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Today, Iām thrilled to share a preprint of our work describing SPEAR, a sparse supervised #Bayesian factor model for #multiomic integration:
biorxiv.org/content/10.1101/ā¦
Follow along this #tweetorial to learn about SPEAR!
@YaleCBB
(1/š§µ)
Jeremy Gygi retweeted
Iām excited to announce that our paper on viral molecular mimicry just came out! Molecular mimicry occurs when pathogens āmimicā host protein structure. Here, we explore mimicry across the human virome and its connection to autoimmunity. @MelamedEsther
nature.com/articles/s41467-0ā¦
Jeremy Gygi retweeted
Excited to share our latest #IMPACC study on patient subtype discovery using longitudinal multi-omics! We identified 5 subtypes among 1,000+ hospitalized #COVID19 patients, highlighting the link between distinct immune responses in those with similar respiratory status to various acute complications and #LongCOVID risk. biorxiv.org/content/10.1101/ā¦
This work is co-led by wonderful students Kexin, Yutong, @colemag9, collaborators @VirusesImmunity, @JoannDArce, Lauren, and the #IMPACC consortium team.
Jeremy Gygi retweeted
We are excited to announce that the 3rd (Public) CMI-PB Challenge is officially underway! Test out your modeling skills to predict immune responses to B. pertussis #whoopingcough booster vaccination using multi-omics datasets for a chance to win. #bioinformatics #immunology (1/5)
Jeremy Gygi retweeted
Our collaborators plot an "immune health metric" that that can be applied widely. Authors include @TsangLab @skleinstein
@NatureMedicine
The IHM
- recognizes marked #aging in healthy adults
- measures age-dependent #antibody responses to #vaccines
nature.com/articles/s41591-0ā¦
Jeremy Gygi retweeted
I'm thrilled to share our new #Bioconductor package, nipalsMCIA, which performs multi-omic dimensionality reduction using the NIPALS algorithm. It is fast (especially for large datasets), and user friendly. Give it a try!
biorxiv.org/content/10.1101/ā¦ (1/4)
Jeremy Gygi retweeted
Honored for our paper on heavy + light chain B cell tree building with Dowser to be picked as a #JI_TopRead!
š#JI_TopRead ā”ļø This study by Jensen et al. optimizes workflows for building #Bcell phylogenic trees using paired H & L chain sequences. Check it out now! @hoehnousk @skleinstein. #ReadTheJI #immunology
Jeremy Gygi retweeted
Our collaborators develop modeling that helps identify multi-omic #immune #signatures
#bioinformatics @LeyingGuan @skleinstein @JeremyGygi @a_konstorum + others
pubmed.ncbi.nlm.nih.gov/3860ā¦
ALT A complex workflow for a bioinformatics paper about identifying #immune #signatures. https://pubmed.ncbi.nlm.nih.gov/38603606/
Jeremy Gygi retweeted
#ClinicalMedicine:
Integrated longitudinal multiomics study identifies immune programs associated with acute #COVID_19 severity and mortality: buff.ly/3UUBKlO
@LeyingGuan @YaleMed
#Immunology
Jeremy Gygi retweeted
Congratulations to our #IMPACC team members @LeyingGuan @JeremyGygi @colemag9 @sciRPatel for our newly published COVID-19 multiomics paper in JCI! Grateful to be working with all of you for the past few years!
I am excited to share that our #IMPACC paper - Integrated longitudinal multi-omics study identifies immune programs associated with acute COVID-19 severity and mortality - was recently published in @jclinicalinvest. jci.org/articles/view/176640 #SystemsBiology #Bioinformatics [1/5]
Our recent #IMPACC #COVID19 #multiomics study published in @jclinicalinvest is featured in @yalemed! Read about it:
"COVID-19: New āOmicsā Models Show Why Some People Are at Greater Risk of Severe Disease, Death"
m.yale.edu/ckst
@LeyingGuan @colemag9 @sciRPatel
Jeremy Gygi retweeted
I am excited to share that our #IMPACC paper - Integrated longitudinal multi-omics study identifies immune programs associated with acute COVID-19 severity and mortality - was recently published in @jclinicalinvest. jci.org/articles/view/176640 #SystemsBiology #Bioinformatics [1/5]
Jeremy Gygi retweeted
Integrated longitudinal multiomics study identifies immune programs associated with acute COVID-19 severity and mortality @jclinicalinvest @LeyingGuan
jci.org/articles/view/176640
Jeremy Gygi retweeted
Excited to share my latest research on #COVID19 and #aging, together with @ATsitsiklis and @colemag9, that just came out on @ScienceTM!
xitter.cf/czbiohub/status/178099ā¦
A new study led by #CZBiohubSF & @UCSF researchers provides fresh insights into why age is a major risk factor for severe #COVID. It is the most comprehensive analysis to date of how age affects the immune response to #SARSCoV2. 1/7
Read in @ScienceTM ā¤µļø
bit.ly/4aUR2Mc
Jeremy Gygi retweeted
SPEAR: A supervised bayesian factor model for the identification of multi-omics signatures academic.oup.com/bioinformatā¦
So happy to have had the chance to present our work on SPEAR with @LeyingGuan and @skleinstein at the @hipcProject annual meeting! Grateful for all the valuable insight and interest.
Jeremy Gygi retweeted
I am excited to announce our paper predicting #immune responses after B. pertussis (#whoopingcough) booster vaccination based on the pre-vaccination immune state is coming out in the March 25th issue on @CellRepMethods cell.com/cell-reports-methodā¦ #SystemsBiology #Bioinformatics (1/8)
Jeremy Gygi retweeted
How can models "overfit" and fail to predict in #immunology? Our collaborators @skleinstein @LeyingGuan + @JeremyGygi explain in new paper.
ncbi.nlm.nih.gov/pmc/articleā¦
On both the TCGA and COVID-19 datasets, we demonstrate that SPEAR is able to construct biologically significant multi-omic factors, finding key pathways and insights that are backed by literature.
(12/13)
If you are working with any type of āomicsā data and have a desire to find predictive analytes for a response of interest, we offer SPEAR as a free publicly available R-package. Feel free to reach out with any questions you may have.
biorxiv.org/content/10.1101/ā¦
Thank you!
(13/13)
