From c7aa195532aeda3c384a7a6c6fde3ff3842b3e64 Mon Sep 17 00:00:00 2001
From: Ines Scheller <56256384+ischeller@users.noreply.github.com>
Date: Fri, 24 Nov 2023 14:45:39 +0100
Subject: [PATCH] Update README.md

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 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

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 [![Coverage status](https://codecov.io/gh/c-mertes/FRASER/branch/master/graph/badge.svg)](https://codecov.io/github/c-mertes/FRASER/branch/master)
 [![License](https://img.shields.io/github/license/mashape/apistatus.svg?maxAge=2592000)](https://github.com/c-mertes/FRASER/blob/master/LICENSE)
 
-FRASER is a tool to detect aberrant splicing events in RNA-seq data. The method is described and published in [Nature Communications](https://doi.org/doi:10.1038/s41467-020-20573-7) and available through [Bioconductor](https://doi.org/doi:10.18129/B9.bioc.FRASER). It is also part of the [Detection of RNA Outlier Pipeline (DROP)](https://github.com/gagneurlab/drop). The DROP pipeline is described and published in [Nature Protocols](https://doi.org/doi:10.1038/s41596-020-00462-5).
+FRASER is a tool to detect aberrant splicing events in RNA-seq data. The method is described and published in [Nature Communications](https://doi.org/doi:10.1038/s41467-020-20573-7) and available through [Bioconductor](https://doi.org/doi:10.18129/B9.bioc.FRASER). It is also part of the [Detection of RNA Outlier Pipeline (DROP)](https://github.com/gagneurlab/drop). DROP is described and published in [Nature Protocols](https://doi.org/doi:10.1038/s41596-020-00462-5).
                                                                              
 The FRASER framework and workflow aims to assist the diagnostics in the field of rare diseases where RNA-seq is performed to identify aberrant splicing defects. For a short tutorial on how to use FRASER on a dataset please use the [vignette](http://bioconductor.org/packages/release/bioc/vignettes/FRASER/inst/doc/FRASER.pdf) or our Colab tutorial at: [http://tinyurl.com/RNA-ASHG-colab](http://tinyurl.com/RNA-ASHG-colab). The Colab is based on a workshop that we presented at ASHG 2019/2020.