kth.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
FISH-quant v2: a scalable and modular tool for smFISH image analysis
PSL Univ, Ctr Computat Biol CBIO, MINES ParisTech, F-75272 Paris 06, France.;Inst Curie, F-75248 Paris, France.;INSERM, U900, F-75248 Paris, France..
KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics.ORCID iD: 0000-0002-0291-926x
Sorbonne Univ, Inst Biol Paris Seine IBPS, Lab Biol Dev, CNRS, F-75005 Paris, France..ORCID iD: 0000-0002-9324-9037
Univ Montpellier, CNRS, IGH, F-34090 Montpellier, France..
Show others and affiliations
2022 (English)In: RNA: A publication of the RNA Society, ISSN 1355-8382, E-ISSN 1469-9001, Vol. 28, no 6, p. 786-795Article in journal (Refereed) Published
Abstract [en]

Regulation of RNA abundance and localization is a key step in gene expression control. Single-molecule RNA fluorescence in situ hybridization (smFISH) is a widely used single-cell-single-molecule imaging technique enabling quantitative studies of gene expression and its regulatory mechanisms. Today, these methods are applicable at a large scale, which in turn come with a need for adequate tools for data analysis and exploration. Here, we present FISH-quant v2, a highly modular tool accessible for both experts and non-experts. Our user-friendly package allows the user to segment nuclei and cells, detect isolated RNAs, decompose dense RNA clusters, quantify RNA localization patterns and visualize these results both at the single-cell level and variations within the cell population. This tool was validated and applied on large-scale smFISH image data sets, revealing diverse subcellular RNA localization patterns and a surprisingly high degree of cell-to-cell heterogeneity.

Place, publisher, year, edition, pages
COLD SPRING HARBOR LAB PRESS, PUBLICATIONS DEPT , 2022. Vol. 28, no 6, p. 786-795
Keywords [en]
image analysis, RNA localization, transcription, smFISH
National Category
Software Engineering Mathematical Analysis Biophysics
Identifiers
URN: urn:nbn:se:kth:diva-313067DOI: 10.1261/rna.079073.121ISI: 000793718200002PubMedID: 35347070Scopus ID: 2-s2.0-85130638938OAI: oai:DiVA.org:kth-313067DiVA, id: diva2:1661647
Note

QC 20220530

Available from: 2022-05-30 Created: 2022-05-30 Last updated: 2025-02-20Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textPubMedScopus

Authority records

Ouyang, Wei

Search in DiVA

By author/editor
Ouyang, WeiSafieddine, Adham
By organisation
Science for Life Laboratory, SciLifeLabCellular and Clinical Proteomics
In the same journal
RNA: A publication of the RNA Society
Software EngineeringMathematical AnalysisBiophysics

Search outside of DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 77 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf