@@ -6,7 +6,7 @@ Given one or several [FASTQ](https://en.wikipedia.org/wiki/FASTQ_format) file(s)
_ROCK_ can therefore be used to reduce and/or homogenize the overall coverage depth within large sets of HTS reads, which is often required to quickly infer accurate _de novo_ genome assemblies (e.g. Desai et al. 2013, Chen et al. 2015).
_ROCK_ can also be used to discard low-covering HTS reads, as those ones are often artefactual, highly erroneous or contaminating sequences.
For more details, see the associated publication: Legrand et al. (2022) [](https://doi.org/10.21105/joss.03790)
## Compilation and installation
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@@ -305,6 +305,8 @@ Durai DA, Schulz MH (2019) _Improving in-silico normalization using read weights
Kokot M, Długosz M, Deorowicz S (2017) _KMC 3: counting and manipulating k-mer statistics_. **Bioinformatics**, 33(17):2759-2761. [doi:10.1093/bioinformatics/btx304](https://doi.org/10.1093/bioinformatics/btx304).
Legrand V, Kergrohen T, Joly N, Criscuolo A (2022) _ROCK: digital normalization of whole genome sequencing data_. **Journal of Open Source Software**, 7(73):3790. [doi:10.21105/joss.03790](https://doi.org/10.21105/joss.03790).
Liu B, Shi Y, Yuan J, Hu X, Zhang H, Li N, Li Z, Chen Y, Mu D, Fan W (2013) _Estimation of genomic characteristics by analyzing k-mer frequency in de novo genome projects_. **arXiv**:[1308.2012v2](https://arxiv.org/abs/1308.2012v2).
