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+=============================
+Batch Effect Correction Tools
+=============================
+
+Variability in datasets not only results from biological processes, but also
+from technical bias [Lander1999]_.
+InMoose offers a collection of tools for the correction of such technical bias,
+also called batch effects.
+
+Please refer to [Behdenna2023]_ for a detailed comparison of InMoose
+implementation with the original R implementations.
+
+.. toctree::
+   :maxdepth: 1
+   :caption: Batch effect correction per type of data:
+
+   for microarray data <pycombatnorm>
+   for RNASeq data <pycombatseq>
+
+
+References
+==========
+
+.. [Behdenna2023] A. Behdenna, M. Colange, J. Haziza, A. Gema, G. Appé, C.-A.
+   Azencott and A.  Nordor. 2023. pyComBat, a Python tool for batch effects
+   correction in high-throughput molecular data using empirical Bayes methods.
+   *BMC Bioinformatics* 7;24(1):459. :doi:`10.1186/s12859-023-05578-5`
+
+.. [Johnson2007] W. E. Johnson, C. Li, A. Rabinovic. 2007. Adjusting batch
+   effects in microarray expression data using empirical Bayes methods.
+   *Biostatistics*, 8, 118–12.  :doi:`10.1093/biostatistics/kxj037`
+
+.. [Lander1999] E. S. Lander. 1999. Array of hope. *Nature Genetics*, 21(1
+   Suppl), 3-4.  :doi:`10.1038/4427`
+
+.. [Zhang2020] Y. Zhang, G. Parmigiani, W. E. Johnson. 2020. ComBat-Seq: batch
+   effect adjustment for RNASeq count data. *NAR Genomics and Bioinformatics*,
+   2(3).  :doi:`10.1093/nargab/lqaa078`
+