Function reference • redeemR

All functions
`ATAC_Wrapper()`	Wrap Seurat ATAC clustering
`AddDatatoplot_clustering(<redeemR>)`	AddDatatoplot_clustering This prepare the clonal clustering data to plot
`AddDatatoplot_clustering()`	AddDatatoplot_clustering This prepare the clonal clustering data to plot
`AddDist(<redeemR>)`	AddDist This add Jaccard, Dice, Jaccard3W distance and stored in DistObjects
`AddDist()`	AddDist This add Jaccard, Dice, Jaccard3W distance and stored in DistObjects
`AddHemSignature()`	Function to add hematopoietic signatures from Griffin_Signatures
`AddTree(<redeemR>)`	Add_Tree Optional, if a phylogentic tree object phylo is already available, can be directly added to the redeemR class in slot TREE
`AddTree()`	Add_Tree Optional, if a phylogentic tree object phylo is already available, can be directly added to the redeemR
`Add_AssignVariant(<redeemR>)`	a function to assign variants to edges based on maximum likihood
`Add_AssignVariant()`	Add_AssignVariant a function to assign variants to edges based on maximum likihood
`Add_DepthMatrix(<redeemR>)`	Add_DepthMatrix Optional, add a matrix with same dimension with the Cts.Mtx and Cts.Mtx.bi, which display the depths
`Add_DepthMatrix()`	Add_DepthMatrix Optional, add a matrix with same dimension with the Cts.Mtx and Cts.Mtx.bi, which display the depths
`Add_tree_cut(<redeemR>)`	a function to cut tree using assigned variant as branch-length on edge
`Add_tree_cut()`	Add_tree_cut a function to cut tree using assigned variant as branch-length on edge
`BinaryDist()`	Compute distances for binary distances
`CV()`	Internal CV
`Clone_FinderMarker()`	Define a function to perform Find marker for top vs bottom clones This function was developed based on DN4T2.basics.ipynb
`ComputeRejectRate()`	Function to compute the reject rate(The filtering rate in concensus variant calling)
`CountVperCell()`	Internal function in plot_variant
`Create_mitoTracing()`	Create_mitoTracing
`Create_redeemR()`	Create_redeemR
`DE.gettripple()`	DE.gettripple
`Datatoplots-class` `Datatoplots`	An intermediate S4 class Datatoplots
`DepthSummary()`	Function to summarize the depth (Total that passed Q30)
`DistObjects-class` `DistObjects`	An intermediate S4 class Datatoplots
`DoDE()`	DoDE
`FromDist2Graph()`	FromDist2Graph From distance object or matrix to graph, default is to return igraph object This function was developed based on
`GEM_Wrapper()`	Wrap Seurat RNA clustering
`GTSummary()`	Function to generate GTS summary
`Get_Clonal_Variants()`	Get_Clonal_Variants
`LineageBiasPlot()`	plot_npSummary to plot the lineage composition
`MakeAllNodes()`	Define a function make the Allnodes(Node\|Parent\|Freq\|CladeSize), where Freq is the number of variants assigned to the node(as ending point) from redeemR object,
`MakeDF4Regress()`	MakeDF4Regress Define a function to make two dataframe for regression analysis This function was developed based on HSC_multiome_Het_2.ipynb
`MakeNN()`	Define a function to make nn list, which can be further used to make adjacency matrix This scan row by row, looking for k.param nearest neighbours
`Make_AnnTable()`	Make_AnnTable, Make a big dataframe, each row is a cell, each column includes info such as clonal UMAP, Clonal ID, ATAC/RNA/WNN UMAP, PCA, gene expression of chosen gene, etc. Require a redeemR object and a multiome wrapper that better matches the cells in the redeemR
`Make_Cells4Nodes()`	Define a function to make a list, each contains the cell names for a node
`Make_matrix(<redeemR>)`	Make_matrix This will make the matixies of Cell VS mitochondrial variants and return redeemR Results stored in Cts.Mtx and Cts.Mtx.bi
`Make_matrix()`	Make_matrix This will make the matixies of Cell VS mitochondrial variants and return redeemR Results stored in Cts.Mtx and Cts.Mtx.bi
