,
Andrew Thurman [aut],
Michael Chimenti [ctb],
Alejandro Pezzulo [ctb]| Title: | Differential Gene Expression Analysis for Multi-subject scRNA-seq |
|---|---|
| Description: | For single cell RNA-seq data collected from more than one subject (e.g. biological sample or technical replicates), this package contains tools to summarize single cell gene expression profiles at the level of subject. A SingleCellExperiment object is taken as input and converted to a list of SummarizedExperiment objects, where each list element corresponds to an assigned cell type. The SummarizedExperiment objects contain aggregate gene-by-subject count matrices and inter-subject column metadata for individual subjects that can be processed using downstream bulk RNA-seq tools. |
| Authors: | Jason Ratcliff [aut, cre] ,
Andrew Thurman [aut],
Michael Chimenti [ctb],
Alejandro Pezzulo [ctb] |
| Maintainer: | Jason Ratcliff <[email protected]> |
| License: | GPL-3 |
| Version: | 1.15.0 |
| Built: | 2024-07-05 05:03:30 UTC |
| Source: | https://github.com/bioc/aggregateBioVar |
Given an input gene-by-cell count matrix from a SingleCellExperiment object, sum within-subject gene counts into an aggregate gene-by-subject count matrix. Column metadata accessed by colData are collated by subjectMetaData to remove variables with inter-cell intrasubject variation, effectively retaining between-subject variation. The summary operations are performed across all cell types and within each cell type. A list of SummarizedExperiment objects is returned each with aggregate gene-by-subject count matrix and inter-subject metadata.
aggregateBioVar(scExp, subjectVar, cellVar)aggregateBioVar(scExp, subjectVar, cellVar)
scExp |
SingleCellExperiment object containing (at minimum) gene counts and column metadata describing sample identifiers and cell types. |
subjectVar |
Metadata column name assigning biological sample identity to aggregate within-subject feature counts. |
cellVar |
Metadata column name assigning cell type. Used for aggregating gene-by-subject count matrices by cell type. |
List of SummarizedExperiment objects with gene-by-subject count matrices and variable inter-subject column metadata across and within cell types.
## Aggregate gene-by-subject count matrix and inter-subject metadata aggregateBioVar( scExp=small_airway, subjectVar="orig.ident", cellVar="celltype" )## Aggregate gene-by-subject count matrix and inter-subject metadata aggregateBioVar( scExp=small_airway, subjectVar="orig.ident", cellVar="celltype" )
Given a vector of unique cell types, calculate a gene-by-subject matrix and inter-subject metadata for a differential expression design matrix.
countsByCell(scExp, subjectVar, cellVar)countsByCell(scExp, subjectVar, cellVar)
scExp |
SingleCellExperiment object containing (at minimum) gene counts and column metadata describing sample identifiers and cell types. |
subjectVar |
Metadata column name assigning biological sample identity to aggregate within-subject feature counts. |
cellVar |
Metadata column name assigning cell type. Used for aggregating gene-by-subject count matrices by cell type. |
List of gene-by-subject and design matrices for each cell type.
summarizedCounts for aggregate counts and metadata
SummarizedExperiment object.
## Return list of `SummarizedExperiments` with gene-by-subject count matrices ## and subject metadata for each unique `SingleCellExperiment` cell type. countsByCell( scExp=small_airway, subjectVar="orig.ident", cellVar="celltype" )## Return list of `SummarizedExperiments` with gene-by-subject count matrices ## and subject metadata for each unique `SingleCellExperiment` cell type. countsByCell( scExp=small_airway, subjectVar="orig.ident", cellVar="celltype" )
Convert gene-by-cell count matrix to gene-by-subject count matrix. Row sums are calculated for each feature (i.e. gene) across cells by subject.
countsBySubject(scExp, subjectVar)countsBySubject(scExp, subjectVar)
scExp |
SingleCellExperiment object containing (at minimum) gene counts and column metadata describing sample identifiers and cell types. |
subjectVar |
Metadata column name assigning biological sample identity to aggregate within-subject feature counts. |
S4 DataFrame of gene-by-subject count sums.
scSubjects for subjects values.
