proActiv is an R package that estimates promoter activity from RNA-Seq data. proActiv uses aligned reads and genome annotations as input, and provides absolute and relative promoter activity as output. The package can be used to identify active promoters and alternative promoters. Details of the method are described in Demircioglu et al.
HTML documentation of proActiv, including a complete step-by-step workflow and a function manual, is available at https://goekelab.github.io/proActiv/.
Additional data on differential promoters in tissues and cancers from TCGA, ICGC, GTEx, and PCAWG is available at https://jglab.org/data-and-software/.
proActiv can be installed from Bioconductor:
if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("proActiv")
proActiv estimates promoter activity from RNA-Seq data. Promoter
activity is defined as the total amount of transcription initiated at
each promoter. proActiv takes as input either BAM files or junction
files (TopHat2 or STAR), and a promoter annotation object of the
relevant genome. An optional argument
condition can be supplied,
describing the experimental condition corresponding to each input file.
Here we demonstrate proActiv with STAR junction files (Human genome
GRCh38 GENCODE v34) as input. These files are taken from the SGNEx
project but restricted to the
chr1:10,000,000-30,000,000 region, and can be found at
library(proActiv) ## List of STAR junction files as input files <- list.files(system.file('extdata/vignette/junctions', package = 'proActiv'), full.names = TRUE) ## Vector describing experimental condition condition <- rep(c('A549','HepG2'), each=3) ## Promoter annotation for human genome GENCODE v34 promoterAnnotation <- promoterAnnotation.gencode.v34.subset result <- proActiv(files = files, promoterAnnotation = promoterAnnotation, condition = condition)
result is a summarizedExperiment object which can be accessed as
assays(results)returns raw/normalized promoter counts, absolute/relative promoter activity and gene expression data
rowData(results)returns promoter metadata and summarized absolute promoter activity by conditions
proActiv can also be run with BAM files as input, but an additional
genome must be supplied:
## From BAM files - genome parameter must be provided files <- list.files(system.file('extdata/testdata/bam', package = 'proActiv'), full.names = TRUE) result <- proActiv(files = files, promoterAnnotation = promoterAnnotation.gencode.v34.subset, genome = 'hg38')
In order to quantify promoter activity, proActiv uses a set of promoters
based on genome annotations. proActiv allows the creation of a promoter
annotation object for any genome from a TxDb object or from a GTF file
preparePromoterAnnotation function. Users have the option to
either pass the file path of the GTF/GFF or TxDb to be used, or use the
TxDb object directly as input. proActiv includes pre-calculated promoter
annotations for the human genome (GENCODE v34). However, due to size
constraints, the annotation is restricted to the
chr1:10,000,000-30,000,000 region. Users can build full annotations by
downloading GTF files from GENCODE page
and following the steps below.
Here, we demonstrate creating the subsetted promoter annotation for the Human genome (GENCODE v34) with both GTF and TxDb:
## From GTF file path gtf.file <- system.file('extdata/vignette/annotation/gencode.v34.annotation.subset.gtf.gz', package = 'proActiv') promoterAnnotation.gencode.v34.subset <- preparePromoterAnnotation(file = gtf.file, species = 'Homo_sapiens') ## From TxDb object txdb.file <- system.file('extdata/vignette/annotation/gencode.v34.annotation.subset.sqlite', package = 'proActiv') txdb <- loadDb(txdb.file) promoterAnnotation.gencode.v34.subset <- preparePromoterAnnotation(txdb = txdb, species = 'Homo_sapiens')
PromoterAnnotation object has 3 slots:
intronRanges: Intron ranges, giving the corresponding transcripts of each intron
promoterIdMapping: An ID mapping between transcripts, promoter IDs and gene IDs
promoterCoordinates: Promoter coordinates (TSS) and internal promoter state, along with the 3’ coordinate of the first exon
Most human genes have multiple promoters that control the expression of distinct isoforms. The use of these alternative promoters enables the regulation of isoform expression pre-transcriptionally. Importantly, alternative promoters have been found to be important in a wide number of cell types and diseases. proActiv includes a workflow to identify and visualize alternative promoter usage between conditions. This workflow is described in detail here.
Date: 7th April 2021
Changes in version 1.1.18:
Gene expression data is now stored in the
assays of the
summarizedExperiment object returned by
proActiv to facilitate
easier filtering of the summarizedExperiment object. The metadata
slot is now empty.
Plotting promoter activity: Implementation of
function to plot boxplots of absolute promoter activity, relative
promoter activity, and gene expression.
Identification of alternative promoters: Implementation of
getAlternativePromoters, used to identify promoters that may
exhibit alternative usage.
Release date: 28th October 2020
Released with Bioconductor 3.12
Release date: 21st August 2020
Changes in version 0.99.0:
Workflow: The wrapper function
proActiv performs all steps to
estimate promoter activity and calculates promoter metadata. A
condition argument can be supplied for
proActiv to summarize
promoter counts and activity across conditions. These results are
returned as a SummarizedExperiment object.
BAM file usage: In addition to junction files,
proActiv now allows
BAM files as input. However, users should note that this function is
not fully optimized and may have long run-time.
Promoter annotation: Improved efficiency in generating promoter
annotations without the need for parallelization with the
preparePromoterAnnotations function. The promoter annotation
object is also trimmed to preserve essential information for running
proActiv, in order to comply with Bioconductor guidelines
concerning package size.
Plotting promoter activity: The plotting function
visualizes promoter activity across conditions. It accepts the
SummarizedExperiment object returned by
proActiv along with a gene
of interest and gene annotations as arguments. This allows users to
visualize promoter activity and identify instances of alternative
Vignette: proActiv now comes with a vignette, documenting a complete
step-by-step workflow in identifying active and alternative promoter
usage. This includes guidance on running
promoter annotations and identifying alternative promoter usage.
Various visualizations of promoter activity are also offered.
Initial Release 0.1.0
Release date: 19th May 2020
This release corresponds to the proActiv version used by Demircioglu et al.
proActiv will not provide promoter activity estimates for promoters which are not uniquely identifiable from splice junctions (single exon transcripts, promoters which overlap with internal exons).
If you use proActiv, please cite:
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