Analytics to read in and segment raw 'GENEActiv' accelerometer data into epochs and events.
    For more details on the 'GENEActiv' device, see <https://activinsights.com/resources/geneactiv-support-1-2/>.

Functions and analytics for GENEA-compatible accelerometer data into R objects. 
             See topic 'GENEAread' for an introduction to the package. 
             See <https://activinsights.com/technology/geneactiv/> for more details on the GENEActiv device.

The GeneCycle package implements the approaches of Wichert
        et al. (2004) <doi:10.1093/bioinformatics/btg364>, Ahdesmaki 
        et al. (2005) <doi:10.1186/1471-2105-6-117> and Ahdesmaki et al.
        (2007) <DOI:10.1186/1471-2105-8-233> for detecting periodically 
        expressed genes from gene expression time series data.

A function that reads in the GEO code of a gene expression dataset, retrieves its data from GEO, (optionally) retrieves the gene symbols of the dataset, and returns a simple dataframe table containing all the data. Platforms available: GPL11532, GPL23126, GPL6244, GPL8300, GPL80, GPL96, GPL570, GPL571, GPL20115, GPL1293,  GPL6102, GPL6104, GPL6883, GPL6884, GPL13497, GPL14550, GPL17077, GPL6480. GEO: Gene Expression Omnibus. ID: identifier code. The GEO datasets are downloaded from the URL <https://ftp.ncbi.nlm.nih.gov/geo/series/>. More information can be found in the following manuscript: Davide Chicco, "geneExpressionFromGEO: an R package to facilitate data reading from Gene Expression Omnibus (GEO)". Microarray Data Analysis, Methods in Molecular Biology, volume 2401, chapter 12, pages 187-194, Springer Protocols, 2021, <doi:10.1007/978-1-0716-1839-4_12>.

Implementation of several generalized F-statistics. The
    current version includes a generalized F-statistic based on the
    flexible isotonic/monotonic regression or order restricted hypothesis
    testing. Based on: Y. Lai (2011) <doi:10.1371/journal.pone.0019754>.

A pipeline with high specificity and sensitivity in extracting 
  proteins from the RefSeq database (National Center for Biotechnology 
  Information). Manual identification of gene families is highly 
  time-consuming and laborious, requiring an iterative process of manual and 
  computational analysis to identify members of a given family. The pipelines 
  implements an automatic approach for the identification of gene families 
  based on the conserved domains that specifically define that family. See 
  Die et al. (2018) <doi:10.1101/436659> for more information and examples.