`Make_tree(<redeemR>)`	Make_tree This will generate a basic phylogenetic tree
`Make_tree()`	Make_tree This will generate a basic phylogenetic tree
`MergeMtx()`	Function to Merge sparse Matrix
`Motifenrich.binom()`	Motifenrich.binom In house function to compute enrichment from Fimo This function was developed based on HSC_multiome_Het.ipynb and HSC_multiome_Het_2.ipynb
`Multi_Wrapper()`	Wrap Seurat Multiomics clustering
`MutationProfile.bulk()`	Function to plot bulk level mutation signatures
`NN2M()`	Define a function convert nn list to adjacency matrix that can be further used for igraph
`ProgenyMapping()`	Define a function to perform single-cell based hard porogeny assignment This function was developed based on DN4T2.basics.ipynb
`ProgenyMapping_np()`	ProgenyMapping_np Define a function to compute network propagation based probability FromDist2Graph is needed to convert fistance matrix into MNN graph
`Reclustering()`	Function to reclustering a seurat object
`Reclustering_hm()`	Function to reclustering_hm a seurat object with Harmony
`Run_Lin_regression()`	Run_Lin_regression
`Run_Lin_regression_poi()`	Run_Lin_regression_poi Firstly used in HSC_multiome_Het_2.ipynb This function was developed based on
`Runplot_scale_2()`	plot_npSummary to assess the outputlevel vs lineage bias, normalize by assigned
`Runplot_scale_3()`	plot_npSummary to assess the outputlevel vs lineage bias, normalize by HSC original clone size
`SeuratLSIClustering(<redeemR>)`	SeuratLSIClustering This will use the mito variants for Seurat clustering (LSI based)
`SeuratLSIClustering()`	SeuratLSIClustering This will use the mito variants for Seurat clustering (LSI based)
`Show_Consensus()`	Function to plot consensus mtDNA mutation benchmark
`Subset_redeemR()`	Subset_redeemR Subset a redeemR object by selecting a subset of cells, return a new redeemR object with only 4 slots: para; CellMeta; Cts.Mtx.bi; UniqueV, can be used for downstreme compute distance, clonal clustering, make tree, etc
`TREE-class` `TREE`	An intermediate S4 class Tree that store tree info
`Tomerge_v2()`	Tomerge_v2
`Translate_RNA2ATAC()`	Function to translate the RNA barcode into ATAC barcode and add a column
`Translate_simple_ATAC2RNA()`	Translate_simple_ATAC2RNA
`Translate_simple_RNA2ATAC()`	Translate_simple_RNA2ATAC
`Vfilter_v3()`	Function to filter variants, deprecated
`Vfilter_v4()`	Function to filter variants, v4
`add_derived_profile_info()`	This is a convinience function, internal borrowed from https://github.com/NickWilliamsSanger/treemut/blob/main/R/treemut.R#L68
`df2ProfileMtx()`	This is a convinience function, internal
`get_ancestral_nodes()`	This is a convinience function, internal borrowed from https://github.com/NickWilliamsSanger/treemut/blob/main/R/treemut.R#L68
`plot_depth()`	Function to plot the mito depth summary
`plot_npSummary()`	plot_npSummary to assess the outputlevel
`plot_variant()`	Function to plot variant metrics
`quick_w_cosine()`	Compute weighted cosine distance
`quick_w_jaccard()`	Compute weighted jaccard distance
`reconstruct_genotype_summary()`	This is a function borrowed from https://github.com/NickWilliamsSanger/treemut/blob/main/R/treemut.R#L68 Input phylo object, return a "profile matrix"--Edge(or denoted as the ending node) vs cell. a 0, 1 character string that indicate what cells in a given node
`redeemR-class` `redeemR`	Major redeem class that store clonal-resolved multi-omics
`redeemR.read()`	Function to read in mitoV outputs
`show(<redeemR>)`	show This will show the basics of redeemR class
`split_profile()`	This is a convinience function, internal borrowed from https://github.com/NickWilliamsSanger/treemut/blob/main/R/treemut.R#L68
`str2vector()`	This is a convinience function, internal

Reference

All functions