## Return cell count matrix aggregated by subject. countsBySubject(scExp=small_airway, subjectVar="orig.ident")## Return cell count matrix aggregated by subject. countsBySubject(scExp=small_airway, subjectVar="orig.ident")
Extract unique values from SingleCellExperiment column (i.e. cell) metadata. Used to determine subject and cell type values.
scSubjects(scExp, ...)scSubjects(scExp, ...)
scExp |
SingleCellExperiment object containing (at minimum) gene counts and column metadata describing sample identifiers and cell types. |
... |
Named metadata variables for subjects and cell types. |
List of character vectors with unique values from SingleCellExperiment column metadata variables.
## Examples of metadata column variable names. names(SummarizedExperiment::colData(small_airway)) ## Return list of subject and cell type values from experiment metadata. scSubjects(scExp=small_airway, subjects="orig.ident", cellTypes="celltype")## Examples of metadata column variable names. names(SummarizedExperiment::colData(small_airway)) ## Return list of subject and cell type values from experiment metadata. scSubjects(scExp=small_airway, subjects="orig.ident", cellTypes="celltype")
SingleCellExperiment objectSmall airway epithelium single-cell RNA sequencing data subset combined from
7 porcine individuals. Genotypes represent wildtype (Genotype WT; n=3)
and CFTR-knockout subjects (Genotype CFTRKO; n=4) expressing a
cystic fibrosis phenotype.
To access cell counts and column metadata:
counts: SummarizedExperiment::assay(small_airway, "counts")
metadata: SummarizedExperiment::colData(small_airway)
Cell types include:
Secretory cell
Endothelial cell
Immune cell
small_airwaysmall_airway
A SingleCellExperiment object with feature counts of 1311 genes (rows) from 2687 individual cells (columns). Features were subset by gene ontology annotation "ion transport" with included child terms ("anion transport", "cation transport", etc.). Includes a count matrix accessed by assay and column metadata accessed by colData. Metadata variables are defined as:
Biological sample identifier (i.e. subject)
Number of UMIs (i.e. depth/size factor)
Features with non-zero counts (i.e. identified features)
Sample Genotype ('CF' == cystic fibrosis)
WT = non-CF pig
CFTRKO = CFTR knockout
Airway region of sample
Cell type labels
Identify single cell experiment metadata variables that are identical within subject (e.g. genotype, treatment, cell line, sample preparation). Effectively excludes metadata variables containing between cell variation. Used as the design matrix for differential expression analysis.
subjectMetaData(scExp, subjectVar)subjectMetaData(scExp, subjectVar)
scExp |
SingleCellExperiment object containing (at minimum) gene counts and column metadata describing sample identifiers and cell types. |
subjectVar |
Metadata column name assigning biological sample identity to aggregate within-subject feature counts. |
Tibble data frame of metadata variables without intrasubject variation from single cell experiment metadata. Rows correspond to aggregated cells (i.e. subject / biological replicate) and columns to metadata attribute variables (e.g. genotype, treatment, cell line).
## Return experiment metadata sans intrasubject variation. subjectMetaData(scExp=small_airway, subjectVar="orig.ident")## Return experiment metadata sans intrasubject variation. subjectMetaData(scExp=small_airway, subjectVar="orig.ident")
Given an input sparse count matrix and corresponding column metadata, aggregate gene counts by subject level. Metadata variables with only inter-subject variation are retained; any variables with cell-level variation within a subject are dropped (e.g. feature / RNA count by cell).
summarizedCounts(scExp, subjectVar)summarizedCounts(scExp, subjectVar)
scExp |
SingleCellExperiment object containing (at minimum) gene counts and column metadata describing sample identifiers and cell types. |
subjectVar |
Metadata column name assigning biological sample identity to aggregate within-subject feature counts. |
SummarizedExperiment object with feature counts aggregated by subject and summarized inter-subject metadata.
## Construct SummarizedExperiment object with gene-by-subject count matrix ## and column metadata summarized to exclude intrasubject variation. ## See `SummarizedExperiment` accessor functions `assay()` and `colData()` ## to access the count matrix and column metadata for downstream analyses. summarizedCounts(scExp=small_airway, subjectVar="orig.ident")## Construct SummarizedExperiment object with gene-by-subject count matrix ## and column metadata summarized to exclude intrasubject variation. ## See `SummarizedExperiment` accessor functions `assay()` and `colData()` ## to access the count matrix and column metadata for downstream analyses. summarizedCounts(scExp=small_airway, subjectVar="orig.ident")