June 2024 PMID 38867267

Gene count normalization in single-cell imaging-based spatially resolved transcriptomics.

Lyla Atta, Kalen Clifton, Manjari Anant, Gohta Aihara, Jean Fan

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Mentions

32

Peak: 17 in Aug 2024

across 3 sources since Sep 2023

Extended reach

125,476

potential audience

Total likes

220

Video views

1,707

Mentions per month

Sep 2023 – Aug 2024

Where it's discussed

X / Twitter29 posts
Bluesky2 posts
YouTube1 videos

AI synopsis

What people are saying

The summaries highlight the technical focus of the discussions, with users referencing concepts like normalization methods and experimental design choices, exemplified by phrases such as 'considerations for gene expression count normalization' and 'how experimental design affects downstream results.' The tone is informative yet exploratory, reflecting an interest in methodological nuances and future implications of the study.

AgreementModerate agreement

Most discussions acknowledge the importance of normalization in spatial transcriptomics research, with some showing agreement with the publication's emphasis on alternative methods like cell volume normalization.

InterestHigh interest

Posts indicate a high level of curiosity about gene count normalization and its implications, as many explicitly mention the technical considerations and potential effects on downstream analysis.

EngagementModerate engagement

Several discussions reference specific methods, such as gene count normalization and experimental design, suggesting some deep engagement, although much of the content remains at an introductory to intermediate level.

ImpactModerate impact

The overall tone suggests that the community considers the publication important for methodological development, though most posts are about understanding rather than directly applying the findings, indicating moderate perceived impact.

Abstract in brief

Recent advances in imaging-based spatially resolved transcriptomics (imSRT) allow for high-throughput profiling of gene locations in tissues, but normalization of gene expression data is essential to account for technical variability.
The study shows that normalization methods based on detected gene counts can distort the actual gene expression levels, especially when gene panels overrepresent specific regions or cell types, leading to false positives or negatives in analysis.
It is recommended to use normalization approaches that do not rely on gene counts, such as cell volume or area normalization, and to carefully evaluate gene panel composition to ensure reliable biological interpretations of the data.]

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Top posts

Most liked on X and Bluesky

Dr. Jean Fan

@JEFworks · X

Learning how to share my scientific talks from home (v5) In this abbreviated talk, I discuss considerations for #geneexpression count normalization in #singlecell imaging-based #spatiallytranscriptomics

Aug 22, 2024 · 131 likes · 16 shares · 8,230 followers View post →

Lyla Atta

@lylaatta · X

Check out our now published investigation into how experimental design and analysis choices can affect downstream results when analyzing imaging-based spatial transcriptomics data. https://t.co/GTvThy7dR5

Jun 13, 2024 · 41 likes · 8 shares · 291 followers View post →

Ming "Tommy" Tang

@tangming2005 · X

Gene count normalization in single-cell imaging-based spatially resolved transcriptomics https://t.co/YxHCx8g1Lj

Oct 11, 2023 · 12 likes · 2 shares · 41,024 followers View post →

bioRxiv Bioinfo

@biorxiv_bioinfo · X

Gene count normalization in single-cell imaging-based spatially resolved transcriptomics https://t.co/MPjRVzNWuX #biorxiv_bioinfo

Sep 1, 2023 · 8 likes · 2 shares · 18,086 followers View post →

bioRxivpreprint

@biorxivpreprint.bsky.social · Bluesky

Gene count normalization in single-cell imaging-based spatially resolved transcriptomics https://www.biorxiv.org/content/10.1101/2023.08.30.555624v1

Sep 1, 2023 · 1 like View post →

bioRxiv Bioinfo

@biorxiv-bioinfo.bsky.social · Bluesky

Gene count normalization in single-cell imaging-based spatially resolved transcriptomics https://www.biorxiv.org/content/10.1101/2023.08.30.555624v1

Sep 1, 2023 · 1 like View post →

All mentions

Gene Count Normalization in Spatial Transcriptomics Data Analysis

This video discusses gene count normalization in single-cell imaging-based spatial transcriptomics, highlighting the importance of choosing appropriate normalization methods to avoid data distortion. It emphasizes…

