version 1.2.0
Updates
- Add subsetting option for the Shiny heatmaps and bubbleplots. The
subset is based on already existing metadata columns.
- Use
leidenbase package for Leiden clustering instead of
leiden (aligning with Seurat’s changes). Algorithm=6
contains the leidenbase implementation, whereas algorithm=4 and 5 are
associated with leiden (for matrix and igraph input objects,
respectively).
- Minimise redundant calculations of the adjacency matrix in the
automatic assessment.
- Add function that calculates the nn2 index in parallel.
- Add an ordering of the points in the metadata shiny plots based on
the order of the input subgroups.
- Scale the colour values of gene expression in ShinyApp based on
provided cap value.
- Control the number of values shown on the continuous UMAP
legend.
- Add option to download multiple genes in separate UMAP files.
- Removes
ggtext dependency from the package (used in the
shiny gene UMAP plots).
Fixes
- Ensure the expression matrix or embedding has row names. If not, set
them to “cell_1”, “cell_2”, etc.
- Treat the case when enrichment analysis returns no results.
- Sort the group 2 markers for enrichment analysis based on the
absolute logfoldchange.
- Discard the metadata columns with too many unique values for
visualisation in the Shiny app.
- When creating a Seurat object, the number of PCs is set to the
minimum between 30 and half the number of genes. This is to avoid errors
when the number of genes is low.
version 1.1.0
Updates
- Add barplot with Cell count or percentage of metadata in the Shiny
context.
- Add option to combine (split) metadata and dynamically create a new
metadata column in the Shiny context.
- Add option to calculate the percentage of cells expressing gene
above a threshold in the summary table from the Shiny Violin
section.
- Add hierarchical plot that shows the relationship between partitions
with different number of clusters.
- Add the option to create the ClustAssess app without the need to run
the stability assessment (the light version). If the clustassess
parameter is NULL, the app will contain only the ‘Comparison’ tab. In
this case, the user should provide the UMAP coordinates in the metadata
dataframe.
- Enable live filtering of the marker genes based on all the columns.
The filtered table will be used as input for the enrichment
analysis.
Fixes
- Fix the case in
write_object when the gene variance
filtering leaves the chunk with one or zero genes.
- Stop allowing the user to calculate the ECC or perform the merging
to a list with less than two partitions by raising an exception.
- Sort the k values numerically in the
merge_resolutions
function.
- Fix the
qualpalr colour space parameter in the
add_metadata function.