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# High-Throughput RNA-seq model fit # High-Throughput RNA-seq model fit
- [Getting started](#getting-started)
- [Installation](#installation)
- [CRAN packages dependencies](#cran-packages-dependencies)
- [Docker](#docker)
## Why use HTRfit ## Why use HTRfit
HTRfit provides a robust statistical framework that allows you to investigate the essential experimental parameters influencing your ability to detect expression changes. Whether you're examining sequencing depth, the number of replicates, or other critical factors, HTRfit's computational simulation is your go-to solution. HTRfit provides a robust statistical framework that allows you to investigate the essential experimental parameters influencing your ability to detect expression changes. Whether you're examining sequencing depth, the number of replicates, or other critical factors, HTRfit's computational simulation is your go-to solution.
...@@ -7,10 +13,13 @@ HTRfit provides a robust statistical framework that allows you to investigate th ...@@ -7,10 +13,13 @@ HTRfit provides a robust statistical framework that allows you to investigate th
Furthermore, by enabling the inclusion of fixed effects, mixed effects, and interactions in your RNAseq data analysis, HTRfit provides the flexibility needed to conduct your differential expression analysis effectively. HTRfit is particularly adapted for the analysis of large number of samples, or highly multiplexed experiments. Furthermore, by enabling the inclusion of fixed effects, mixed effects, and interactions in your RNAseq data analysis, HTRfit provides the flexibility needed to conduct your differential expression analysis effectively. HTRfit is particularly adapted for the analysis of large number of samples, or highly multiplexed experiments.
- [Installation](#installation) ## Getting started
- [CRAN packages dependencies](#cran-packages-dependencies)
- [Docker](#docker) * [ Theory behind HTRfit ](https://htrfit-lbmc-yvertlab-vortex-plasticity-mutation-477701eb488dfd9.gitbiopages.ens-lyon.fr/articles/01-theoryBehindHtrfit.html)
- [Getting started](#getting-started) * [ Simulation tutorial ](https://htrfit-lbmc-yvertlab-vortex-plasticity-mutation-477701eb488dfd9.gitbiopages.ens-lyon.fr/articles/02-tutorial.html)
* [ RNAseq analysis with HTRfit ](https://htrfit-lbmc-yvertlab-vortex-plasticity-mutation-477701eb488dfd9.gitbiopages.ens-lyon.fr/articles/03-rnaseq_analysis.html)
* [ Benchmarking HTRfit/DESeq2 ](https://htrfit-lbmc-yvertlab-vortex-plasticity-mutation-477701eb488dfd9.gitbiopages.ens-lyon.fr/articles/04-htrfit_vs_deseq2.html)
## Installation ## Installation
...@@ -92,10 +101,3 @@ docker run -it --rm \ ...@@ -92,10 +101,3 @@ docker run -it --rm \
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. 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** can be installed using the [method A](#method-a).
## Getting started
* [ Theory behind HTRfit ](https://htrfit-lbmc-yvertlab-vortex-plasticity-mutation-477701eb488dfd9.gitbiopages.ens-lyon.fr/articles/theoryBehindHtrfit.html)
* [ Simulation tutorial ](https://htrfit-lbmc-yvertlab-vortex-plasticity-mutation-477701eb488dfd9.gitbiopages.ens-lyon.fr/articles/tutorial.html)
* [ Benchmarking HTRfit/DESeq2 ](https://htrfit-lbmc-yvertlab-vortex-plasticity-mutation-477701eb488dfd9.gitbiopages.ens-lyon.fr/articles/htrfit_vs_deseq2.html)
* [ RNAseq analysis with HTRfit ](https://htrfit-lbmc-yvertlab-vortex-plasticity-mutation-477701eb488dfd9.gitbiopages.ens-lyon.fr/articles/rnaseq_analysis.html)
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