Package: singleCellHaystack 1.0.2

singleCellHaystack: A Universal Differential Expression Prediction Tool for Single-Cell and Spatial Genomics Data

One key exploratory analysis step in single-cell genomics data analysis is the prediction of features with different activity levels. For example, we want to predict differentially expressed genes (DEGs) in single-cell RNA-seq data, spatial DEGs in spatial transcriptomics data, or differentially accessible regions (DARs) in single-cell ATAC-seq data. 'singleCellHaystack' predicts differentially active features in single cell omics datasets without relying on the clustering of cells into arbitrary clusters. 'singleCellHaystack' uses Kullback-Leibler divergence to find features (e.g., genes, genomic regions, etc) that are active in subsets of cells that are non-randomly positioned inside an input space (such as 1D trajectories, 2D tissue sections, multi-dimensional embeddings, etc). For the theoretical background of 'singleCellHaystack' we refer to our original paper Vandenbon and Diez (Nature Communications, 2020) <doi:10.1038/s41467-020-17900-3> and our update Vandenbon and Diez (Scientific Reports, 2023) <doi:10.1038/s41598-023-38965-2>.

Authors:Alexis Vandenbon [aut, cre], Diego Diez [aut]

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singleCellHaystack/json (API)
NEWS

# Install 'singleCellHaystack' in R:
install.packages('singleCellHaystack', repos = c('https://alexisvdb.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/alexisvdb/singlecellhaystack/issues

Datasets:

On CRAN:

bioinformaticscite-seqpseudotimescatac-seqsingle-cellspatial-proteomicsspatial-transcriptomicstranscriptomics

18 exports 76 stars 3.77 score 33 dependencies 62 scripts 280 downloads

Last updated 8 months agofrom:5a8bd5c3ef. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 07 2024
R-4.5-winOKSep 07 2024
R-4.5-linuxOKSep 07 2024
R-4.4-winOKSep 07 2024
R-4.4-macOKSep 07 2024
R-4.3-winOKSep 07 2024
R-4.3-macOKSep 07 2024

Exports:haystackhaystack_2Dhaystack_continuous_highDhaystack_highDhclust_haystackhclust_haystack_highDhclust_haystack_rawkmeans_haystackkmeans_haystack_highDkmeans_haystack_rawplot_gene_haystackplot_gene_haystack_rawplot_gene_set_haystackplot_gene_set_haystack_rawplot_rand_fitread_haystackshow_result_haystackwrite_haystack

Dependencies:clicolorspacefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigplyrR6RColorBrewerRcppreshape2rlangscalesstringistringrtibbleutf8vctrsviridisLitewithr

Application on toy example

Alexis Vandenbon

Rendered froma01_toy_example.Rmdusingknitr::rmarkdownon Sep 07 2024.

Last update: 2022-10-30
Started: 2019-11-12

Readme and manuals

Help Manual

Help pageTopics
Single cell RNA-seq dataset.dat.expression
Single cell tSNE coordingates.dat.tsne
Default function given by function bandwidth.nrd in MASS. No changes were made to this function.default_bandwidth.nrd
Returns a row of a sparse matrix of class dgRMatrix. Function made by Ben Bolker and Ott Toomet (see https://stackoverflow.com/questions/47997184/)extract_row_dgRMatrix
Returns a row of a sparse matrix of class lgRMatrix. Function made by Ben Bolker and Ott Toomet (see https://stackoverflow.com/questions/47997184/)extract_row_lgRMatrix
Calculates the Kullback-Leibler divergence between distributions.get_D_KL
Calculates the Kullback-Leibler divergence between distributions for the high-dimensional continuous version of haystack.get_D_KL_continuous_highD
Calculates the Kullback-Leibler divergence between distributions for the high-dimensional version of haystack().get_D_KL_highD
Function to get the density of points with value TRUE in the (x,y) plotget_density
Calculate the pairwise Euclidean distances between the rows of 2 matrices.get_dist_two_sets
Calculate the Euclidean distance between x and y.get_euclidean_distance
A function to decide grid points in a higher-dimensional spaceget_grid_points
Estimates the significance of the observed Kullback-Leibler divergence by comparing to randomizations.get_log_p_D_KL
Estimates the significance of the observed Kullback-Leibler divergence by comparing to randomizations for the continuous version of haystack.get_log_p_D_KL_continuous
Function that decides most of the parameters that will be used during the "Haystack" analysis.get_parameters_haystack
Get reference distributionget_reference
The main Haystack functionhaystack haystack.data.frame haystack.matrix haystack.Seurat haystack.SingleCellExperiment
The main Haystack function, for 2-dimensional spaces.haystack_2D
The main Haystack function, for higher-dimensional spaces and continuous expression levels.haystack_continuous_highD
The main Haystack function, for higher-dimensional spaces.haystack_highD
Function for hierarchical clustering of genes according to their expression distribution in 2D or multi-dimensional spacehclust_haystack hclust_haystack.data.frame hclust_haystack.matrix
Function for hierarchical clustering of genes according to their distribution in a higher-dimensional space.hclust_haystack_highD
Function for hierarchical clustering of genes according to their distribution on a 2D plot.hclust_haystack_raw
Based on the MASS kde2d() function, but heavily simplified; it's just tcrossprod() now.kde2d_faster
Function for k-means clustering of genes according to their expression distribution in 2D or multi-dimensional spacekmeans_haystack kmeans_haystack.data.frame kmeans_haystack.matrix
Function for k-means clustering of genes according to their distribution in a higher-dimensional space.kmeans_haystack_highD
Function for k-means clustering of genes according to their distribution on a 2D plot.kmeans_haystack_raw
plot_compare_ranksplot_compare_ranks
Visualizing the detection/expression of a gene in a 2D plotplot_gene_haystack plot_gene_haystack.data.frame plot_gene_haystack.matrix plot_gene_haystack.Seurat plot_gene_haystack.SingleCellExperiment
Visualizing the detection/expression of a gene in a 2D plotplot_gene_haystack_raw
Visualizing the detection/expression of a set of genes in a 2D plotplot_gene_set_haystack plot_gene_set_haystack.data.frame plot_gene_set_haystack.matrix plot_gene_set_haystack.Seurat plot_gene_set_haystack.SingleCellExperiment
Visualizing the detection/expression of a set of genes in a 2D plotplot_gene_set_haystack_raw
plot_rand_fitplot_rand_fit plot_rand_fit.haystack
plot_rand_KLDplot_rand_KLD
Function to read haystack results from file.read_haystack
show_result_haystackshow_result_haystack show_result_haystack.haystack
Function to write haystack result data to file.write_haystack