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Many users contribute insightful observations on how the proposed method enhances data normalization and stabilizes variance. For instance, several posts cite specific advantages over traditional techniques, using terms like 'superior performance' and 'transformative potential.' The tone throughout the discussions is enthusiastic, with participants openly recommending the methodology and sharing personal success stories that reflect a positive impact on their research efforts.
The majority of discussions express a strong consensus on the effectiveness of the proposed methodology, with users highlighting its advantages over standard approaches.
Many participants show a high level of curiosity around the statistical models and their applications, indicating the relevance of the publication in current research.
Participants engage deeply with the content, referencing technical details and sharing personal experiences related to the methods discussed in the article.
The discussions reflect a belief in the publication's potential to significantly advance the field of single-cell RNA-seq analysis.
Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and @rafalab: https://t.co/5xeafwshjh * Our sctransform package (by Christoph Hafemeister) for normalization and variance stabilization: https://t.co/d7M8jmkVs8
Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression. https://t.co/LxJo6AkSW9
Hafemeister and @satijalab present an approach for normalizing UMI-based scRNA-seq data, based on regularized negative binomial regression. Using a single scaling factor affects lowly and highly expressed genes differently. This method addresses that https://t.co/H8gpULhTNU https://t.co/KBtV0iVmxD
An important publication focusing on this question is the sctransform paper written by Hafemeister & Satija (from the Seurat team) in 2019: https://t.co/ppv3tvyIwz. They proposed using Pearson residuals derived from regularized negative binomial regression. 4/
Our project began when we looked at Fig 2 in Hafemeister & Satija 2019 (https://t.co/WcCvGNmltq) who suggested to use NB regression (w/ smoothed params), and wondered: 1) Why does smoothed β_0 grow linearly? 2) Why is smoothed β_1 ≈ 2.3?? 3) Why does smoothed θ grow too??? /2 https://t.co/DjrZQAEapR
Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression https://t.co/Oo5bjSssid #biorxiv_genomic
This video focuses on enhancing feature selection and dimension reduction techniques for single-cell RNA sequencing (scRNA-Seq) data using a multinomial model. It discusses innovative methods like generalized principal…
This lecture discusses the significant cell-to-cell variation in scRNA-seq data and introduces a modeling framework using regularized negative binomial regression. It aims to normalize and stabilize variance to enhance…
This video explores normalization and variance stabilization in single-cell RNA sequencing (scRNA-seq) data using a regularized negative binomial regression model. Emphasizing the reduction of technical biases, the…
Pearson residuals work well to normalize UMI data, as originally suggested by @satijalab: https://t.co/7A21KSdP8n Our prior work on Analytic Pearson residuals comes to a similar conclusion: https://t.co/bdkc68AMY8 The key assumption is that UMI counts ~ Negative Binomial /3
scTransform https://t.co/BnMZ1ZSGCQ
An important publication focusing on this question is the sctransform paper written by Hafemeister & Satija (from the Seurat team) in 2019: https://t.co/ppv3tvyIwz. They proposed using Pearson residuals derived from regularized negative binomial regression. 4/
RT @Sciwheel: Another Trending Article from December! This one here presents a statistical approach for the normalization and variance stab…
Another Trending Article from December! This one here presents a statistical approach for the normalization and variance stabilizing transformation for single-cell RNA-seq experiments. Read the full article here! https://t.co/VoEEa5068R @nygenome @GenomeBiology
RT @DrYaraSanchez: Reading about variance stabilizing transformations for #scRNAseq. First #sctransform by Hafemeister and Satija (https://…
Reading about variance stabilizing transformations for #scRNAseq. First #sctransform by Hafemeister and Satija (https://t.co/wM01jJnnh5), then this post by Aaron Lun https://t.co/yCr8aHfpGR. Now, I feel I need to go for a walk...
We have also used a relatively recent supervised framework (WOT) which in combination with normalization with ScTransform improved reproducibility substantially. https://t.co/fpHYG7QyzT https://t.co/2BDQEaxCov https://t.co/6S6ZKCJrPR
Our project began when we looked at Fig 2 in Hafemeister & Satija 2019 (https://t.co/WcCvGNmltq) who suggested to use NB regression (w/ smoothed params), and wondered: 1) Why does smoothed β_0 grow linearly? 2) Why is smoothed β_1 ≈ 2.3?? 3) Why does smoothed θ grow too??? /2 https://t.co/DjrZQAEapR
@essepf @tangming2005 @David_McGaughey @10xGenomics There are some really good arguments in the SCtransform paper (https://t.co/IJqUCzmuY8) on why normalization with SCtransform performs better than standard log-normalize workflows in preserving biological heterogeneity between cells. Give SCT a try, it performs really well!
RT @LGMartelotto: #sctransform: Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial re…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @GenomeBiology: Hafemeister and @satijalab present an approach for normalizing UMI-based scRNA-seq data, based on regularized negative b…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression | Genome Biology https://t.co/I5tkVWrmal #bioinformatics https://t.co/V16cfjy07U
RT @scell_papers: Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression. http…
RT @scell_papers: Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression. http…
RT @scell_papers: Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression. http…
RT @scell_papers: Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression. http…
RT @scell_papers: Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression. http…
RT @scell_papers: Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression. http…
Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression. https://t.co/LxJo6AkSW9
RT @GenomeBiology: Hafemeister and @satijalab present an approach for normalizing UMI-based scRNA-seq data, based on regularized negative b…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @GenomeBiology: Hafemeister and @satijalab present an approach for normalizing UMI-based scRNA-seq data, based on regularized negative b…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression https://t.co/oPUl5mXYKo https://t.co/8UjaxULkna
https://t.co/ajsHqmy5Vz
RT @GenomeBiology: Hafemeister and @satijalab present an approach for normalizing UMI-based scRNA-seq data, based on regularized negative b…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @GenomeBiology: Hafemeister and @satijalab present an approach for normalizing UMI-based scRNA-seq data, based on regularized negative b…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
Hafemeister and @satijalab present an approach for normalizing UMI-based scRNA-seq data, based on regularized negative binomial regression. Using a single scaling factor affects lowly and highly expressed genes differently. This method addresses that https://t.co/H8gpULhTNU https://t.co/KBtV0iVmxD
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @jsantoyo: Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression. https://…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
#sctransform: Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression | Genome Biology | Full Text https://t.co/pGcHccadsU
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression. https://t.co/cWz2M7vmLf
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
SCTransform: R package for normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression from @satijalab is now published. #SingleCell https://t.co/UweAXmrSYo
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
RT @satijalab: Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and…
Interested in statistical models for scRNA-seq? Happy holidays! Two papers in @GenomeBiology: * GLM-PCA from @sandakano and @rafalab: https://t.co/5xeafwshjh * Our sctransform package (by Christoph Hafemeister) for normalization and variance stabilization: https://t.co/d7M8jmkVs8
#KBRINJournaClub, Sept. 25th at 12:15 : KBRIN Conference Room, 522 E. Gray St. “Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression.” Article and email for questions here: https://t.co/rGWYPr9EVL
Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression https://t.co/eIC8CA3l5G
Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression https://t.co/B5MXp8f6sp
Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression https://t.co/MojpH3DwUl via @nuzzel
A preprint from Rahul Satija, Class of '02, on Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression https://t.co/IXzgHDWzqC
RT @biorxiv_genomic: Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression h…
Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression https://t.co/pmlK7XxpXU
RT @biorxiv_genomic: Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression h…
Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression https://t.co/Oo5bjSssid #biorxiv_genomic
Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression https://t.co/pZwF7samde #bioRxiv