Pathomx is a workflow-based data analysis tool built on IPython. It began as a metabolomic-analysis toolkit, but has extended to support general data analysis workflows. It aims to be simple to use for non-experts while powerful enough for complex analysis tasks. Key to both of these goals is the ability to create 'custom tools' that can be drag-dropped together to form larger workflows.
This short demo shows analysis of a publically available GEO dataset using Pathomx, with a workflow build using the new visual editor (available in the next release).
The NCBI Gene Expression Omnibus (GEO) is 'is a public functional genomics data repository supporting MIAME-compliant data submissions.' In other words, its a online database of freely available experimental gene-expression data. Quite useful.
Short demo of an experimental analysis of metabolomic (NMR) data using Pathomx. Metabolomic test dataset produced from THP-1 cells grown under normal and hypoxic conditions. Spectra (2D 1H JRES) have been pre-processed and quantified using the BML-NMR service.
A Python implementation of the Icoshift algorithm, a versatile tool for the rapid alignment of 1D NMR spectra