Genome Biol May 2021 PMID 34034771

scDesign2: a transparent simulator that generates high-fidelity single-cell gene expression count data with gene correlations captured.

Tianyi Sun, Dongyuan Song, Wei Vivian Li, Jingyi Jessica Li

Full text PDF Download social card

Mentions

Peak: 40 in May 2021

across 2 sources since May 2021

Extended reach

610,623

potential audience

Total likes

143

Video views

1,722

Mentions per month

May 2021 – Jun 2024

Where it's discussed

X / Twitter76 posts
YouTube2 videos

AI synopsis

What people are saying

The discussions surrounding the publication often mention scDesign2’s ability to maintain gene correlations and generate high-fidelity data, with comments emphasizing its relevance in fields like data science and bioinformatics. Phrases such as 'transformative tool' and mentions of its probabilistic model suggest that many users are not only aware of scDesign2's capabilities but see it as a significant innovation in the field, which contributes to the overall positive sentiment.

AgreementModerate agreement

Most discussions reflect a supportive stance towards scDesign2, with several users highlighting its innovative features.

InterestHigh interest

There is strong curiosity about the capabilities of scDesign2, evidenced by multiple users engaging with aspects of the simulator.

EngagementHigh engagement

Discussions delve into specific technical features, such as the use of copulas, indicating a deeper understanding and connection to the topic.

ImpactHigh impact

Participants perceive this simulator as having significant potential to advance research in single-cell transcriptomics.

Abstract in brief

scDesign2 is a new simulator designed to create realistic single-cell gene expression data while preserving gene correlations.
It addresses key challenges in single-cell transcriptomics by meeting three objectives: maintaining gene integrity, capturing correlations, and generating variable cell counts.
The simulator employs probabilistic models and utilizes copulas to enhance its transparency and precision in generating high-quality synthetic data.

Read the full abstract

All mentions

Statistical Rigor in Genomics Data Analysis and Hypothesis Testing Guidance

Jingyi Jessica Li discusses the importance of statistical rigor in genomics data science, covering differential expression analysis, gene expression simulation, and FDR control, with practical guidelines for making…

Computational Genomics Summer Institute CGSI · Nov 14, 2022 1,467 views

Advanced Differential Expression Analysis with Clipper Method

JSB UCLA · Jun 4, 2024 255 views

Daniel Osorio

@dcosorioh · X

@mo_lotfollahi If you have a reference dataset with the cell types you are interested in, you may use scDesign2 https://t.co/KQ2rP5jUEN

Jan 10, 2024 · 1 like · 435 followers View post →

Simona Cristea

@simocristea · X

The paper introduces scDesign2, a simulator that specifically models not only the marginal distributions of individual genes, but also the joint distribution of thousands of genes. https://t.co/s5vPIuC55Q https://t.co/qrJ63jhntF

Mar 3, 2023 · 1 like · 9,466 followers View post →

TensorFlow Bot

@bot_tensorflow · X