Edward Zhao

Biostatistics PhD candidate at UW-Seattle.

[Edward Zhao @edward130603]

Check out BayesSpace, our #Bayesian #Rstats tool for clustering and resolution enhancement of @10xGenomics #spatialtranscriptomics data. Bring your data to near #singlecell resolution.

Paper on @NatureBiotech: https://t.co/bcBLopREkj

w/@raphg @m_sto @BielasLab @FH_IRC @ 1/5

[Zhiqiang Sha (@zhiqiangsha.bsky.social) @sha_zhiqiang]

We used BayesSpace to perform a data-driven analysis based on gene expression profiles, identifying layer-like clustering in cerebral
cortical tissue samples. @edward130603 @raphg, thanks for developing such an amazing approach.

[Daniela Bezdan @Daniela_Bezdan]

@mason_lab @nanostringtech dropping the news of the SAHA project, detailed resolution in #spatialgenomics with 120-plex CosMx SMI @agbt #agbt23

[Abizar Lakdawalla @LAbizar]

#agbt23 @mason_lab @nanostringtech CosMx RNA and Protein plus GeoMx coding RNA on Prostate, clearly see the 'private lives of cells'. Next liver, see new cells or cell states by RNA expression. My take, goodbye Single cells, welcome Spatial!

[Edward Zhao @edward130603]

I think this partly arises from a tendency for authors to visualize the sample that gave good results for their method. We’ve found more consistent results across samples when using the joint clustering approach https://t.co/If9NMSHSjV

[Lior Pachter @lpachter]

The fact that

SingleCellExperiment →← Seurat →← Scanpy

has had numerous repercussions for single-cell genomics, including inconsistencies in results, siloing of tools and methods, and one-off papers that die upon publication.

[Edward Zhao @edward130603]

@SSuthram https://t.co/YMEyRvwTnJ I thought this one was pretty good last year.

[Stephanie Hicks, PhD @stephaniehicks]

Edward Zhao @edward130603 from @UWBiostat presenting a Markov random field method to cluster #spatial #transcriptomics data (BayesSpace) #ENAR2022

🔗 https://t.co/QJ4ugvJ7qS

[Vitalii Kleshchevnikov, PhD @vitaliikl]

My 1st paper out in @NatureBiotech 🎉 Thread as promised👇
Cell2location, built from first principles, improves the sensitivity and scale of tissue atlasing (combines single cell + spatial transcriptomics).
Amazing teamwork @bayraktar_lab @OliverStegle https://t.co/NSU5ljezk4 1/n

[🇲🇽 Leonardo Collado-Torres @lcolladotor]

Thank you @10xGenomics Jess Dines, Dan Walker, @JKat10x, @SvenAT for inviting me to present at "Extending Spatial Analysis With Third-Party Bioinformatics Tools" 😊

https://t.co/1NoiuxCJuz @OGConferences

Spreading the #rstats @Bioconductor 💕

Slides at https://t.co/t7GHkj1vGu

[Fred Hutch Cancer Center @fredhutch]

'Infinity Flow’ adds machine learning to widespread, but limited, technology for analyzing single cells - new paper in @ScienceAdvances by @headleylab @raphg @EvNewell1 @EtienneBecht https://t.co/QYrebKpy29

[Rong Fan @RongFan8]

Dear Spatial Omics fans, our seminar series 6 is kicking off next week. See the terrific lineup of speakers @ResolveBioSci, @vizgen_inc, @ACDbio, @spatialgenomics, @ABoettiger, @JeffSpraggins, @NanoPOTS_SCP, @MichaelYGerner, @ColeTrapnell, @IoaVlachos, @Lu_Wei8, @KellyStevensLab

[MadhaviTippani @MadhaviTippani]

Excited to share my 1st, first-author paper: https://t.co/x7SInbaVcy. Learned & accomplished so much through this process - can now call myself a ‘bookdown’, ‘LaTeX’, ‘@Overleaf’, ‘@bioRxiv, ‘@Git’ expert. Thanks to my mentors @lcolladotor , @martinowk , @CerceoPage , @kr_maynard

[Edward Zhao @edward130603]

Outline of talk:
- Overview of spatial transcriptomics analysis pipeline
- Comparison of current tools for clustering spatial data
- Package demo: joint clustering of multiple samples
- Package demo: resolution enhancement of spatial expression data in cancer
2/2

[Edward Zhao @edward130603]

@Bioconductor meeting #Bioc2021 starts tomorrow! I will be demoing the #BayesSpace #Rstats package for clustering and resolution enhancement of #spatialtranscriptomics data on 8/4/2021 at 7PM PDT.

Register at https://t.co/AZxOurWhxU
1/2

[Dr. Jean Fan @JEFworks]

Thrilled to share our #Bioinformatics work led by @bf_miller_ +team. We deconvolve multicellular pixel resolution #spatialtranscriptomics data w/o #singlecell references to recover cell-type specific spatial patterns.

📰 https://t.co/geytdjfWJq
🖥️ https://t.co/6Qv4zxNyFL #RStats

[Edward Zhao @edward130603]

And we show similar improvements in an invasive ductal carcinoma sample that had not been previously reported. Thanks to @SvenAT and @TheBioCed for providing the dataset and their feedback! Data available at: https://t.co/CMKTcRs0Cr

[Edward Zhao @edward130603]

Check out BayesSpace, our #Bayesian #Rstats tool for clustering and resolution enhancement of @10xGenomics #spatialtranscriptomics data. Bring your data to near #singlecell resolution.

Paper on @NatureBiotech: https://t.co/bcBLopREkj

w/@raphg @m_sto @BielasLab @FH_IRC @ 1/5

[Edward Zhao @edward130603]

We validate BayesSpace resolution enhancement using immunofluorescence staining. Enhancement to the subspot level resolves finer stroma/tumor boundaries in ovarian cancer and identifies intra-tumoral regions with high immune presence.