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Update README.md
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LorenzoMerotto authored Jan 23, 2025
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Expand Up @@ -85,8 +85,13 @@ For more detailed usage instructions, see the Documentation:

Note that, while _immunedeconv_ itself is free ([BSD](https://github.com/omnideconv/immunedeconv/blob/master/LICENSE)), you may need to obtain a license to use the individual methods. See the table below for more information. If you use this package in your work, please cite both our package and the method(s) you are using.

For the human-based methods, cite:
> Sturm, G., Finotello, F., Petitprez, F., Zhang, J. D., Baumbach, J., Fridman, W. H., ..., List, M., Aneichyk, T. (2019). Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics, 35(14), i436-i445. https://doi.org/10.1093/bioinformatics/btz363
For the mouse/custom-based methods, cite:

> Merotto, L., Sturm, G., Dietrich, A., List, M., Finotello, F. (2024). Making mouse transcriptomics deconvolution accessible with immunedeconv, Bioinformatics Advances, Volume 4, Issue 1. https://doi.org/10.1093/bioadv/vbae032
| method | organism | license | citation |
| -------------------------------------------------------------------------- | -------- | ------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| [quanTIseq](http://icbi.at/software/quantiseq/doc/index.html) | human | free ([BSD](https://github.com/omnideconv/immunedeconv/blob/master/LICENSE.md)) | Finotello, F., Mayer, C., Plattner, C., Laschober, G., Rieder, D., Hackl, H., ..., Sopper, S. (2019). Molecular and pharmacological modulators of the tumor immune contexture revealed by deconvolution of RNA-seq data. Genome medicine, 11(1), 34. https://doi.org/10.1186/s13073-019-0638-6 |
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