Package index • Spectre

All functions

adjust.files(): adjust.files

check.files(): check.files

create.dt(): create.dt - convert a Seurat or SingleCellExperiment to a data.table

create.stats(): create.stats - perform statistical analysis and generate an output data.table

create.sumtable(): create.sumtable - create a data.table 'summarising' cellular data by sample and population/cluster.

demo.clustered: demo.clustered - Demo data.table with cells (rows) x markers (columns), with clusters, populations, and UMAP values added

do.add.cols(): do.add.cols

do.add.masks(): do.add.masks

do.add.percell(): do.add.percell

do.aggregate(): Aggregate data using data.table functions – summarises the mean, median, or sum expression of each marker on each cluster/population

do.align(): do.align - Function to align multiple batches of a dataset.

do.asinh(): Transform data using ArcSinh transformation

do.calculate.area(): do.calculate.area

do.clip(): do.clip - Clips data using a specified lower and upper value

do.combine.cols(): do.combine.cols - Combine the values of two columns into a single column

do.create.outlines(): do.create.outlines

do.extract(): do.extract

do.extract.cell.dat(): do.extract.cell.dat

do.filter(): do.filter - filtering data.table using multiple match values

do.filter.percell(): do.filter.percell

do.label.from.polygon(): do.label.from.polygon

do.list.summary(): Summarise the column names and row numbers for elements of a list

do.list.switch(): List switch or inversion

do.logicle(): Using logicle to transform data

do.merge.files(): do.merge.files - Function to merge a list of data.tables (one data.table per 'sample') into a single large data.table.

do.pull.data(): do.pull.data

do.reorder(): do.reorder - custom row re-ordering of a data.table

do.rescale(): do.rescale - Re-scale data in selected columns between two values, usually 0 and 1.

do.stats: Statistical analysis

do.subsample(): Subsample data

do.zscore(): do.zscore - Calculate z.score for a dataset

fast.colour.plot(): DEPRECATED fast colour plot

fast.multi.plot(): DEPRECATED fast multi plot

make.autograph(): make.autograph - Creates plots using ggplot2

make.colour.plot(): Make colour plot

make.multi.plot(): Make multiple plots for multiple columns and/or multiple sample/group/clusters

make.pheatmap(): make.pheatmap - Create a 'pretty' heatmap (pheatmap)

make.spatial.plot(): make.spatial.plot

make.volcano.plot(): Make an enhanced volcano plot

package.check(): package.check - a function to check the installation of all required packages.

package.install(): package.install - a function to install packages required for Spectre.

package.load(): package.load - a function to load (library) all required packages.

prep.cytonorm(): prep.cytonorm - Prepare reference data into a FlowSOM object

read.files(): Read CSV or FCS files into a list.

read.spatial.files(): Read TIFF files into R and and create spatial data object

run.align(): run.align - Run the alignment model on a target data.table

run.align(): run.cytonorm - Run the alignment model on a target data.table

run.fitsne(): Run FIt-SNE, Fourier Transform TSNE.

run.flowsom(): Run FlowSOM

run.harmony(): run.harmony - dun Harmony alignment on a data.table

run.knn.classifier(): run.knn.classifier - Run KNN classifier

run.pca(): Run the PCA algorithm (using stats::prcomp)

run.phenograph(): run.phenograph - Run phenograph clustering

run.rpca(): Run rPCA for batch correction

run.spatial.analysis(): run.spatial.analysis

run.tsne(): Run the tSNE algorithm (using Rtsne::Rtsne())

run.umap(): Run UMAP

spatial-class spatial: spatial object

train.align(): train.cytonorm - Prepare reference data into a FlowSOM object

train.knn.classifier(): train.knn.classifier - Train KNN classifier

write.files(): write.files - Write .csv or .fcs files

write.hdf5(): write.hdf5