ArticleNucleic acids research2020
dotdotdot: an automated approach to quantify multiplex single molecule fluorescent in situ hybridization (smFISH) images in complex tissues.
Article in Nucleic acids research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 1 of them a synthesis that pooled it.
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Who cites it
47 citing papers in PubMed, 1 synthesis or guideline pooled it, 92 citations in OpenAlex.
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- Applications and development of in situ nucleic acid visualization techniques.Frontiers in bioengineering and biotechnology · 2026Review
- Transcriptomic Analysis of the Human Habenula in Schizophrenia.The American journal of psychiatry · 2025Article
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- Stimulation of Locus Ceruleus Inputs to the Prelimbic Cortex in Mice Induces Cell Type-Specific Expression of theeNeuro · 2024Article
- Dopamine-mediated formation of a memory module in the nucleus accumbens for goal-directed navigation.Nature neuroscience · 2024Article
- Comparative Analysis of Gene Expression Analysis Methods for RNA in Situ Hybridization Images.The Journal of molecular diagnostics : JMD · 2024Article
- Overexpression of thebioRxiv : the preprint server for biology · 2024Article
- Stimulation of locus coeruleus inputs to the frontal cortex in mice induces cell type-specific expression of thebioRxiv : the preprint server for biology · 2024Article
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7 authors at 1 institution in 1 country.
Funding
Abstract
Multiplex single-molecule fluorescent in situ hybridization (smFISH) is a powerful method for validating RNA sequencing and emerging spatial transcriptomic data, but quantification remains a computational challenge. We present a framework for generating and analyzing smFISH data in complex tissues while overcoming autofluorescence and increasing multiplexing capacity. We developed dotdotdot (https://github.com/LieberInstitute/dotdotdot) as a corresponding software package to quantify RNA transcripts in single nuclei and perform differential expression analysis. We first demonstrate robustness of our platform in single mouse neurons by quantifying differential expression of activity-regulated genes. We then quantify spatial gene expression in human dorsolateral prefrontal cortex (DLPFC) using spectral imaging and dotdotdot to mask lipofuscin autofluorescence. We lastly apply machine learning to predict cell types and perform downstream cell type-specific expression analysis. In summary, we provide experimental workflows, imaging acquisition and analytic strategies for quantification and biological interpretation of smFISH data in complex tissues.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.