Single Cell Analysis and Differential Expression
Quick utility to check if given character vector is colors Thanks to S...
armaCor - matrix column correlations. Allows faster matrix correlation...
Perform basic 'pagoda2' processing, i.e. adjust variance, calculate pc...
Generate a 'pagoda2' web application from a 'Pagoda2' object
Rescale the weights in an edge matrix to match a given perplexity. Fro...
Returns a list vector with the number of cells that are present in mor...
Get the number of cells in each selection group
Translate cell cluster dendrogram to an array, one row per node with 1...
Collapse aspect patterns into clusters
Compare two different clusterings provided as factors by plotting a no...
Perform differential expression on a p2 object given a set of web sele...
Perform differential expression on a p2 object given a set of web sele...
Correct unloading of the library
Perform extended 'Pagoda2' processing. Generate organism specific GO e...
Returns a factor of cell membership from a p2 selection object the fac...
Converts a list of factors into 'pagoda2' metadata optionally filterin...
Converts a names factor to a p2 selection object if colors are provide...
Filter cells based on gene/molecule dependency
Given a cell clustering (partitioning) and a set of user provided sele...
Get a control geneset for cell scoring using the method described in P...
Generate differential expression genesets for the web app given a cell...
Returns all the cells that are in the designated selections. Given a p...
Assign names to the clusters, given a clustering vector and a set of s...
Retrieves the colors of each selection from a p2 selection object as a...
Get a mapping form internal to external names for the specified select...
Converts the output of hierarchical differential expression aspects in...
Generate a Rook Server app from a 'Pagoda2' object. This generates a '...
Scale the designated values between the range of 0 and 1
Return the mode of a vector
Get a vector of the names of an object named by the names themselves. ...
Generate a GO environment for human for overdispersion analysis for th...
Generates zebrafish (Danio rerio) GO annotation for the web object
Generate a GO environment for the organism specified
Generates GO annotation for the web object from the GO environment use...
Generates GO annotation for the web object for any species
Generate a GO environment for human for overdispersion analysis for th...
Generates human GO annotation for the web object
Generate a GO environment for mouse for overdispersion analysis for th...
Generates mouse (Mus musculus) GO annotation for the web object
Create 'PAGODA1' web application from a 'Pagoda2' object 'PAGODA1' fou...
Generate a list metadata structure that can be passed to a 'pagoda2' w...
Generate a 'pagoda2' web object from a 'Pagoda2' object using hierarch...
p2ViewPagodaApp R6 class
Collapse aspects driven by the same combinations of genes. (Aspects ar...
Collapse aspects driven by similar patterns (i.e. separate the same se...
Pagoda2 R6 class
pagoda2WebApp class to create 'pagoda2' web applications via a Rook se...
pagoda2WebApp_arrayToJSON
pagoda2WebApp_availableAspectsJSON
pagoda2WebApp_call
pagoda2WebApp_cellmetadataJSON
pagoda2WebApp_cellOrderJSON
pagoda2WebApp_geneInformationJSON
Generate a dendrogram of groups
pagoda2WebApp_generateEmbeddingStructure
pagoda2WebApp_generateGeneKnnJSON
pagoda2WebApp_getCompressedEmbedding
pagoda2WebApp_packCompressFloat64Array
pagoda2WebApp_packCompressInt32Array
pagoda2WebApp_readStaticFile
pagoda2WebApp_reducedDendrogramJSON
pagoda2WebApp_serializeToStaticFast
pagoda2WebApp_serverLog
pagoda2WebApp_sparseMatList
Parallel, optionally verbose lapply. See ?parallel::mclapply for more ...
Calculate correlation distance between PC magnitudes given a number of...
Plot multiclassified cells per selection as a percent barplot
Plot the embedding of a 'Pagoda2' object with the given values
Get a dataframe and plot summarising overlaps between selection of a p...
Project a distance matrix into a lower-dimensional space. (from elbamo...
Quick loading of 10X CellRanger count matrices
This function reads a matrix generated by the 10x processing pipeline ...
Read a pagoda2 cell selection file and return it as a factor while rem...
Reads a 'pagoda2' web app exported cell selection file exported as a l...
Remove cells that are present in more than one selection from all the ...
Score cells by getting mean expression of genes in signatures
Score cells after standardising the expression of each gene removing o...
Puram, Bernstein (Cell, 2018) Score cells as described in Puram, Berns...
Calculate the default number of batches for a given number of vertices...
Directly open the 'pagoda2' web application and view the 'p2web' appli...
Set names equal to values, a stats::setNames wrapper function
Subset a gene signature to the genes in the given matrix with optional...
View pathway or gene-weighted PCA 'Pagoda2' version of the function pa...
Validates a pagoda2 selection object
Internal function to visualize aspects of transcriptional heterogeneit...
Generate a 'pagoda2' web object
Sets the ncol(mat)*trim top outliers in each row to the next lowest va...
Writes a list of genes as a gene selection that can be loaded in the w...
Writes a pagoda2 selection object as a p2 selection file that be be lo...
Analyzing and interactively exploring large-scale single-cell RNA-seq datasets. 'pagoda2' primarily performs normalization and differential gene expression analysis, with an interactive application for exploring single-cell RNA-seq datasets. It performs basic tasks such as cell size normalization, gene variance normalization, and can be used to identify subpopulations and run differential expression within individual samples. 'pagoda2' was written to rapidly process modern large-scale scRNAseq datasets of approximately 1e6 cells. The companion web application allows users to explore which gene expression patterns form the different subpopulations within your data. The package also serves as the primary method for preprocessing data for conos, <https://github.com/kharchenkolab/conos>. This package interacts with data available through the 'p2data' package, which is available in a 'drat' repository. To access this data package, see the instructions at <https://github.com/kharchenkolab/pagoda2>. The size of the 'p2data' package is approximately 6 MB.
Useful links