Prof. Jean Fan · Aug 22, 2024 1,707 views

Ken Xie

@CuriousKX · X

RT @JEFworks: Learning how to share my scientific talks from home (v5) In this abbreviated talk, I discuss considerations for #geneexpress…

Aug 24, 2024 · 16 shares · 119 followers View post →

Kévin Lebrigand, PhD

@kevinlebrigand · X

RT @JEFworks: Learning how to share my scientific talks from home (v5) In this abbreviated talk, I discuss considerations for #geneexpress…

Aug 23, 2024 · 16 shares · 403 followers View post →

Mo Ebrahimkhani

@MoEbrahimkhani · X

RT @JEFworks: Learning how to share my scientific talks from home (v5) In this abbreviated talk, I discuss considerations for #geneexpress…

Aug 23, 2024 · 16 shares · 1,212 followers View post →

priya joseph

@ayirpelle · X

RT @JEFworks: Learning how to share my scientific talks from home (v5) In this abbreviated talk, I discuss considerations for #geneexpress…

Aug 23, 2024 · 16 shares · 4,875 followers View post →

Paul Geeleher

@PGeeleher · X

RT @JEFworks: Learning how to share my scientific talks from home (v5) In this abbreviated talk, I discuss considerations for #geneexpress…

Aug 23, 2024 · 16 shares · 652 followers View post →

Gioele La Manno

@GioeleLaManno · X

RT @JEFworks: Learning how to share my scientific talks from home (v5) In this abbreviated talk, I discuss considerations for #geneexpress…

Aug 23, 2024 · 16 shares · 3,307 followers View post →

sunshine

@sunshin21502307 · X

RT @JEFworks: Learning how to share my scientific talks from home (v5) In this abbreviated talk, I discuss considerations for #geneexpress…

Aug 23, 2024 · 16 shares · 27 followers View post →

yancui

@civy1216 · X

RT @JEFworks: Learning how to share my scientific talks from home (v5) In this abbreviated talk, I discuss considerations for #geneexpress…

Aug 23, 2024 · 16 shares · 10 followers View post →

Morange Nathaly

@ScBioinfoGirl · X

RT @JEFworks: Learning how to share my scientific talks from home (v5) In this abbreviated talk, I discuss considerations for #geneexpress…

Aug 23, 2024 · 16 shares · 3 followers View post →

Jen Li

@DrJenLi_Renal · X

RT @JEFworks: Learning how to share my scientific talks from home (v5) In this abbreviated talk, I discuss considerations for #geneexpress…

Aug 23, 2024 · 16 shares · 670 followers View post →

Johns Hopkins Engineering

@HopkinsEngineer · X

RT @JEFworks: Learning how to share my scientific talks from home (v5) In this abbreviated talk, I discuss considerations for #geneexpress…

Aug 22, 2024 · 16 shares · 17,515 followers View post →

Isaac Vidal, MSc

@IsaacVidalPar · X

RT @JEFworks: Learning how to share my scientific talks from home (v5) In this abbreviated talk, I discuss considerations for #geneexpress…

Aug 22, 2024 · 16 shares · 356 followers View post →

Yilin

@yilinyang0619 · X

RT @JEFworks: Learning how to share my scientific talks from home (v5) In this abbreviated talk, I discuss considerations for #geneexpress…

Aug 22, 2024 · 16 shares · 23 followers View post →

Vitalii Kleshchevnikov, PhD

@vitaliikl · X

RT @JEFworks: Learning how to share my scientific talks from home (v5) In this abbreviated talk, I discuss considerations for #geneexpress…

Aug 22, 2024 · 16 shares · 1,796 followers View post →

Joshua G. Schraiber

@jgschraiber · X

RT @JEFworks: Learning how to share my scientific talks from home (v5) In this abbreviated talk, I discuss considerations for #geneexpress…

Aug 22, 2024 · 16 shares · 7,740 followers View post →

Dr. Jean Fan

@JEFworks · X

Learning how to share my scientific talks from home (v5) In this abbreviated talk, I discuss considerations for #geneexpression count normalization in #singlecell imaging-based #spatiallytranscriptomics

