README.md

In CMET-UGent/MicroRaman: Phenotyping of microbial Raman spectroscopy data

MicroRaman

• Authors: Frederiek-Maarten Kerchkof, Cristina Garcia Timermans, and Ruben Props.

• Contributors: Benjamin Buysschaert, Jasmine Heyse, and Peter Rubbens.

The goal of this package is to provide a standardized and automated workflow for Raman spectra analysis.

If you use this package, please consider citing the original publication in which is was first used:

García-Timermans, C., Rubbens, P., Kerckhof, F. M., Buysschaert, B., Khalenkow, D., Waegeman, W., Skirtach, A. G. & Boon, N. (2018). Label-free Raman characterization of bacteria calls for standardized procedures. Journal of microbiological methods, 151, 69-75.

García‐Timermans, C., Rubbens, P., Heyse, J., Kerckhof, F.‐M., Props, R., Skirtach, A.G., Waegeman, W. and Boon, N. (2020), Discriminating Bacterial Phenotypes at the Population and Single‐Cell Level: A Comparison of Flow Cytometry and Raman Spectroscopy Fingerprinting. Cytometry. doi:10.1002/cyto.a.23952

Install the package:

library("devtools")
install_github("CMET-UGent/MicroRaman", build_vignettes = TRUE)

For exploring the functionalities, take a look at the vignette:

vignette("Demo", package = "MicroRaman")

Core functions

Functions | Description | Functional? ------------ | ----------- | ----------- hs_import | Import Thermo Galactic's spc file format data into the R environment | YES hs_preprocess | Preprocesses the data using the Garcia-Timermans et al. (2020) workflow | YES hs_resample | Resample hyperSpec object to a requested number of spectra | YES hs_contrast | Calculate contrasts between spectra of specified groups of cells | YES hs_hclust | Hierarchical clustering of Raman spectra (with or without bootstrap support) | YES hs_hclust_cutoff | Visualization of distance cut-off in hclust plots | YES hs_type | Clusters spectra using partitioning around medoids | YES hs_PCA | Principal Component Analysis of Raman spectra | YES hs_tsne | t-distributed stochastic neighbor embedding of Raman spectra | YES hs_phenoRam | Calculation of Hill diversity numbers for each individual Raman spectrum | YES hs_coll_curve | Checks sensitivity of Hill diversity calculations under various sample sizes | YES hs_RF | Train Random Forest classifier to distinguish between groups of cells | YES hs_RF_pred | Predict using Random Forest classifier on new data | YES hs_SCAdiss | Calculates the spectral contrast angle (SCA) between all cells in a hyperSpec object | YES

Convenience functions

Functions | Description | Functional? ------------| ----------- | ----------- hs_conv_mq | Converts a hyperSpec::hyperSpec object directly to a MALDIquant::MassSpectrum object | YES mq_conv_hs | Converts a MALDIquant::MassSpectrum object directly to a hyperSpec::hyperSpec object | YES hs_tidy_filenames | Tidies up hyperspec spectral IDs | YES hs_SCA_conv_itol | Convert SCA dissimilarity matrix to itol-compatible object | NO mq_plot | | NO mq_baseline_plot | | NO mq_iter_plot | | NO intervalplot | | NO model_fit_stats | | NO pred_r_squared | | NO PRESS | | NO SCA | Calculates the spectral contrast angle between two vectors | YES wlcutter | | NO

Available datasets

Some datasets are included in the package. They allow the examples and vigenttes to be run. They can be loaded using:

library("MicroRaman")
data("<name of dataset>")

Dataset name | Data contents -------------| ---------------- hs_example | Hyperspec object contaning single-cell data of 64 GFP expressing yeast cells

CMET-UGent/MicroRaman documentation built on July 25, 2020, 6:20 p.m.