Package index • blaseRtools

All functions

Ape-class Ape: An S4 class to hold genebank/APE file data.

Ape.DNA(): Get the DNASringSet Slot from an Ape Object

Ape.fasta(): Save an Ape Instance as a Fasta File

Ape.fimo(): Run FIMO on Selected Ape Object Features

Ape.granges(): Get the GRanges Slot from an Ape Object

Ape.save(): Save an Ape Instance as a Genebank Format File

Ape.setFeatures(): Set the FEATURES Slot of a GRanges Object

COMMENTS(): Get the Comments Slot from an Ape Object

FEATURES(): Get the Features Slot from an Ape Object

show(<Image_>) file_path() `file_path<-`() species() `species<-`() stage() `stage<-`() genetics() `genetics<-`() treatment() `treatment<-`() microscope() `microscope<-`() mag() `mag<-`() filter() `filter<-`() use() `use<-`() note() `note<-`(): An S4 Class for Holding Image Metadata

show(<ImageCatalog>) `[`(<ImageCatalog>,<ANY>,<ANY>,<ANY>) `[[`(<ImageCatalog>,<ANY>,<ANY>) `$`(<ImageCatalog>) ImageCatalog.as_tibble() ImageCatalog.write() ImageCatalog.add() ImageCatalog.delete(): An S4 Image Catalog

LOCUS(): Get the Locus Slot from an Ape Object

LearnGraph(): Run link[monocle3]{learn_graph} on a Seurat object

blaseRtools blaseRtools-package SeuratWrappers-package: blaseRtools: R Tools for Blaser Lab Data Analysis

Trace-class Trace: An S4 class to Hold Genome Track Data

Trace.data(): Get the Trace Data Slot from a Trace Object

Trace.gene_model(): Get the gene_model Slot from a Trace Object

Trace.links(): Get the Links Slot from a Trace Object

Trace.peaks(): Get the peaks Slot from a Trace Object

Trace.plot_range(): Get the plot_range Slot from a Trace Object

Trace.setData(): Set the Trace Data Slot of a GRanges Object

Trace.setLinks(): Set the Links Slot of a GRanges Object

Trace.setRange(): Set the Plot Range Slot of a GRanges Object

Trace.setpeaks(): Set the peaks Slot of a GRanges Object

add_cds_factor_columns(): Add predefined sample-level cell metadata to cell data sets while importing

aggregate(<Matrix>): Compute summary statistics of a Matrix

as.Seurat(<cell_data_set>): Convert single cell experiment to Seurat

as.cell_data_set(): Convert objects to Monocle3 cell_data_set objects

bb_aggregate(): Aggregate Single Cell Gene Expression

bb_align(): Align a CDS object according to a metadata variable

bb_annotate_npc(): Annotate a Plot using NPC Coordinates

bb_blind_images(): Make a Copy of Image Files and Rename With File Hashes in Blinded Folder

bb_buff_granges(): Clean Up Your GRanges Object

bb_cds_anno(): Annotate a CDS by Label Transfer

bb_cds_heatmap(): Make a Heatmap of Aggregated Gene Expressionf from a CDS

bb_cellchat(): Infer Cell-Cell Communication

bb_cellchat_heatmap(): Make a Complex Heatmap From a CellChat Object With Sensible Defaults

bb_cellmeta(): Get Cell Metadata

bb_cite_umap(): Plot a UMAP Showing Cite-Seq Antibody Binding

bb_cluster_representation(): Cluster Representation By Fisher Exact Test Per Cell

bb_cluster_representation2(): Cluster Representation By Regression Per Sample

bb_daseq(): Calculate Differential Abundance Using DAseq

bb_doubletfinder(): Use doubletfinder to model and mark doublets

bb_extract_msig(): Extract MSIGDB Gene Sets

bb_fix_file_path(): Convert windows filepath to linux-compatible.

bb_fragment_replacement(): Replace The Path to a Fragment File In a Signac Object

bb_gene_dotplot(): Make a dotplot of gene expression by cell population

bb_gene_modules(): A function to generate gene modules and add them to the Gene Metadata

bb_gene_pseudotime(): Plot expression of a gene or genes in pseudotime.

