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SMART-Q: An Integrative Pipeline Quantifying Cell Type-Specific RNA Transcription
Accurate RNA quantification at the single-cell level is critical for understanding the dynamics of gene expression and regulation across space and time. Single molecule FISH (smFISH), such as RNAscope, provides spatial and quantitative measurements of individual transcripts, therefore, can be used t...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7190163/ https://www.ncbi.nlm.nih.gov/pubmed/32348304 http://dx.doi.org/10.1371/journal.pone.0228760 |
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author | Yang, Xiaoyu Bergenholtz, Seth Maliskova, Lenka Pebworth, Mark-Phillip Kriegstein, Arnold R. Li, Yun Shen, Yin |
author_facet | Yang, Xiaoyu Bergenholtz, Seth Maliskova, Lenka Pebworth, Mark-Phillip Kriegstein, Arnold R. Li, Yun Shen, Yin |
author_sort | Yang, Xiaoyu |
collection | PubMed |
description | Accurate RNA quantification at the single-cell level is critical for understanding the dynamics of gene expression and regulation across space and time. Single molecule FISH (smFISH), such as RNAscope, provides spatial and quantitative measurements of individual transcripts, therefore, can be used to explore differential gene expression among a heterogeneous cell population if combined with cell identify information. However, such analysis is not straightforward, and existing image analysis pipelines cannot integrate both RNA transcripts and cellular staining information to automatically output cell type-specific gene expression. We developed an efficient and customizable analysis method, Single-Molecule Automatic RNA Transcription Quantification (SMART-Q), to enable the analysis of gene transcripts in a cell type-specific manner. SMART-Q efficiently infers cell identity information from multiplexed immuno-staining and quantifies cell type-specific transcripts using a 3D Gaussian fitting algorithm. Furthermore, we have optimized SMART-Q for user experiences, such as flexible parameters specification, batch data outputs, and visualization of analysis results. SMART-Q meets the demands for efficient quantification of single-molecule RNA and can be widely used for cell type-specific RNA transcript analysis. |
format | Online Article Text |
id | pubmed-7190163 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-71901632020-05-06 SMART-Q: An Integrative Pipeline Quantifying Cell Type-Specific RNA Transcription Yang, Xiaoyu Bergenholtz, Seth Maliskova, Lenka Pebworth, Mark-Phillip Kriegstein, Arnold R. Li, Yun Shen, Yin PLoS One Research Article Accurate RNA quantification at the single-cell level is critical for understanding the dynamics of gene expression and regulation across space and time. Single molecule FISH (smFISH), such as RNAscope, provides spatial and quantitative measurements of individual transcripts, therefore, can be used to explore differential gene expression among a heterogeneous cell population if combined with cell identify information. However, such analysis is not straightforward, and existing image analysis pipelines cannot integrate both RNA transcripts and cellular staining information to automatically output cell type-specific gene expression. We developed an efficient and customizable analysis method, Single-Molecule Automatic RNA Transcription Quantification (SMART-Q), to enable the analysis of gene transcripts in a cell type-specific manner. SMART-Q efficiently infers cell identity information from multiplexed immuno-staining and quantifies cell type-specific transcripts using a 3D Gaussian fitting algorithm. Furthermore, we have optimized SMART-Q for user experiences, such as flexible parameters specification, batch data outputs, and visualization of analysis results. SMART-Q meets the demands for efficient quantification of single-molecule RNA and can be widely used for cell type-specific RNA transcript analysis. Public Library of Science 2020-04-29 /pmc/articles/PMC7190163/ /pubmed/32348304 http://dx.doi.org/10.1371/journal.pone.0228760 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication. |
spellingShingle | Research Article Yang, Xiaoyu Bergenholtz, Seth Maliskova, Lenka Pebworth, Mark-Phillip Kriegstein, Arnold R. Li, Yun Shen, Yin SMART-Q: An Integrative Pipeline Quantifying Cell Type-Specific RNA Transcription |
title | SMART-Q: An Integrative Pipeline Quantifying Cell Type-Specific RNA Transcription |
title_full | SMART-Q: An Integrative Pipeline Quantifying Cell Type-Specific RNA Transcription |
title_fullStr | SMART-Q: An Integrative Pipeline Quantifying Cell Type-Specific RNA Transcription |
title_full_unstemmed | SMART-Q: An Integrative Pipeline Quantifying Cell Type-Specific RNA Transcription |
title_short | SMART-Q: An Integrative Pipeline Quantifying Cell Type-Specific RNA Transcription |
title_sort | smart-q: an integrative pipeline quantifying cell type-specific rna transcription |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7190163/ https://www.ncbi.nlm.nih.gov/pubmed/32348304 http://dx.doi.org/10.1371/journal.pone.0228760 |
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