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described in Wang et al., "A Statistical Approach of Background Removal and Spectrum Identification for SERS Data" (Unpublished).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.

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Description file content

Package
sabarsi
Type
Package
Title
Background Removal and Spectrum Identification for SERS Data
Version
0.1.0
Description
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described in Wang et al., "A Statistical Approach of Background Removal and Spectrum Identification for SERS Data" (Unpublished).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.
Depends
R (>= 3.5.0)
Suggests
knitr, rmarkdown (>= 1.13)
Imports
stats (>= 3.5.0)
License
GPL-3
Encoding
UTF-8
LazyData
true
VignetteBuilder
knitr
RoxygenNote
6.1.1
NeedsCompilation
no
Packaged
2019-08-07 11:29:47 UTC; Chuanqi
Author
Li Jun [cre], Wang Chuanqi [aut]
Maintainer
Li Jun
Repository
CRAN
Date/Publication
2019-08-08 12:30:02 UTC

install.packages('sabarsi')

0.1.0

4 months ago

Li Jun

GPL-3

Depends on

R (>= 3.5.0)

Imports

stats (>= 3.5.0)

Suggests

knitr, rmarkdown (>= 1.13)

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