
Security Fundamentals
Turtles, Clams, and Cyber Threat Actors: Shell Usage
The Socket Threat Research Team uncovers how threat actors weaponize shell techniques across npm, PyPI, and Go ecosystems to maintain persistence and exfiltrate data.
Authors: Ted Verhey, Heewon Seo, Sorana Morrissy
cNMF-SNS (consensus Non-negative Matrix Factorization Solution Network Space) is a Python package enabling mosaic integration of bulk, single-cell, and spatial expression data between and within datasets. Datasets can have partially overlapping features (eg. genes) as well as non-overlapping features. cNMF provides a robust, unsupervised deconvolution of each dataset into gene expression programs (GEPs). Network-based integration of GEPs enables flexible integration of many datasets across assays (eg. Protein, RNA-Seq, scRNA-Seq, spatial expression) and patient cohorts.
Communities with GEPs from multiple datasets can be annotated with dataset-specific annotations to facilitate interpretation.
Here are just a few of the things that cNMF-SNS does well:
Install the package with conda (in an isolated conda environment)
conda create -n cnmfsns -c conda-forge cnmfsns
conda activate cnmfsns
cNMF-SNS can factorize a wide variety of datasets, but will work optimally in these conditions:
To get started, sample proteomics datasets and a Jupyter notebook tutorial is available here.
Detailed API reference can be found on ReadTheDocs.
See the command line interface documentation.
For errors arising during use of cNMF-SNS, create and browse issues in the GitHub "issues" tab.
FAQs
cNMF Solution Network Space
We found that cnmfsns demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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