Discover and read the best of Twitter Threads about #bioc2022
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Tons of exciting new single-cell genomics tools have been showcased at #bioc2022 this week. Today @LambdaMoses presented SpatialFeatureExperiment, an S4 class extending SpatialExperiment, facilitating geospatial stats for spatial #scRNAseq using Voyager github.com/pachterlab/Voy… 1/ 
The design of SpatialFeatureExperiment and the plans for Voyager were formed from a careful study that @LambdaMoses conducted of the spatial transcriptomics field (published as the "Museum of Spatial Transcriptomics"): nature.com/articles/s4159… 2/
While there are several analysis tools for spatial transcriptomics data, and extensions of #scRNAseq platforms such as Seurat for spatial data, they have limitations in terms of the methods they implement from the field of geospatial statistics. 3/
Amy Willis @AmyDWillis
about to present on model misspecification in microbiome studies at #bioc2022
An April '22 preprint from David Clausen and Dr. Willis:
arxiv.org/abs/2204.12733
about to present on model misspecification in microbiome studies at #bioc2022
An April '22 preprint from David Clausen and Dr. Willis:
arxiv.org/abs/2204.12733
@AmyDWillis Great and simple motivation from looking at mock communities (over-detection) as to why to move away from:
E(W_ij) = c_j mu_ij (just size factor scaling)
instead use:
E(W_ij) = c_j mu_ij (just size factor scaling)
instead use:
@AmyDWillis Oops that should have been c_i, the scaling factor for sample i.
i for sample here, j for taxa here (wide count tables)
Now introducing taxon specific efficiencies e_j to account for over-detection:
i for sample here, j for taxa here (wide count tables)
Now introducing taxon specific efficiencies e_j to account for over-detection:
Eric Davis @ericscottdavis1 & Wancen Mu @WancenM presenting two branches of functionality in the {nullranges} pkg: finding matched sets of genomic ranges based on covariates & bootstrapping blocks of genomic ranges. Both play well w/ {plyranges} for downstream analysis
#bioc2022
#bioc2022
Both methods are based statistical methods for refining null comparisons. E.g. we were inspired by {MatchIt}, {cobalt} and other matching packages, as well as {GSC} for the block bootstrap (method described in Bickel et al 2010)
Development and conference attendance for Eric and Wancen was supported by an EOSS award from @cziscience. Contributions from @dphansti, @mikhaildozmorov, @_StuartLee, @timtriche and other members of #nullranges slack channel
Previously described here:
Previously described here:
