# RLSeq <img src="https://rlbase-data.s3.amazonaws.com/misc/assets/whitebgRLSeq+Logo.png" align="right" alt="logo" width="240" style = "border: none; float: right;">
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*RLSeq* (part of [*RLSuite*](https://gccri.bishop-lab.uthscsa.edu/rlsuite/)) is used for downstream analysis of R-loop datasets. It provides methods for data quality control and exploratory analysis within the context of the hundreds of publicly-available R-loop mapping data sets provided by [RLBase](https://github.com/Bishop-Laboratory/RLBase) and accessed via [RLHub](https://github.com/Bishop-Laboratory/RLHub). Finally, *RLSeq* provides a user-friendly HTML report that summarizes the analysis results.
**NOTE**: To run *RLSeq* in your browser, please see [*RLBase*](https://gccri.bishop-lab.uthscsa.edu/rlbase/).
### From Bioconductor
if (!requireNamespace("BiocManager", quietly = TRUE))
### From Github
1. Update to the `devel` version of bioconductor.
BiocManager::install(version = "devel")
2. Install **RLHub** and **RLSeq** with remotes.
This is an example workflow using a publicly-available R-loop mapping data set that
was reprocessed and standardized in [*RLBase*](https://gccri.bishop-lab.uthscsa.edu/rlbase/).
# Peaks and coverage can be found in RLBase
rlbase <- "https://rlbase-data.s3.amazonaws.com"
pks <- file.path(rlbase, "peaks", "SRX1025890_hg38.broadPeak")
cvg <- file.path(rlbase, "coverage", "SRX1025890_hg38.bw")
# Initialize data in the RLRanges object.
# Metadata is optional, but improves the interpretability of results
rlr <- RLRanges(
peaks = pks,
coverage = cvg,
genome = "hg38",
mode = "DRIP",
label = "POS",
sampleName = "TC32 DRIP-Seq"
# The RLSeq command performs all analyses
rlr <- RLSeq(rlr)
# Generate an html report
The code above performs a typical analysis. It builds the `RLRanges` object, an extension of `GRanges` for
use with RLSeq. Then, it runs all core analyses using `RLSeq()`. Finally, it generates an
HTML report with `report()` (see the report
For more information, see the package website [here](https://bishop-laboratory.github.io/RLSeq/).