562,344 research outputs found
MPAgenomics : An R package for multi-patients analysis of genomic markers
MPAgenomics, standing for multi-patients analysis (MPA) of genomic markers,
is an R-package devoted to: (i) efficient segmentation, and (ii) genomic marker
selection from multi-patient copy number and SNP data profiles. It provides
wrappers from commonly used packages to facilitate their repeated (sometimes
difficult) use, offering an easy-to-use pipeline for beginners in R. The
segmentation of successive multiple profiles (finding losses and gains) is
based on a new automatic choice of influential parameters since default ones
were misleading in the original packages. Considering multiple profiles in the
same time, MPAgenomics wraps efficient penalized regression methods to select
relevant markers associated with a given response
TRUFAS, a wavelet based algorithm for the rapid detection of planetary transits
Aims: We describe a fast, robust and automatic detection algorithm, TRUFAS,
and apply it to data that are being expected from the CoRoT mission. Methods:
The procedure proposed for the detection of planetary transits in light curves
works in two steps: 1) a continuous wavelet transformation of the detrended
light curve with posterior selection of the optimum scale for transit
detection, and 2) a period search in that selected wavelet transformation. The
detrending of the light curves are based on Fourier filtering or a discrete
wavelet transformation. TRUFAS requires the presence of at least 3 transit
events in the data. Results: The proposed algorithm is shown to identify
reliably and quickly the transits that had been included in a standard set of
999 light curves that simulate CoRoT data. Variations in the pre-processing of
the light curves and in the selection of the scale of the wavelet transform
have only little effect on TRUFAS' results. Conclusions: TRUFAS is a robust and
quick transit detection algorithm, especially well suited for the analysis of
very large volumes of data from space or ground-based experiments, with long
enough durations for the target-planets to produce multiple transit events.Comment: 9 pages, 10 figures, accepted by A&
An R package for determining groups in multiple survival curves
Survival analysis includes a wide variety of methods for analyzing time-to-event data. One basic but important goal in survival analysis is the comparison of survival curves between groups. Several nonparametric methods have been proposed in the literature to test for the equality of survival curves for censored data. When the null hypothesis of equality of curves is rejected, leading to the clear conclusion that at least one curve is different, it can be interesting to ascertain whether curves can be grouped or if all these curves are different from each other. We present the R clustcurv package which allows determining groups with an automatic selection of their number. The applicability of the proposed method is illustrated using real data
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