Function reference • scalop

All functions
`GeneInfo()`	Get Genomic Information
`MGH136`	Glioblastoma patient MGH136
`Markers_Normal`	Marker gene sets of Normal Cell Types and Pan-Cancer Programs
`NormalBrainSignatures2`	98 Signatures for Normal Brain Cell Types
`NormalBrainSignatures3`	178 Signatures for Normal Brain Cell Types
`NormalSignatures`	205 Signatures for Normal Cell Types
`Sapply()`	sapply wrapper
`Unlist()`	Unlist, keeping original list or element names
`add_to_dataframe()`	Join a dataframe and a named vector
`aggr_gene_expr()`	log-Average expression of genes across all cells
`alias2ensembl()`	FUNCTION_TITLE
`alias2entrez()`	FUNCTION_TITLE
`alias2refseq()`	FUNCTION_TITLE
`alias2symbol()`	FUNCTION_TITLE
`alias2ucsc()`	FUNCTION_TITLE
`allowedExons()`	FUNCTION_TITLE
`annomap()`	One-bar annotation ggplot
`as_bulk()`	Convert sc-matrix to simulated bulk
`as_bulk_samples()`	Convert sc-matrix to simulated bulk samples matrix
`as_four_state_gbm()`	Convert 6-state to 4-state GBM scores
`assign_bulk_states()`	Assign Samples to States by High- and Low -frequency of their Cells in each State
`baseScores()`	Basic Scoring of Matrix by Gene sigs
`bin()`	Generate Equally-Sized Bins
`binmatch()`	Control Signatures From Expression Bins
`bootstrap_summary()`	Summary Statistics for Bootstrapped State Fractions
`bootstrapped_state_fractions()`	Bootstrapped State Fractions
`cluster.methods`	agglomeration method in hierarchical clustering agglomeration method in hierarchical clustering when grouping members into a tree structure.
`col_subset()`	Keep columns whose names match a pattern
`colcenter()`	Center a matrix column-wise
`coldetected()`	Number of non-zero values per column
`combine_group2_dea()`	Aggregate `scalop::dea` output for one group against many in turn
`comply()`	Apply a Function to All Pairs of Elements in 'x' or Between 'x' and 'y'
`cor.methods`	Correlation method method for computing correlation coefficients
`cpm()`	Convert Counts to Counts-Per-Million (CPM)
`dea()`	Differential Expression Analysis
`dims()`	<dim> for many matrices
`discrete_colours`	The 297 discrete colours available across different RColorBrewer palettes.
`dist.methods`	distance metric method for computing distances from a matrix object
`doubletCells()`	Identify potential doublet cells
`enricher()`	Functional enrichments
`=`()	ensembl2symbol
`entrez2alias()`	FUNCTION_TITLE
`entrez2ensembl()`	FUNCTION_TITLE
`entrez2refseq()`	FUNCTION_TITLE
`entrez2symbol()`	FUNCTION_TITLE
`entrez2ucsc()`	FUNCTION_TITLE
`expr_housekeeping()`	Expression level of Housekeeping Genes
`filter_signatures()`	Filter Out Lowly-Correlated Genes from Signature(s)
`filter_sigs()`	Filter genes in sigs according to reference
`fitBimodal()`	Fit a Bimodal Gaussian Distribution
`flip()`	Flip the (nested) elements of a character vector (or list) with its names
`foldchange()`	fold changes
`frac_mito()`	Fraction of a Cell's Expression Level Coming From Mitochondrial Genes
`futurama`	futurama, 12 Discrete Colours
`geneLength()`	FUNCTION_TITLE
`genericModel()`	FUNCTION_TITLE
`getGRCh()`	Get hg19 or hg38 information from biomaRt
`get_ensembl()`	FUNCTION_TITLE
`get_entrez()`	FUNCTION_TITLE
`get_genes()`	FUNCTION_TITLE
`get_refseq()`	FUNCTION_TITLE
`get_signatures()`	FUNCTION_TITLE
`get_snn_graph_clusters()`	FUNCTION_TITLE
`get_symbols()`	FUNCTION_TITLE
`get_ucsc()`	FUNCTION_TITLE
`ggDensity()`	FUNCTION_TITLE
`ggmap()`	gmap wrapper
`ggoutliers()`	Plot model and Outliers
`ggpubr`	ggpubr, 3 Discrete Colours
`ggvolcano()`	Volcano plot
`gmap()`	Plot A Heatmap with ggplot2
`graster()`	Plot A Heatmap with ggplot2
`grombine()`	Combine ggplot grobs or plots
`grouped_reorder()`	Grouped Reorder and Ungroup
`grouped_rowcenter()`	Center matrix rows by subsets of columns
