You also have the option to download a release directly from the [HTRfit release page](https://gitbio.ens-lyon.fr/aduvermy/HTRfit/-/releases). Once you've downloaded the release, simply untar the archive. After that, open your R console and execute the following command, where HTRfit-v1.0.0 should be replaced with the path to the untarred folder:
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@@ -67,6 +67,12 @@ We have developed [Docker images](https://hub.docker.com/repository/docker/ruana
7. Enjoy HTRfit !
## Biosphere virtual machine
A straightforward way to use **HTRfit** is to run it on a Virtual Machine (VM) through [Biosphere](https://biosphere.france-bioinformatique.fr/catalogue/). We recommend utilizing a VM that includes RStudio for an integrated development environment (IDE) experience. Biosphere VM resources can also be scaled according to your simulation needs.
**HTRfit** can be installed using the [method A](#method-A).
## HTRfit simulation workflow
In the realm of RNAseq analysis, various key experimental parameters play a crucial role in influencing the statistical power to detect expression changes. Parameters such as sequencing depth, the number of replicates, and more have a significant impact. To navigate the selection of optimal values for these experimental parameters, we introduce a comprehensive statistical framework known as **HTRfit**, underpinned by computational simulation. Moreover, **HTRfit** offers seamless compatibility with DESeq2 outputs, facilitating a comprehensive evaluation of RNAseq analysis.
