#scrna — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #scrna, aggregated by home.social.
-
Any #tiledb #scRNA users out there?
I am ingesting data from an `h5ad` file into a soma with `tiledbsoma.io.from_h5ad` (#python API).
Does this function load the entire h5ad into memory before conversion? Python keeps crashing which I am guessing are OOO issues. If yes, is there another option to do this conversion without loading the data in memory?
It would be strange if the only option is to load the whole thing into memory considering how massive scRNA datasets are these days.
-
Any #tiledb #scRNA users out there?
I am ingesting data from an `h5ad` file into a soma with `tiledbsoma.io.from_h5ad` (#python API).
Does this function load the entire h5ad into memory before conversion? Python keeps crashing which I am guessing are OOO issues. If yes, is there another option to do this conversion without loading the data in memory?
It would be strange if the only option is to load the whole thing into memory considering how massive scRNA datasets are these days.
-
So excited to share MMoCHi: a tool I've built for multi-modal cell type classification for CITE-seq data
The pre-print can be found here:
https://www.biorxiv.org/content/10.1101/2023.07.06.547944v1And we've put it out on #GitHub so that you can try it out on your own data:
https://mmochi.readthedocs.io
#scRNAseq #scRNA #CITEseq #sequencing #analysis #ColumbiaUniversity #immunology -
@InnesBT This review paper by Gasperini, Tome, and Shendure is pretty good for the biology and protocols you can use for answering questions like this:
https://www.nature.com/articles/s41576-019-0209-0
It covers a lot o protocols and methods (#MPRA, #CRISPR screens, #eQTLs, #scRNA-seq, etc), but it doesn't focus as much on the computational construction of those things.
-
I'm excited about this new #genomics #scRNA #rnaseq preprint from @ariel_hippen! It's a molecular biology deep dive into what happens when you dissociate and single-cell sequence a tissue with the goal of performing deconvolution of bulk tissue.
Some key bits: there are dissociation effects, RNA capture/depletion effects, and potentially some microfluidics effects with the #10X platform. Also, deconvolution algorithms are variably robust to these things.
See more:
https://www.biorxiv.org/content/10.1101/2022.12.04.519045v1