Thrilled to announce my 1st paper from @stevens1lab is now published @NatureNeuro. “Dissection of Artifactual and Confounding Glial Signatures by scRNA-seq of Mouse and Human Brain”. Why is it important? a 🧵👇 #singlecell #microglia #methodsmatter 1/n https://t.co/oAyJbduTqJ

🚨 We're hiring! 🚨 The Morris Lab @BrighamWomens & @harvardmed is looking for a Research Technician to join our team! 🔬 Focus: Lineage reprogramming & genomic tech development 🧫 Skills: Molecular biology, cell culture, mouse work 📍 Boston, MA https://t.co/I1APZMfP8l

Our #bionformatics #Rstats method CRAWDAD (Cell-type Relationship Analysis Workflow Done Across Distances) for quantifying cell-type spatial relationships in #singlecell #spatialomics data is now published! https://t.co/Ij7uuWU3BY Congrats to the team 🥳🥂 #AcademicTwitter

Finally, as always, I want to thank everyone who uses scCustomize. I could never have imagined it would be adopted & used by some many people & it’s really fantastic every time I read paper or see plot that was made using scCustomize. Happy single cell analysis!!! 💻📈🧬 20/20

As always there are a ton of bug fixes in this update here too. Thank you to everyone who has report issues on GitHub! There’s more in this update too besides these highlights so check out changelog for full details!! 19/n

A number of functions have updated parameters, including `Clustered_DotPlot` which has 8!! new parameters to further customize the output plot and plot legends. See changelog for full details on new/updated parameters in this update. 18/n

scCustomize now includes `seq_zeros` function to easily create sequences with preceding zeros. You can either specify the number of preceding zeros desired or the function will set automatically based on sequence length. 17/n

The base R `seq` family of functions has a ton of uses. However, due to the way numbers are ordered in R (& other software) it can sometimes be helpful to have preceding zeros in your sequences to keep things in numerical order (e.g., 01, 02, 03, instead of 1, 2, 3). 16/n

Now here’s two functions that aren’t limited to scRNA-seq analysis but can generally be helpful in your work in R. First, `Split_Vector` which allows you to split a vector in a specified number of chunks or chunks of specific length. 15/n

Now we supply that to `cells` in `DoHeatmap` and the result now looks like this. We can now clearly visualize the differences in expression between the identities. To make it even easier you can also just call `Random_Cells_Downsample` from within the `DoHeatmap` call. 14/n

However, by using `Random_Cells_Downsample` we can create a plot with equal number of cells per identity for proper visualization. Here I create a down sampled cell vector of 150 cells per group (or the max number of cells for groups smaller than 150 cells). 13/n

The default cell level heatmap scales the size of each identity based on the number of cells. This can lead to heatmaps where visualizing the expression in small clusters can be nearly impossible. 12/n

This update also contains new function `Random_Cells_Downsample` to return randomly downsampled set of cells with equal numbers of cells per identity. There are many scenarios where this can be helpful but one that I use a lot is when plotting cell-level heatmaps. 11/n

Just like human function, `Updated_MGI_Symbols` requires one time internet connection to download the MGI file but then stores it in local cache so not internet is required for subsequent use. 10/n

The last scCustomize update brought the advance of `Updated_HGNC_Symbols` for updating human gene symbols. This update brings the equivalent function of mice using MGI database: `Updated_MGI_Symbols`. 9/n

scCustomize also makes it’s first venture in spatial plotting with addition of `SpatialDimPlot_scCustom` which is sibling to `DimPlot_scCustom` and contains similar updates to color scheme and other defaults. See new spatial vignette for details: https://t.co/0AknunI6Q0 8/n

One new plotting function “Factor_Cor_Plot” has been added which will plot correlation between feature loadings of liger iNMF factors (works with both Seurat and Liger objects). LIGER vignette is in progress and will I get that finished as soon as I can! 7/n

Old liger functions have been updated to enable working with either old or new style liger objects. New liger interaction functions have been added. “Subset_LIGER”, “Cells_by_Identities_LIGER”. 6/n

scCustomize v3.0.0 contains massive updates for interaction with new style liger objects (liger v2.0.0+). Changelog contains the full updates list but some highlights are: Extending Seurat generic functions to work with liger (Cells, Features, Idents, WhichCells, etc) 5/n

In addition to new species and metrics `Add_Cell_QC` is now S3 generic function and works with either Seurat or Liger objects. I have also added new vignette specifically dedicated to this and other QC functions in scCustomize. https://t.co/8RE6Zm1hOg 4/n

`Add_Cell_QC` also can work with ensembl IDs instead of feature names and has all ensembl IDs for default species stored within the package, no download required! 3/n