You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Variational inference for antibody-based single cell technologies.
11
11
12
-
## Getting started
12
+
CytoVI accomplishes the following analysis tasks:
13
+
14
+
- Integration/batch correction
15
+
- Differential protein expression analysis
16
+
- Label-free differential abundance analysis
17
+
- Imputation of unseen proteins from overlapping antibody panels
18
+
- Technology integration (e.g. Flow and Mass cytometry)
19
+
- RNA/modality imputation after integration of flow/mass cytometry data with CITE-seq data
20
+
- Automated cell annotation via transfer learning
13
21
14
-
Please refer to the [documentation][link-docs]. In particular, the
22
+
## Getting started
15
23
16
-
-[API documentation][link-api].
24
+
To get started please check out the basic analysis notebook in the [docs](https://github.com/florianingelfinger/CytoVI/blob/main/docs/notebooks/Basic_CytoVI_workflow.ipynb).
17
25
18
26
## Installation
19
27
20
-
You need to have Python 3.9 or newer installed on your system. If you don't have
28
+
You need to have Python 3.10 or newer installed on your system. If you don't have
21
29
Python installed, we recommend installing [Mambaforge](https://github.com/conda-forge/miniforge#mambaforge).
22
30
23
31
There are several alternative options to install CytoVI:
0 commit comments