With 'satin' functions, visualisation, data extraction and further analysis like producing climatologies from several images, and anomalies of satellite derived ocean data can be easily done.  Reading functions can import a user defined geographical extent of data stored in netCDF files.  Currently supported ocean data sources include NASA's Oceancolor web page <https://oceancolor.gsfc.nasa.gov/>, sensors VIIRS-SNPP; MODIS-Terra; MODIS-Aqua; and SeaWiFS.  Available variables from this source includes chlorophyll concentration, sea surface temperature (SST), and several others.  Data sources specific for SST that can be imported too includes Pathfinder AVHRR <https://www.ncei.noaa.gov/products/avhrr-pathfinder-sst> and GHRSST <https://www.ghrsst.org/>.  In addition, ocean productivity data produced by Oregon State University can also be handled previous conversion from HDF4 to HDF5 format.  Many other ocean variables can be processed by importing netCDF data files from two European Union's Copernicus Marine Service databases <https://marine.copernicus.eu/>, namely Global Ocean Physical Reanalysis and Global Ocean Biogeochemistry Hindcast.

Given raster files directly downloaded from various websites,
    it generates a raster structure where it merges them if they are tiles
    of the same scene and classifies them according to their spectral and
    spatial resolution for easy access by name.

Performs mutational signature analysis for targeted sequenced tumors. Unlike the canonical analysis of mutational signatures, SATS factorizes the mutation counts matrix into a panel context matrix (measuring the size of the targeted sequenced genome for each tumor in the unit of million base pairs (Mb)), a signature profile matrix, and a signature activity matrix. SATS also calculates the expected number of mutations attributed by a signature, namely signature burden, for each targeted sequenced tumor. For more details see Lee et al. (2024) <doi:10.1101/2023.05.18.23290188>.

A metric expressing the quality of a UMAP layout. This is a
    package that contains the Saturn_coefficient() function that reads an
    input matrix, its dimensionality reduction produced by UMAP, and
    evaluates the quality of this dimensionality reduction by producing a
    real value in the [0; 1] interval. We call this real value Saturn
    coefficient. A higher value means better dimensionality reduction; a
    lower value means worse dimensionality reduction.
    Reference: Davide Chicco et al. "The Saturn coefficient for evaluating
    the quality of UMAP dimensionality reduction results" (2025, in preparation).