Aug 22, 2024 · 131 likes · 16 shares · 8,230 followers View post →

choiLab

@jungminchoilab · X

RT @lylaatta: Check out our now published investigation into how experimental design and analysis choices can affect downstream results whe…

Jun 13, 2024 · 8 shares · 330 followers View post →

HopkinsMDPhD

@HopkinsMDPhD · X

RT @lylaatta: Check out our now published investigation into how experimental design and analysis choices can affect downstream results whe…

Jun 13, 2024 · 8 shares · 638 followers View post →

Keith Robison

@OmicsOmicsBlog · X

RT @lylaatta: Check out our now published investigation into how experimental design and analysis choices can affect downstream results whe…

Jun 13, 2024 · 8 shares · 9,983 followers View post →

Toshiro Hara

@hara_toshiro · X

RT @lylaatta: Check out our now published investigation into how experimental design and analysis choices can affect downstream results whe…

Jun 13, 2024 · 8 shares · 604 followers View post →

Yannis Ntekas

@ntekasi · X

RT @lylaatta: Check out our now published investigation into how experimental design and analysis choices can affect downstream results whe…

Jun 13, 2024 · 8 shares · 305 followers View post →

SEQanswers

@SEQanswers · X

RT @lylaatta: Check out our now published investigation into how experimental design and analysis choices can affect downstream results whe…

Jun 13, 2024 · 8 shares · 3,227 followers View post →

Lyla Atta

@lylaatta · X

Check out our now published investigation into how experimental design and analysis choices can affect downstream results when analyzing imaging-based spatial transcriptomics data. https://t.co/GTvThy7dR5

Jun 13, 2024 · 41 likes · 8 shares · 291 followers View post →

zhenzhen wang

@zhenzhen_wang · X

RT @tangming2005: Gene count normalization in single-cell imaging-based spatially resolved transcriptomics https://t.co/YxHCx8g1Lj

Oct 11, 2023 · 2 shares · 15 followers View post →

Ming "Tommy" Tang

@tangming2005 · X

Gene count normalization in single-cell imaging-based spatially resolved transcriptomics https://t.co/YxHCx8g1Lj

Oct 11, 2023 · 12 likes · 2 shares · 41,024 followers View post →

Ikemen

@HandsomeKinoko · X

Gene count normalization in single-cell imaging-based spatially resolved transcriptomics｜Ikemen Mas Kot @HandsomeKinoko #note https://t.co/cZ07x5PE50

Sep 9, 2023 · 1,273 followers View post →

Scholars Corner

@scholarscorner_ · X

RT @biorxiv_bioinfo: Gene count normalization in single-cell imaging-based spatially resolved transcriptomics https://t.co/MPjRVzNWuX #bio…

Sep 3, 2023 · 2 shares · 10 followers View post →

Monika Mohenska

@m_mohenska · X

RT @biorxiv_bioinfo: Gene count normalization in single-cell imaging-based spatially resolved transcriptomics https://t.co/MPjRVzNWuX #bio…

Sep 2, 2023 · 2 shares · 401 followers View post →

bioRxiv Bioinfo

@biorxiv-bioinfo.bsky.social · Bluesky

Gene count normalization in single-cell imaging-based spatially resolved transcriptomics https://www.biorxiv.org/content/10.1101/2023.08.30.555624v1

Sep 1, 2023 · 1 like View post →

bioRxivpreprint

@biorxivpreprint.bsky.social · Bluesky

Gene count normalization in single-cell imaging-based spatially resolved transcriptomics https://www.biorxiv.org/content/10.1101/2023.08.30.555624v1

Sep 1, 2023 · 1 like View post →

bioRxiv Bioinfo

@biorxiv_bioinfo · X

Gene count normalization in single-cell imaging-based spatially resolved transcriptomics https://t.co/MPjRVzNWuX #biorxiv_bioinfo

Sep 1, 2023 · 8 likes · 2 shares · 18,086 followers View post →