Analyze, Process, Identify, and Share Raman and (FT)IR Spectra.

Open Specy 1.0

Analyze, Process, Identify, and Share Raman and (FT)IR Spectra

Raman and (FT)IR spectral analysis tool for plastic particles and other environmental samples (Cowger et al. 2021, doi: 10.1021/acs.analchem.1c00123). With read_any(), Open Specy provides a single function for reading individual, batch, or map spectral data files like .asp, .csv, .jdx, .spc, .spa, .0, and .zip. process_spec() simplifies processing spectra, including smoothing, baseline correction, range restriction and flattening, intensity conversions, wavenumber alignment, and min-max normalization. Spectra can be identified in batch using an onboard reference library (Cowger et al. 2020, doi: 10.1177/0003702820929064) using match_spec(). A Shiny app is available via run_app() or online at https://openanalysis.org/openspecy/.

Installation

OpenSpecy is available from CRAN and GitHub.

Install from CRAN (stable version)

You can install the latest release of OpenSpecy from CRAN with:

install.packages("OpenSpecy")

Install from GitHub (development version)

To install the development version of this package, paste the following code into your R console (requires devtools):

if (!require(devtools)) install.packages("devtools")
devtools::install_github("wincowgerDEV/OpenSpecy-package")

Getting started

library(OpenSpecy)
run_app()

Simple workflow for single spectral identification

See package vignette for a detailed standard operating procedure.

# Fetch current spectral library from https://osf.io/x7dpz/
get_lib("derivative")

# Load library into global environment
spec_lib <- load_lib("derivative")

# Read sample spectrum
raman_hdpe <- read_extdata("raman_hdpe.csv") |> 
  read_any()

# Look at the spectrum
plotly_spec(raman_hdpe)

# Process the spectra and conform it to the library format
raman_proc <- raman_hdpe |>
  process_spec(conform_spec_args = list(range = spec_lib$wavenumbers), 
               smooth_intens = T, make_rel = T)

# Compare raw and processed spectra
plotly_spec(raman_hdpe, raman_proc)

top_matches <- match_spec(raman_proc, library = spec_lib, na.rm = T, top_n = 5,
                          add_library_metadata = "sample_name",
                          add_object_metadata = "col_id")

# Print the top 5 results with relevant metadata
top_matches[, c("object_id", "library_id", "match_val", "SpectrumType",
                "SpectrumIdentity")]

# Get all metadata for the matches
get_metadata(spec_lib, logic = top_matches$library_id)

Citations

Cowger W, Steinmetz Z, Gray A, Munno K, Lynch J, Hapich H, Primpke S, De Frond H, Rochman C, Herodotou O (2021). “Microplastic Spectral Classification Needs an Open Source Community: Open Specy to the Rescue!” Analytical Chemistry, 93(21), 7543–7548. doi: 10.1021/acs.analchem.1c00123.

Cowger W, Steinmetz Z, Leong N, Faltynkova A, Sherrod H (2024). “OpenSpecy: Analyze, Process, Identify, and Share Raman and (FT)IR Spectra.” R package, 1.0.8. https://github.com/wincowgerDEV/OpenSpecy-package.