`hca()` `hca_cor()` `hca_dist()` `hca_tree()` `hca_order()` `hca_groups()` `hca_reorder()`	Hierarchical clustering analysis
`headl()`	Left-hand head a matrix or dataframe
`headr()`	Right-hand head a matrix or dataframe
`hierarchy()`	Cell state hierarchy coordinates
`hms_span()`	Subtract POSIXt Class Objects in HH:MM:SS Format
`is_accnum()`	FUNCTION_TITLE
`is_alias()`	FUNCTION_TITLE
`is_annotation()`	FUNCTION_TITLE
`is_ensembl()`	FUNCTION_TITLE
`is_entrez()`	FUNCTION_TITLE
`is_refseq()`	FUNCTION_TITLE
`is_symbol()`	FUNCTION_TITLE
`is_ucsc()`	FUNCTION_TITLE
`jacFilt()`	Filter List By Jaccard
`Jaccard()`	Compute Jaccard Similarities between Pairs of Character Vectors
`jacmap()`	Convert a list to a jaccard matrix and plot with `scalop::gmap`
`ldcast()`	Turn a list into a dataframe
`logRowMeans()`	Row Means of Log2 data
`logcpm()`	Convert CPM to logCPM
`map_alias()`	FUNCTION_TITLE
`map_ensembl()`	FUNCTION_TITLE
`map_entrez()`	FUNCTION_TITLE
`map_genes()`	FUNCTION_TITLE
`map_refseq()`	FUNCTION_TITLE
`map_symbol()`	FUNCTION_TITLE
`markerScores()`	Score a Matrix with Marker Gene Sets Of Normal Cell Types
`mat01()`	Character List to Binary (membership) Matrix
`maxcol_strict()`	Strict Column Assign
`metaprograms()`	Compute Metaprograms
`msigdb()`	FUNCTION_TITLE
`nSigGenes()`	FUNCTION_TITLE
`ncols()`	<ncol> for many matrices
`nrows()`	<nrow> for many matrices
`ntop()`	Select top n elements
`ohmySNNclusters()`	SNN Graph-Based Clustering
`ohmyqc()`	Quality control statistics for single cell RNA seq data
`ohmytsne()`	A plot-friendly output for the Barnes-Hut implementation of t-SNE.
`outliers()`	FUNCTION_TITLE
`Overlap()`	FUNCTION_TITLE
`pairup()`	List combinations
`pal19`	pal19, 19 Pretty Discrete Colours
`pal28`	pal28, 28 Pretty Discrete Colours
`palG34R`	palG34R, a palette of reds and blues for cases within two groups
`pca()`	Principal Component Analysis
`plot_hierarchy()`	Plot State Hierarchy (Quadrant plot)
`programs()`	Find cell clusters and retrieve significant expresion programs
`range_rowmeans()`	Range of the rowMeans of a matrix
`refseq2alias()`	FUNCTION_TITLE
`refseq2ensembl()`	FUNCTION_TITLE
`refseq2entrez()`	FUNCTION_TITLE
`refseq2symbol()`	FUNCTION_TITLE
`refseq2ucsc()`	FUNCTION_TITLE
`row_subset()`	Keep rows whose names match a pattern
`rowcenter()`	Center a matrix row-wise
`rowdetected()`	Number of non-zero values per row
`sample_strict()`	Assign Rows and Sample
`scdata`	scRNA-seq data from a patient with Glioblastoma
`score()`	Score matrix columns for groups of rows
`setColNames()`	Set the colnames in an object
`setRowNames()`	Set the rownames in an object
`sigScores()`	Score a Matrix by Gene sigs (Signatures)
`simpsons`	simpsons, 16 Discrete Colours
`state_fractions()`	State Fractions (by group)
`state_high_genes()`	Genes Associated with High Frequency of a Cellular State
`subsplit()`	Split a vector, list, matrix or dataframe into into a list of matrices or nested list according to substring matches.
`substri()`	Extract substrings between delimiters by position
`symbol2alias()`	FUNCTION_TITLE
`symbol2ensembl()`	FUNCTION_TITLE
`symbol2entrez()`	FUNCTION_TITLE
`symbol2refseq()`	FUNCTION_TITLE
`symbol2ucsc()`	FUNCTION_TITLE
`taill()`	Left-hand tail a matrix or dataframe
`tailr()`	Right-hand tail a matrix or dataframe
`theme_scalop()`	FUNCTION_TITLE
`totalExons()`	FUNCTION_TITLE
`tpm()`	Convert logTPM to TPM
`ucsc2alias()`	FUNCTION_TITLE
`ucsc2ensembl()`	FUNCTION_TITLE
`ucsc2entrez()`	FUNCTION_TITLE
`ucsc2refseq()`	FUNCTION_TITLE
`ucsc2symbol()`	FUNCTION_TITLE
`unique_sample_names()`	Get unique sample names
`unlogcpm()`	Convert logCPM to CPM
`logtpm()` `unlogtpm()`	Convert TPM to logTPM
`vannomap()`	One-bar annotation ggplot
`which_annotation()`	FUNCTION_TITLE
`wilcoxtest()`	wilcoxon-tests
`x2y()`	FUNCTION_TITLE

Reference

All functions