We are pleased to share the software and tools that we have developed in order to process our raw data. Below you will find a list, download links, and appropriate citations.
BMXP CORE TOOLS
Our core tools for processing data are written in Python and C, and are freely available. They consist of:
- Eclipse - Align multiple LCMS datasets by feature descriptors
- Blueshift - Drift Correction using pooled references and internal standards
- Gravity- Feature Clustering based on RT and sample abundance correlation
- Chroma - Performant .raw and .mzml file reader for extraction of MS2 and XICs
For publication, please cite this publication for Eclipse.
TARGETED FEATURE EXTRACTOR
Coming soon, a cross-platform targeted feature extractor, designed for guided/manual integration of features on large projects. TFE can be used for Orbitrap or QQQ data, and is designed to handle thousands of samples. Stay tuned.
CASTNET
Python REST<->Neo4j bindings, offering typecasting and schema management. Castnet powers our internal database Atlas.
KBBQ GRAPH
A memory efficient Python and C graph library for working with very large k-partite graphs. KBBQGraph was developed to handle Eclipse matching for large (100k+ features) or many (>50) datasets.