| Title: | Single Cell Transcriptome Data and Analysis of Mouse mTEC cells |
|---|---|
| Description: | This data package contains the code used to analyse the single-cell RNA-seq and the bulk ATAC-seq data from the manuscript titled: Single-cell transcriptome analysis reveals coordinated ectopic-gene expression patterns in medullary thymic epithelial cells. This paper was published in Nature Immunology 16,933-941(2015). The data objects provided in this package has been pre-processed: the raw data files can be downloaded from ArrayExpress under the accession identifiers E-MTAB-3346 and E-MTAB-3624. The vignette of this data package provides a documented and reproducible workflow that includes the code that was used to generate each statistic and figure from the manuscript. |
| Authors: | Alejandro Reyes |
| Maintainer: | Alejandro Reyes <[email protected]> |
| License: | LGPL |
| Version: | 1.40.0 |
| Built: | 2026-10-10 12:04:58 UTC |
| Source: | https://git.bioconductor.org/packages/Single.mTEC.Transcriptomes |
This document contains all the code used to analyse the single-cell RNA-seq and the bulk ATAC-seq data from the manuscript by Brennecke et al, 2015. The purpose of this package is to provide full reproducibility of the results presented in the manuscript. This package provides a documented and reproducible workflow of the code that was used to generate each number and figure from the manuscript.
Brennecke et al. Single-cell transcriptome analysis reveals coordinated ectopic gene-expression patterns in medullary thymic epithelial cells. Nature Immunology 16,933-941 (2015)
A character vector of ensembl gene identifiers defined by Sansom et al, 2014. This list was downloaded from the supplementary material of the manuscript.
data(aireDependentSansom)data(aireDependentSansom)
Sansom et al. Population and single-cell genomics reveal the Aire dependency, relief from Polycomb silencing, and distribution of self-antigen expression in thymic epithelia. Genome Res. 24, 1918–1931 (2014).
A character vector defining biotype for each mouse ensembl gene identifier. Biotypes were queried using biomaRt.
data(biotypes)data(biotypes)
A character vector defining biotype for each human ensembl gene identifier. Biotypes were queried using biomaRt.
data(biotypesHuman)data(biotypesHuman)
A data frame containing information about the Cea1 co-expression group defined in Pinto et al, 2013.
data(cea1Coexpression)data(cea1Coexpression)
Pinto et al. Overlapping gene coexpression patterns in human medullary thymic epithelial cells generate self-antigen diversity. Proc. Natl. Acad. Sci. U.S.A. 110, E3497–3505, (2013).
A matrix containing the gene-gene Spearman correlation across single unselected cells.
A matrix containing the gene-gene Spearman correlation across single unselected cells, using the data from Sansom et al, 2014.
data(corMatsNoMarker) data(corMatsSansom)data(corMatsNoMarker) data(corMatsSansom)
Sansom et al. Population and single-cell genomics reveal the Aire dependency, relief from Polycomb silencing, and distribution of self-antigen expression in thymic epithelia. Genome Res. 24, 1918–1931 (2014).
List of highly variable genes according to the method by Brennecke et al, 2013.
data(deGenesNone)data(deGenesNone)
Brennecke et al. Accounting for technical noise in single-cell RNA-seq experiments. Nat. Methods. 10, 1093-1095 (2013).
List of highly variable genes according to the method by Brennecke et al, 2013, using the data by Santom et al.
data(deGenesSansom)data(deGenesSansom)
Brennecke et al. Accounting for technical noise in single-cell RNA-seq experiments. Nat. Methods. 10, 1093-1095 (2013). Sansom et al. Population and single-cell genomics reveal the Aire dependency, relief from Polycomb silencing, and distribution of self-antigen expression in thymic epithelia. Genome Res. 24, 1918–1931 (2014).
DESeqDataSet object summarizing the ATAC-seq data presented in the manuscript. This object contains the read counts of each sample over a window of 4Kb around transcription start sites.
data(dxdATAC)data(dxdATAC)
DESeqDataSet object of the read counts from selected tissues from the FANTOM dataset.
data(fantom)data(fantom)
Forrest et al. A promoter-level mammalian expression atlas. 24, 1918–1931. (2014).
Character vector of mouse gene names. The gene names were queried using biomaRt.
data(geneNames)data(geneNames)
Character vector of human gene names. The gene names were queried using biomaRt.
data(geneNamesHuman)data(geneNamesHuman)
GenomicRanges object containing the coordinate ranges of mouse protein coding genes used in the manuscript.
data(geneRanges)data(geneRanges)
DESeqDataSet object containing the read counts from the single-cell RNA-seq dataset generated by Brennecke et al, 2015.
data(mTECdxd)data(mTECdxd)
Brennecke et al. Single-cell transcriptome analysis reveals coordinated ectopic gene-expression patterns in medullary thymic epithelial cells. Nature Immunology 16,933-941 (2015)
A data frame containing information about the Muc1 co-expression group defined in Pinto et al, 2013.
data(muc1Coexpression)data(muc1Coexpression)
Pinto et al. Overlapping gene coexpression patterns in human medullary thymic epithelial cells generate self-antigen diversity. Proc. Natl. Acad. Sci. U.S.A. 110, E3497–3505, (2013).
List containing the results from the clustering analysis from Figure 2 from the manuscript.
data(nomarkerCellsClustering)data(nomarkerCellsClustering)
Data frame containing the mapping statistics from the single-cell RNA-seq data.
data(percentsGG)data(percentsGG)
Result from the gene permutations from Figure 5 from the manuscript.
data(permutationResults)data(permutationResults)
Objects containing the output scLVM on the single-mTEC RNA-seq data.
data(scLVM_output)data(scLVM_output)
Buettner et al. Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells. Nat. Biotechnol. 2015.
Data frame containing the TRA classification from Pinto et al, 2013.
data(tras)data(tras)