NEWS.md
drop_uninformative_genes
:
check_sce()
function.bootstrap_enrichment_test
:
standardise_sct_data=
, standardise_hits=
: let users have more control over data standardisation steps.check_ewce_genelist_inputs
: updated accordingly.store_gene_data
to avoid hitting memory limits.ewce_plot()
- Dendrogram not reordering cell types in plot
make_dendro = TRUE
for ewce_plot()
.generate_bootstrap_plots
check_ewce_genelist_inputs()
call.check_ewce_genelist_inputs
/bootstrap_enrichment_test
sctSpecies_origin
lets users clarify that their data originally came from mouse even when it is currently formatted as human orthologs. This is necessary for creating the appropriate background gene lists.grDevices
as dep entirely.fix_celltype_names
make_unique
to make this function easily usable for vectors where the same celltype appears multiple times.bootstrap_enrichment_test
generate_bootstrap_plots
. now stored as a list element named gene_data
in data.table
format.generate_bootstrap_plots
gene_data
. It will also tell you which of these options it’s using.ggsave
instead if grDevices
.adj_pval_thresh
savePath
arg to the more accurate save_dir
. Expose appending BootstrapPlots to the user within the argument.generate_bootstrap_plots_for_transcriptome
savePath
arg to the more accurate save_dir
. Expose appending BootstrapPlots to the user within the argument.ggsave
instead if grDevices
.hits
+ hitGenes
arg all to hits
.drop_uninformative_genes
/ generate_celltype_data
verbose
arg to matrix formatting functions.generate_controlled_bootstrap_geneset
combinedGenes
arg as it was not being used anywhere within.check_args_for_bootstrap_plot_generation
ttSpecies
, sctSpecies
orthogene
databases improving.rworkflows
GHA.
rworkflows::use_badges
to README.Rmd.ewceData (>=1.7.1)
is now required, due to a fix made only in the development version of rtracklayer
.cowplot
dependency.%>%
with |>
calc_quantiles
:
filter_variance_quantiles
stats::ecdf
vs. dplyr::ntile
methods.EWCE
as it’s not longer used anywhere.bin_columns_into_quantiles
:
matrixIn
–> vec
to reflect what the function actually does.filter_variance_quantiles
:
bin_columns_into_quantiles
instead of calc_quantiles
to be consistent with how quantiles are handled in the rest of EWCE
.stats::quantile
).ewce_plot
:
gridArrange
/cowplot
to patchwork
.filter_ctd_genes
get_ctd_matrix_names
: New function to get a list of all data matrices in CTD.check_ewce_genelist_inputs
:
standardise_ctd
:
check_species()
as_sparse=TRUE
.fix_celltype_names
:
orthogene
, so going through and making sure everything still works / is able to take advantage of new features (e.g. separation of non121_strategy
and agg_func
args, many:many mapping):
filter_nonorthologs
: Pass up args from orthogene::convert_orthologs
.generate_celltype_data
: @inheritDotParamsmethod
argument from orthogene::create_background
and orthogene::convert_orthologs
is now passed up as an argument to EWCE
functions to give users more control. “homologene” chosen as default for all functions. “homologene” has fewer species than “orthogene” but doesnt need to import data from the web. It also has more 1:1 mouse:human orthologs.bin_specificity_into_quantiles
to set specificity matrix name produced.orthogene
.standardise_ctd
.DelayedArray
object class.plot_ctd
).EWCE::example_bootstrap_results()
.BiocCheck
, and rebuild/deploy pkgdown site.drop_uninformative_genes
generate_celltype-data
bootstrap_enrichment_test
ewceData
files have to be downloaded):
test-DelayedArray
test-merge_sce
test-get_celltype_table
test-list_species
test-run_DGE
test-check_percent_hits
is_32bit()
to all tests to ensure they don’t get run twice on Windows OS.check-bioc-docker.yml
: Runs CRAN/Bioc checks, rebuilds and pushes pkgdown
website, runs and uploads test coverage report,dockerhub.yml
: Builds Bioconductor Docker container with EWCE
installed, runs CRAN checks and (if checks are successful) pushes container to neurogenomicslab DockerHub.docs
folder, as the documentation website comes from the gh-pages branch now, and is automatically built by GHA workflow after each push to main branch.fix_celltype_names
to help with standardising celltype names in alignment with standardise_ctd
.generate_bootstrap_plots_for_transcriptome
: Now supports any species (not just mouse or human).
tt
) into output_species
gene symbols.ewce_expression_data
via new example_transcriptome_results
function.@return
documentation for internal functions.test_
==> test-
drop_uninformative_genes
for now until we run benchmarking to see how each affects the EWCE
results.bootstrap_plots
function internal.orthogene
improve within- and across-species gene mappings in extended vignette.standardise_ctd
output:
input_species
and output_species
EWCE
, orthogene
, and homologene
drop_uninformative_genes()
has been expanded to allow the utilisation of differential expression approachesDeprecated & Defunct
check.ewce.genelist.inputs
cell.list.dist
bootstrap.enrichment.test
bin.specificity.into.quantiles
bin.columns.into.quantiles
add.res.to.merging.list
prepare.genesize.control.network
prep.dendro
get.celltype.table
calculate.specificity.for.level
calculate.meanexp.for.level
generate.celltype.data
generate.bootstrap.plots
generate.bootstrap.plots.for.transcriptome
fix.bad.mgi.symbols
fix.bad.hgnc.symbols
filter.genes.without.1to1.homolog
ewce.plot
cells.in.ctd
drop.uninformative.genes