SIFT-R {siftr} 📦

Tools for streamlining the use of SIFT-MS data in WACL.

Note: Maintenance of this package has been taken over by WACL at: https://github.com/wacl-york/siftr/

To install, just write the following into your R console.

devtools::install_github("jack-davison/siftr")

Reading Data

Currently, the only feature of the package is simplifying the reading-in of SIFT data.

Raw SIFT data

The key function is read_sift, which simply reads in raw SIFT data and returns a list of data frames. By "raw" I refer to data laid out in nine sub-tables, beginning with a meta-data section, followed by the PREPARATION phase, then SAMPLE phase, etc., concluding with the summary section.

siftr::read_sift("~/my_sift_data.csv")

Depending on the mode the SIFT runs in, the structure of its .csv can change. For example, the preparation phase may not be included. If this is the case, use the drop_prep argument.

siftr::read_sift("~/my_sift_data_batched.csv", drop_prep = T)

siftr also defaults to being very chatty, letting you know what it is doing to keep you updated and help debug any issues. If you want it to shut up, set the chatty argument to FALSE.

If you have multiple SIFT files and are only interested in one of the tables, you can use the read_many_sift function with a vector of file paths and a table (one of "time", "meta", "prep_phase", "sample_phase", "phase_mean_values", "intensity_corrected", "time_vs_mass", "concentrations", "analytes" or "summary", defaulting to "concentrations").

siftr::read_many_sift(my_files, table = "summary")

siftr::read_many_sift() can also be passed the drop_prep argument.

Pre-Processed SIFT data

Depending on the set-up of the SYFT, data output can be pre-processed into a more readable format with just three sub-tables; analyte concentrations, concentrations per reagents and concentrations per products. In this case, the function read_proc_sift can be used to quickly read these into R.

siftr::read_proc_sift("~/my_sift_lab_data.csv")

There is an equivalent function for reading a single table from multiple files. Once again, provide a vector of file paths and a table (one of "analyte_conc", "conc_per_reagent" or "conc_per_product", defaulting to "analyte_conc".)

siftr::read_many_proc_sift(my_files, table = "conc_per_product")