sabarsi: Background Removal and Spectrum Identification for SERS Data

Implements a new approach 'SABARSI' described in Wang et al., "A Statistical Approach of Background Removal and Spectrum Identification for SERS Data" (Unpublished). Sabarsi forms a pipeline for SERS (surface-enhanced Raman scattering) data analysis including background removal, signal detection, signal integration, and cross-experiment comparison. The background removal algorithm, the very first step of SERS data analysis, takes into account the change of background shape.

Getting started

Package details

AuthorLi Jun [cre], Wang Chuanqi [aut]
MaintainerLi Jun <>
Package repositoryView on CRAN
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sabarsi documentation built on Aug. 8, 2019, 5:02 p.m.