectmicroarray analysis
dc.subjectnonhuman
dc.subjectontogeny
dc.subjectphenotype
dc.subjectreverse transcription
dc.subjectReview
dc.subjectRNA sequence
dc.subjectsingle cell sequencing
dc.subjectanimal
dc.subjectgene expression profiling
dc.subjecthigh throughput sequencing
dc.subjectimmunological technique
dc.subjectimmunology
dc.subjectinformation processing
dc.subjectprocedures
dc.subjectsequence analysis
dc.subjectsingle cell analysis
dc.subjectsoftware
dc.subjectAllergy and Immunology
dc.subjectAnimals
dc.subjectDatasets as Topic
dc.subjectGene Expression Profiling
dc.subjectHigh-Throughput Nucleotide Sequencing
dc.subjectHumans
dc.subjectImmunologic Techniques
dc.subjectSequence Analysis, RNA
dc.subjectSingle-Cell Analysis
dc.subjectSoftware
dc.typeReview
dc.contributor.departmentMICROBIOLOGY AND IMMUNOLOGY
dc.description.doi10.3389/fimmu.2018.02425
dc.description.sourcetitleFrontiers in Immunology
dc.description.volume9
dc.description.issueOCT
dc.description.page2425
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