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stemangiolastemangiola
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Merge pull request #71 from noriakis/update-documentation
Documentation revision
2 parents 32381c7 + 7effd27 commit 4c7cde6

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‎NAMESPACE

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@@ -38,64 +38,30 @@ S3method(slice_min,Seurat)
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S3method(slice_sample,Seurat)
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S3method(slice_tail,Seurat)
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S3method(summarise,Seurat)
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S3method(summarize,Seurat)
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S3method(tbl_format_header,tidySeurat)
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S3method(tidy,Seurat)
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S3method(unite,Seurat)
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S3method(unnest,tidyseurat_nested)
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export("%>%")
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export()
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export(add_count)
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export(arrange)
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export(as_tibble)
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export(bind_rows)
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export(count)
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export(distinct)
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export(extract)
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export(filter)
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export(full_join)
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export(get_abundance_sc_long)
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export(get_abundance_sc_wide)
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export(ggplot)
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export(glimpse)
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export(group_by)
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export(inner_join)
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export(join_features)
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export(join_transcripts)
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export(left_join)
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export(mutate)
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export(nest)
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export(pivot_longer)
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export(plot_ly)
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export(pull)
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export(rename)
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export(right_join)
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export(rowwise)
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export(sample_frac)
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export(sample_n)
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export(select)
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export(separate)
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export(slice)
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export(slice_head)
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export(slice_max)
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export(slice_min)
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export(slice_sample)
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export(slice_tail)
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export(summarise)
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export(tbl_format_header)
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export(tidy)
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export(unite)
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export(unnest)
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export(unnest_seurat)
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exportMethods(aggregate_cells)
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exportMethods(join_features)
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importFrom(Matrix,rowSums)
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importFrom(Seurat,Assays)
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importFrom(Seurat,GetAssayData)
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importFrom(Seurat,SplitObject)
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importFrom(Seurat,VariableFeatures)
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importFrom(SeuratObject,"DefaultAssay<-")
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importFrom(cli,cat_line)
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importFrom(SeuratObject,DefaultAssay)
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importFrom(dplyr,add_count)
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importFrom(dplyr,arrange)
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importFrom(dplyr,contains)
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importFrom(dplyr,count)
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importFrom(dplyr,distinct)
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importFrom(dplyr,distinct_at)
@@ -122,6 +88,7 @@ importFrom(dplyr,slice_min)
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importFrom(dplyr,slice_sample)
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importFrom(dplyr,slice_tail)
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importFrom(dplyr,summarise)
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importFrom(dplyr,summarize)
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importFrom(dplyr,vars)
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importFrom(ellipsis,check_dots_used)
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importFrom(fansi,strwrap_ctl)
@@ -152,15 +119,13 @@ importFrom(rlang,enquo)
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importFrom(rlang,enquos)
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importFrom(rlang,expr)
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importFrom(rlang,flatten_if)
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importFrom(rlang,is_empty)
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importFrom(rlang,is_spliced)
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importFrom(rlang,names2)
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importFrom(rlang,quo_name)
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importFrom(rlang,quo_squash)
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importFrom(stats,setNames)
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importFrom(stringr,regex)
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importFrom(stringr,str_detect)
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importFrom(stringr,str_replace)
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importFrom(tibble,as_tibble)
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importFrom(tibble,column_to_rownames)
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importFrom(tibble,enframe)
@@ -173,6 +138,7 @@ importFrom(tidyr,separate)
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importFrom(tidyr,spread)
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importFrom(tidyr,unite)
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importFrom(tidyr,unnest)
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importFrom(tidyselect,eval_select)
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importFrom(ttservice,aggregate_cells)
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importFrom(ttservice,bind_cols)
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importFrom(ttservice,bind_rows)

‎R/attach.R

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core <- c("dplyr", "tidyr", "ttservice", "ggplot2")
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core_unloaded <- function() {
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search <- paste0("package:", core)
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core[!search %in% search()]
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}
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# Attach the package from the same library it was loaded from before.
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# [source: https://github.com/tidy-biology/tidyverse/issues/171]
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same_library <- function(pkg) {
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loc <- if (pkg %in% loadedNamespaces())
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dirname(getNamespaceInfo(pkg, "path"))
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library(pkg, lib.loc=loc, character.only=TRUE, warn.conflicts=FALSE)
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}
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tidyverse_attach <- function() {
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to_load <- core_unloaded()
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suppressPackageStartupMessages(
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lapply(to_load, same_library))
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invisible(to_load)
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}

‎R/data.R

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#' Example data set 2
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#'
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#' Cell types of 80 PBMC single cells
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#'
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#' A dataset containing the barcodes and cell types of 80 PBMC single cells.
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#'
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#' @format A tibble containing 80 rows and 2 columns.
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#' Cells are a subsample of the Peripheral Blood Mononuclear Cells (PBMC)
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#' dataset of 2,700 single cell. Cell types were identified with SingleR.
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#' \describe{
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#' \item{cell}{cell identifier, barcode}
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#' \item{first.labels}{cell type}
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#' }
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#' @source \url{https://satijalab.org/seurat/v3.1/pbmc3k_tutorial.html}
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#' @usage data(cell_type_df)
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#' @return `tibble`
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"cell_type_df"
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#' Example data set 2
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#' Intercellular ligand-receptor interactions for
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#' 38 ligands from a single cell RNA-seq cluster.
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#'
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#' A dataset containing ligand-receptor interactions within a sample.
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#' There are 38 ligands from a single cell cluster versus 35 receptors
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#' in 6 other clusters.
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#'
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#' @format A `tibble` containing 100 rows and 9 columns.
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#' Cells are a subsample of the PBMC dataset of 2,700 single cells.
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#' Cell interactions were identified with `SingleCellSignalR`.
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#' \describe{
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#' \item{sample}{sample identifier}
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#' \item{ligand}{cluster and ligand identifier}
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#' \item{receptor}{cluster and receptor identifier}
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#' \item{ligand.name}{ligand name}
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#' \item{receptor.name}{receptor name}
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#' \item{origin}{cluster containing ligand}
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#' \item{destination}{cluster containing receptor}
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#' \item{interaction.type}{type of interation, paracrine or autocrine}
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#' \item{LRscore}{interaction score}
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#' }
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#' @source \url{https://satijalab.org/seurat/v3.1/pbmc3k_tutorial.html}
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#' @usage data(pbmc_small_nested_interactions)
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#' @return `tibble`
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"pbmc_small_nested_interactions"

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