A detailed comparison of analysis processes for MCC-IMS data in disease classification-Automated methods can replace manual peak annotations.

ABSTRACT:

Motivation

Disease classification from molecular measurements typically requires an analysis pipeline from raw noisy measurements to final classification results. Multi capillary column-ion mobility spectrometry (MCC-IMS) is a promising technology for the detection of volatile organic compounds in the air of exhaled breath. From raw measurements, the peak regions representing the compounds have to be identified, quantified, and clustered across different experiments. Currently, several steps of this analysis process require manual intervention of human experts. Our goal is to identify a fully automatic pipeline that yields competitive disease classification results compared to an established but subjective and tedious semi-manual process.

Method

We combine a large number of

SUBMITTER: Horsch S 

PROVIDER: S-EPMC5598980 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature