# BARCHAN: Blob Alignment for Robust CHromatographic ANalysis

## TL;DR

BARCHAN is an automated, robust alignment method for 2D gas chromatography data that improves speed and reliability in peak identification and quantification.

## Contribution

The paper introduces BARCHAN, a novel peak registration algorithm that automates chromatogram alignment using probabilistic transformations, handling noise and missing peaks.

## Key findings

- Proves to be fast and reliable in aligning chromatograms.
- Reduces analysis time significantly.
- Effective in handling noise and outliers.

## Abstract

Comprehensive Two dimensional gas chromatography (GCxGC) plays a central role into the elucidation of complex samples. The automation of the identification of peak areas is of prime interest to obtain a fast and repeatable analysis of chromatograms. To determine the concentration of compounds or pseudo-compounds, templates of blobs are defined and superimposed on a reference chromatogram. The templates then need to be modified when different chromatograms are recorded. In this study, we present a chromatogram and template alignment method based on peak registration called BARCHAN. Peaks are identified using a robust mathematical morphology tool. The alignment is performed by a probabilistic estimation of a rigid transformation along the first dimension, and a non-rigid transformation in the second dimension, taking into account noise, outliers and missing peaks in a fully automated way. Resulting aligned chromatograms and masks are presented on two datasets. The proposed algorithm proves to be fast and reliable. It significantly reduces the time to results for GCxGC analysis.