semvec/pypi-packages huggingface dataset:
gssnng 0.5.0
Gene Set Scoring on the Nearest Neighbor Graph (gssnng)
License: MIT

# gssnng
Gene Set Scoring on the Nearest Neighbor Graph (gssnng) for Single Cell RNA-seq (scRNA-seq).


This package works with Scanpy AnnData objects stored as h5ad files.

  *  **[Read the Docs!](https://gssnng.readthedocs.io/en/latest/)**

  * **Notebook using gmt files  ===>>>**  [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/IlyaLab/gssnng/blob/main/notebooks/gssnng_quick_start.ipynb)

  * **Notebook using Decoupler/Omnipath style API ===>>>** [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/IlyaLab/gssnng/blob/main/notebooks/Scoring_PBMC_data_with_the_GSSNNG_decoupleR_API.ipynb)

  * **Notebook for smoothing counts. COMING SOON! For now, see the example script in test.

  * **See the paper ===>>>** [gssnng](https://academic.oup.com/bioinformaticsadvances/article/3/1/vbad150/7321111?login=false)

The GSSNNG method is based on using the nearest neighbor graph of cells for data smoothing. This essentially creates 
mini-pseudobulk expression profiles for each cell, which can be scored by using single sample gene set scoring 
methods often associated with bulk RNA-seq. 

Nearest neighbor graphs (NNG) are constructed based on user defined groups (see the 'groupby' parameter below). 
The defined groups can be processed in parallel, speeding up the calculations. For example, a NNG could be 
constructed within each cluster or jointly by cluster *and* sample. Smoothing can be performed using either the 
adjacency matrix (all 1s) or the weighted graph to give less weight to more distant cells.
curry-batch 0.4.2
Curry a list of commands passed as arguments with a YAML list of argument lists, then output the command stdout as a new YAML list of lists.
License: MIT
Requires Python: >=3.12,<4.0

Curry-batch reads from stdin a YAML list of argument lists and a set of command templates as arguments.
It curries the commands with the argument lists, runs them, and captures the outputs, storing them in a new list.

Example:

argument list:
- - hello
  - world
- - brain
  - wash

template filters:
"echo {1}" "echo {2}" "echo {1}, {2}!" "echo {1} {2} {1} {2}"

output:
- - hello
  - world
  - hello, world!
  - hello world hello world
- - brain
  - wash
  - brain, wash!
  - brain wash brain wash