From 97c329793e6ace210fe5e12800e8d8a9ef3f861a Mon Sep 17 00:00:00 2001 From: Mikaela Koutrouli <81096946+mikelkou@users.noreply.github.com> Date: Fri, 8 Dec 2023 13:38:21 +0100 Subject: [PATCH] Update README.md --- README.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index a7d5ef3..f6e392b 100644 --- a/README.md +++ b/README.md @@ -23,7 +23,7 @@ pip install favapy ``` ## favapy as Python library -Read the jupyter-notebook: [How_to_use_favapy_in_a_notebook](https://github.com/mikelkou/fava/blob/main/How_to_use_favapy_in_a_notebook.ipynb) +Read the [How_to_use_favapy_in_a_notebook](https://github.com/mikelkou/fava/blob/main/How_to_use_favapy_in_a_notebook.ipynb) or the [documentation](https://fava.readthedocs.io/en/latest/). favapy supports both AnnData objects and count/abundance matrices. @@ -34,15 +34,13 @@ Run favapy from the command line as follows: favapy ``` -### Optional parameters: +#### Optional parameters: ``` -t Type of input data ('tsv' or 'csv'). Default value = 'tsv'. -n The number of interactions in the output file (with both directions, proteinA-proteinB and proteinB-proteinA). Default value = 100000. --cor Type of correlation method ('pearson' or 'spearman'). Default value = 'pearson' - -c The cut-off on the Correlation scores.The scores can range from 1 (high correlation) to -1 (high anti-correlation). This option overwrites the number of interactions. Default value = None. -d The dimensions of the intermediate\hidden layer. Default value depends on the input size. @@ -53,6 +51,8 @@ favapy -b The batch size. Default value = 32. +-cor Type of correlation method ('pearson' or 'spearman'). Default value = 'pearson' + ```