Full Changelog: v1.0.1...v2.0.0

Since May 13 2024, we have put out multinichenetr 2.0.0. on the main branch. Please install this latest version of multinichenetr, which has been improved at several levels compared to the first version:

Novelties

Here is a concise list of methodological novelties compared to the previous version. See the tutorials for more in-depth explanation on each of these aspects. These novelties will also be discussed in the revised version of the manuscript.

• It is now possible to add new prioritization criteria based on additional data modalities. This option can helps users prioritize interactions better if they have additional complementary data, such as proteomics data. This option can help overcome major limitations of cell-cell communication inference from transcriptomics data.
• An additional alternative workflow has been added to prioritize interactions involving condition-specific cell types. This option was added to not ignore biological signal from potentially relevant condition-specifc cell types.
• More emphasis on the usability of the "Intercellular regulatory network" to prune prioritized interactions.
• Integration with the Omnipath L-R database to check database source, quality and curation effort behind prioritized ligand-receptor interactions.

Software changes

Here is a concise list of software changes compared to the previous version. See the tutorials for more in-depth explanation on each of these aspects.

• Gene filtering has been modified slightly, resulting in fewer and easier to interpret parameters and more consistency with the rest of the MultiNicheNet methodology
• Prioritization can now be done by only using the up-regulatory ligand activities instead of both up- and downregulatory activities. This option was added because of the difficulty of interpreting downregulatory activities.
• The option to flexibly change prioritization weights has been replaced by the option to select biological scenario’s. This reduces the number of parameters for the end users and limits unwanted tunability of end results.
• The standard interpretable bubble plot visualization has been extended and provides now information about cell-type specificity, fraction of expression, and curation effort of the ligand-receptor pairs according to Omnipath. As a result of this, this plot now summarizes all the criteria used for prioritization and gives an indication about the curation effort of the ligand-receptor prior knowledge. This can help users now to get better insights in their results and define better candidate interactions for follow-up validation.