Experiment and sample description

This package provides the output of running Salmon on a set of 24 RNA-seq samples from Alasoo, et al. “Shared genetic effects on chromatin and gene expression indicate a role for enhancer priming in immune response”, published in Nature Genetics, January 2018 doi: 10.1038/s41588-018-0046-7.

6 donors were selected from those that had publicly available reads in ENA. The selection procress is recorded in the file inst/scripts/ena_download.R, the donors were chosen as all female, the sample having been received as frozen, and then the top 6 were chosen based on mean purity as recorded by the study authors.

Salmon quantification

Salmon version 0.12.0 was run using Gencode human reference transcripts v29, with a snakemake script that can be seen in inst/scripts/Snakemake and with log output in inst/scripts/snakemake.log.

The quantification output is in the inst/extdata/quants directory. The quant.sf files have been gzipped to preserve space, so they are stored as quant.sf.gz. Salmon was run with 20 Gibbs inferential replicates for each sample. To reduce the size of the package, the inferential replicates (aux_info/bootstrap) and the aux_info/ambig_info.tsv files are no longer included in inst/extdata/quants (as of version 1.29.1). The full Salmon output, including the inferential replicates, is archived on Zenodo: doi: 10.5281/zenodo.22982581. The inferential replicates for a subset of genes are provided in the macro_txp_se object (see below).

The file inst/extdata/gencode.v29.annotation.slim.gtf.gz is a reduced version of the Gencode v29 GTF file, containing only the gene and transcript features, with a subset of the attributes (gene_id, transcript_id, gene_type, gene_name, transcript_type, transcript_name). It can be used to build transcript and gene ranges, but not exon ranges. It was created with the script inst/scripts/makeSlimGTF.sh.

Sample information

The inst/scripts/ena_downloads.R R script also shows how the column data file coldata.csv was generated. This file contains the phenotypic information about the 24 samples:

dir <- system.file("extdata", package="macrophage")
coldata <- read.csv(file.path(dir,"coldata.csv"))
coldata <- coldata[,c(1,2,3,5)]
coldata
##             names sample_id line_id condition_name
## 1  SAMEA103885102    diku_A  diku_1          naive
## 2  SAMEA103885347    diku_B  diku_1           IFNg
## 3  SAMEA103885043    diku_C  diku_1         SL1344
## 4  SAMEA103885392    diku_D  diku_1    IFNg_SL1344
## 5  SAMEA103885182    eiwy_A  eiwy_1          naive
## 6  SAMEA103885136    eiwy_B  eiwy_1           IFNg
## 7  SAMEA103885413    eiwy_C  eiwy_1         SL1344
## 8  SAMEA103884967    eiwy_D  eiwy_1    IFNg_SL1344
## 9  SAMEA103885368    fikt_A  fikt_3          naive
## 10 SAMEA103885218    fikt_B  fikt_3           IFNg
## 11 SAMEA103885319    fikt_C  fikt_3         SL1344
## 12 SAMEA103885004    fikt_D  fikt_3    IFNg_SL1344
## 13 SAMEA103885284    ieki_A  ieki_2          naive
## 14 SAMEA103885059    ieki_B  ieki_2           IFNg
## 15 SAMEA103884898    ieki_C  ieki_2         SL1344
## 16 SAMEA103885157    ieki_D  ieki_2    IFNg_SL1344
## 17 SAMEA103885111    podx_A  podx_1          naive
## 18 SAMEA103884919    podx_B  podx_1           IFNg
## 19 SAMEA103885276    podx_C  podx_1         SL1344
## 20 SAMEA103885021    podx_D  podx_1    IFNg_SL1344
## 21 SAMEA103885262    qaqx_A  qaqx_1          naive
## 22 SAMEA103885228    qaqx_B  qaqx_1           IFNg
## 23 SAMEA103885308    qaqx_C  qaqx_1         SL1344
## 24 SAMEA103884949    qaqx_D  qaqx_1    IFNg_SL1344

SummarizedExperiment

The package also contains a summarized experiment object created using the script in inst/scripts/gse_create.R. This object can be loaded with data("gse").

Additionally, the package contains a transcript-level SummarizedExperiment, macro_txp_se, including the 20 inferential replicates, for all transcripts of a random subset of 2000 expressed genes plus the GBP gene family, and a transcript-to-gene table, macro_tx2gene. These were created with the script in inst/scripts/makeSumExp.R and are used in the fishpond vignette. See ?macro_txp_se and ?macro_tx2gene for details.

Acknowledgments

Thanks to the study authors for posting their data publicly and clearly labelling their data.

Session info

sessionInfo()
## R version 4.6.1 (2026-06-24)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 24.04.5 LTS
## 
## Matrix products: default
## BLAS:   /home/biocbuild/bbs-3.24-bioc/R/lib/libRblas.so 
## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.0  LAPACK version 3.12.0
## 
## locale:
##  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=en_GB              LC_COLLATE=C              
##  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
##  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
## 
## time zone: America/New_York
## tzcode source: system (glibc)
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## loaded via a namespace (and not attached):
## [1] compiler_4.6.1 cli_3.6.6      tools_4.6.1    otel_0.2.0     knitr_1.52    
## [6] xfun_0.61      rlang_1.3.0    evaluate_1.0.5