This package contains an implementation of the CGHnormaliter strategy for normalization of two-channel array Comparative Genomic Hybridization (aCGH) data displaying many copy number imbalances. The key idea of our method is that temporary exclusion of aberrations from the aCGH data allows for a more appropriate calculation of the LOWESS regression curve. As a result, after normalization, the l...

This package contains an implementation of the CGHnormaliter strategy for normalization of two-channel array Comparative Genomic Hybridization (aCGH) data displaying many copy number imbalances. The key idea of our method is that temporary exclusion of aberrations from the aCGH data allows for a more appropriate calculation of the LOWESS regression curve. As a result, after normalization, the l...

This package contains an implementation of the CGHnormaliter strategy for normalization of two-channel array Comparative Genomic Hybridization (aCGH) data displaying many copy number imbalances. The key idea of our method is that temporary exclusion of aberrations from the aCGH data allows for a more appropriate calculation of the LOWESS regression curve. As a result, after normalization, the l...

This package contains an implementation of the CGHnormaliter strategy for normalization of two-channel array Comparative Genomic Hybridization (aCGH) data displaying many copy number imbalances. The key idea of our method is that temporary exclusion of aberrations from the aCGH data allows for a more appropriate calculation of the LOWESS regression curve. As a result, after normalization, the l...

This package contains an implementation of the CGHnormaliter strategy for normalization of two-channel array Comparative Genomic Hybridization (aCGH) data displaying many copy number imbalances. The key idea of our method is that temporary exclusion of aberrations from the aCGH data allows for a more appropriate calculation of the LOWESS regression curve. As a result, after normalization, the l...

This package contains an implementation of the CGHnormaliter strategy for normalization of two-channel array Comparative Genomic Hybridization (aCGH) data displaying many copy number imbalances. The key idea of our method is that temporary exclusion of aberrations from the aCGH data allows for a more appropriate calculation of the LOWESS regression curve. As a result, after normalization, the l...

BACKGROUND Discharge destination after critical illness is increasingly recognized as a valuable patient-centered outcome. Recently, vitamin D status has been shown to be associated with important outcomes such as length of stay (LOS) and mortality in intensive care unit (ICU) patients. Our goal was to investigate whether vitamin D status on ICU admission is associated with discharge destinatio...

Epidemiological control of coronavirus disease 2019 (COVID-19) is needed to estimate the infection period confirmed cases and identify potential cases. The present study, targeting for which time COVID-19 symptom onset was disclosed, aimed investigate relationship between intervals (day) from testing cycle threshold (CT) values real-time reverse transcription-polymerase chain reaction. Of cases...

This package contains an implementation of the CGHnormaliter strategy for improved normalization of dual-channel array Comparative Genomic Hybridization (aCGH) data displaying many copy number imbalances. The key idea of our method is that temporary exclusion of aberrations from the data allows for a more appropriate calculation of the LOWESS regression curve. As a result, after normalization, ...

The least squares linear regression estimator is well-known to be highly sensitive to unusual observations in the data, and as a result many more robust estimators have been proposed as alternatives. One of the earliest proposals was least-sum of absolute deviations (LAD) regression, where the regression coefficients are estimated through minimization of the sum of the absolute values of the re...