EWCE-package
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EWCE: Expression Weighted Celltype Enrichment |
add_res_to_merging_list()
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Add to results to merging list |
bin_columns_into_quantiles()
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bin_columns_into_quantiles
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bin_specificity_into_quantiles()
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bin_specificity_into_quantiles |
bootstrap_enrichment_test()
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Bootstrap cell type enrichment test |
check_ewce_genelist_inputs()
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check_ewce_genelist_inputs |
check_percent_hits()
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Get percentage of target cell type hits |
controlled_geneset_enrichment()
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Celltype controlled geneset enrichment |
convert_new_ewce_to_old()
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convert_new_ewce_to_old |
convert_old_ewce_to_new()
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convert_old_ewce_to_new |
drop_uninformative_genes()
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Drop uninformative genes |
ewce_expression_data()
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Bootstrap cell type enrichment test for transcriptome data |
ewce_plot()
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Plot EWCE results |
example_bootstrap_results()
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Example bootstrap enrichment results |
filter_genes_without_1to1_homolog()
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filter_genes_without_1to1_homolog |
filter_nonorthologs()
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Filter non-orthologs |
fix_bad_hgnc_symbols()
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fix_bad_hgnc_symbols |
fix_bad_mgi_symbols()
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fix_bad_mgi_symbols
- Given an expression matrix, wherein the rows are supposed to be MGI
symbols, find those symbols which are not official MGI symbols, then
check in the MGI synonm database for whether they match to a proper MGI
symbol. Where a symbol is found to be an aliases for a gene that is already
in the dataset, the combined reads are summed together. |
generate_bootstrap_plots()
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Generate bootstrap plots |
generate_bootstrap_plots_for_transcriptome()
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Generate bootstrap plots |
generate_celltype_data()
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Generate CellTypeData (CTD) file |
get_celltype_table()
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get_celltype_table |
get_summed_proportions()
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Get summed proportions |
load_rdata()
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load_rdata
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merge_ctd()
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Merge multiple CellTypeDataset references |
merge_two_expfiles()
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Merge two exp files |
merged_ewce()
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Multiple EWCE results from multiple studies |
plot_ctd()
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Plot CellTypeData metrics |
prep.dendro()
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prep.dendro |
sct_normalize()
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Normalize expression matrix |
standardise_ctd()
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Convert a CellTypeDataset into standardized format |