bb_gene_umap(): Make a Plot of Gene Expression in UMAP Form

bb_gene_violinplot(): Make a plot of gene expression in UMAP form

bb_genebubbles(): Create a Gene Bubble/Dot Plot

bb_goenrichment(): Go Term Enrichment

bb_goscatter(): Make a scatter plot of GO term associations

bb_gosummary(): A function to reduce go terms by semantic similarity

bb_import_seacr_peaks(): Import Peaks from SEACR

bb_load_tenx_h5(): Load a 10X Genomics H5 File and Return a CDS

bb_load_tenx_targz(): Load 10X Data Into CDS

bb_loupeR(): Create a Loupe File from a Cell Data Set

bb_makeTrace(): Construct a Trace object from a Signac Object or Granges object

bb_make_ape_genomic(): Make an Ape Genome Object

bb_make_ape_transcript(): Make an Ape Transcriptome Object

bb_merge_narrowpeaks(): A Function To Merge Replicate Narrow Peaks GRanges

bb_metafeature(): A Function to Generate Data For Making MetaPlots

bb_monocle_() bb_monocle_anno() bb_monocle_project(): Annotate Single cell Data Using Monocle3

bb_monocle_regression(): A function to perform regression on single cell data.

bb_monocle_regression_better(): An Improved Function to Perform Regression on Single Cell Data.

bb_parseape(): Parse a Genebank File and Construct an APE Object

bb_plot_genes_in_pseudotime(): Plots expression for one or more genes as a function of pseudotime

bb_plot_rowData_col(): A helper function to generate a data frame in the proper form for aggregate expression plotting with bb_gene_umap.

bb_plot_trace_axis(): Plot The X Axis From A Trace Object

bb_plot_trace_data(): Plot The Trace Data From A Trace Object

bb_plot_trace_links(): Plot The Link Data From A Trace Object

bb_plot_trace_model(): Plot The Gene Model From A Trace Object

bb_plot_trace_peaks(): Plot The peak Data From A Trace Object

bb_plotfootprint(): Plot motif footprinting results

bb_print_full_stats(): Print out a stats report

bb_promoter_overlap(): Calculate The Overlap Between Peaks and Promoters

bb_pseudobulk_mf(): Run Multifactor Pseudobulk Analysis using Deseq2

bb_pseudocells(): Generate a CDS from Bulk RNA-seq data

bb_pseudotime(): Learn Graph and Calculate Pseudotime

bb_qc(): A function to run qc tests on cds objects.

bb_read_bam(): Read Bam Files

bb_read_narrowpeak(): A Function to Read In Narrow Peaks Files

bb_rejoin(): Rejoin qc and doubletfinder data to a cds object

bb_remove_dupes(): Remove rows that have duplicates in a given column

bb_rowmeta(): Get Feature/Gene Metadata

bb_seurat_anno(): A function to generate automated cell labelings with Seurat

bb_split_atac(): Split Out Peaks Data

bb_split_citeseq(): Split Antibody Capture Data into Alt Experiment

bb_tbl_to_coldata(): A Function To Add Tibble Columns To Cell Metadata

bb_tbl_to_matrix(): Convert a wide-form tibble a matrix

bb_tbl_to_rowdata(): A Function To Add Tibble Columns To Feature Metadata

bb_triplecluster(): A function to generate clusters from scRNA-seq data

bb_unblind_images(): Rejoin Blinded Scores to Original File Names

bb_var_umap(): A function to generate a UMAP with colors mapped to colData variables

dMcast(): Casts or pivots a long data frame into a wide sparse matrix

data_median_se(): Generate median +/- se stat object for jitter ggplot

data_summary_mean_sd(): Generate mean +/- sd stat object for jitter ggplot

data_summary_mean_se(): Generate mean +/- se stat object for jitter ggplot

data_summary_median_iqr(): Generate median +/- iqr stat object for jitter ggplot

data_summary_median_mad(): Generate median +/- mad stat object for jitter ggplot

filter_cds(): Filter a CDS

geom_split_violin(): geom_split_violin

granges_to_features(): Format a GRanges Object as a Character Vector For Inclusion in Genebank File

`%notin%`: Operators

merge.Matrix() join.Matrix(): Merges two Matrices or matrix-like objects

normalize_batch(): Noramalize a Data Table by Group and Batch

rBind.fill(): Combine matrixes by row, fill in missing columns

se(): Calculate standard error of the mean

show(<Ape>): Show an Ape Object

show(<Trace>): Show a Trace Object