Title: Modeling Correlational Magnitude Transformations in
Description: Modeling the correlation transitions under specified distributional assumptions within the realm of discretization in the context of the latency and threshold concepts.
Imports: BinNonNor, BinOrdNonNor, GenOrd, moments, mvtnorm, psych
Packaged: 2016-07-19 21:33:05 UTC; rawanallozi

Packaged: 2016-07-21 16:49:59 UTC; rawanallozi

Packaged: 2016-09-29 16:41:14 UTC; rawanallozi

Packaged: 2017-01-25 18:24:30 UTC; rawanallozi

Packaged: 2017-03-28 15:39:18 UTC; rawanallozi

Packaged: 2018-01-10 15:23:26 UTC; rawanallozi

Author: Rawan Allozi, Hakan Demirtas, Ran Gao
Description: Modeling the correlation transitions under specified distributional assumptions within the realm of discretization in the context of the latency and threshold concepts. The details of the method are explained in Demirtas, H. and Vardar-Acar, C. (2017) <DOI:10.1007/978-981-10-3307-0_4>.

Title: Correct Overloaded Peaks from GC-APCI-MS Data
Authors@R: person("Jan", "Lisec", role = c("aut", "cre"), email = "jan.lisec@charite.de")
Description: Analyzes and modifies metabolomics raw data (generated using GC-APCI-MS, Gas Chromatography-Atmospheric Pressure Chemical Ionization-Mass Spectrometry) to correct overloaded signals, i.e. ion intensities exceeding detector saturation leading to a cut-off peak. Data in xcmsRaw format are accepted as input and mzXML files can be processed alternatively. Overloaded signals are detected automatically and modified using an Gaussian or Isotopic-Ratio approach, QC plots are generated and corrected data are stored within the original xcmsRaw or mzXML respectively to allow further processing.

Authors@R: person("Jan", "Lisec", role = c("aut", "cre"), email = "jan.lisec@bam.de")

Author: Abbas Rahal, Anna Akpawu, Justin Chitpin and David R. Bickel
Description: There are many estimators of false discovery rate. In this package we compute the Nonlocal False
Discovery Rate (NFDR) and the estimators of local false discovery rate: Corrected False discovery
Rate (CFDR), Re-ranked False Discovery rate (RFDR) and the blended estimator.