Parents (Total: 3)

The searched file hash is included in 3 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
FileSize	841560
MD5	1DB1B4456745B05E66819A15DD48BFE4
PackageDescription	Bioconductor resampling-based multiple hypothesis testing Non-parametric bootstrap and permutation resampling-based multiple testing procedures (including empirical Bayes methods) for controlling the family-wise error rate (FWER), generalized family-wise error rate (gFWER), tail probability of the proportion of false positives (TPPFP), and false discovery rate (FDR). Several choices of bootstrap-based null distribution are implemented (centered, centered and scaled, quantile-transformed). Single-step and step-wise methods are available. Tests based on a variety of t- and F-statistics (including t-statistics based on regression parameters from linear and survival models as well as those based on correlation parameters) are included. When probing hypotheses with t-statistics, users may also select a potentially faster null distribution which is multivariate normal with mean zero and variance covariance matrix derived from the vector influence function. Results are reported in terms of adjusted p-values, confidence regions and test statistic cutoffs. The procedures are directly applicable to identifying differentially expressed genes in DNA microarray experiments.
PackageMaintainer	Debian R Packages Maintainers <r-pkg-team@alioth-lists.debian.net>
PackageName	r-bioc-multtest
PackageSection	gnu-r
PackageVersion	2.48.0-1
SHA-1	C1506112846289AD257B474197D2601B1270C457
SHA-256	61D866F9CBF1A1D327354F85643CB24ABDCC0F4D249CD085C8FDC75F270C6D85

Key	Value
FileSize	842644
MD5	D98FB0100604F07D73044BCFAB882EFF
PackageDescription	Bioconductor resampling-based multiple hypothesis testing Non-parametric bootstrap and permutation resampling-based multiple testing procedures (including empirical Bayes methods) for controlling the family-wise error rate (FWER), generalized family-wise error rate (gFWER), tail probability of the proportion of false positives (TPPFP), and false discovery rate (FDR). Several choices of bootstrap-based null distribution are implemented (centered, centered and scaled, quantile-transformed). Single-step and step-wise methods are available. Tests based on a variety of t- and F-statistics (including t-statistics based on regression parameters from linear and survival models as well as those based on correlation parameters) are included. When probing hypotheses with t-statistics, users may also select a potentially faster null distribution which is multivariate normal with mean zero and variance covariance matrix derived from the vector influence function. Results are reported in terms of adjusted p-values, confidence regions and test statistic cutoffs. The procedures are directly applicable to identifying differentially expressed genes in DNA microarray experiments.
PackageMaintainer	Debian R Packages Maintainers <r-pkg-team@alioth-lists.debian.net>
PackageName	r-bioc-multtest
PackageSection	gnu-r
PackageVersion	2.48.0-1
SHA-1	90E3748FE83539CEDB15A654B40FBEAB7B6ABC79
SHA-256	5FF3F0D049CF4E6F3F06435047A5D97BA03E8CFABE402205B255159DBC81138C

Key	Value
FileSize	841148
MD5	2FDAB6360B4D175868D73F707B7E5447
PackageDescription	Bioconductor resampling-based multiple hypothesis testing Non-parametric bootstrap and permutation resampling-based multiple testing procedures (including empirical Bayes methods) for controlling the family-wise error rate (FWER), generalized family-wise error rate (gFWER), tail probability of the proportion of false positives (TPPFP), and false discovery rate (FDR). Several choices of bootstrap-based null distribution are implemented (centered, centered and scaled, quantile-transformed). Single-step and step-wise methods are available. Tests based on a variety of t- and F-statistics (including t-statistics based on regression parameters from linear and survival models as well as those based on correlation parameters) are included. When probing hypotheses with t-statistics, users may also select a potentially faster null distribution which is multivariate normal with mean zero and variance covariance matrix derived from the vector influence function. Results are reported in terms of adjusted p-values, confidence regions and test statistic cutoffs. The procedures are directly applicable to identifying differentially expressed genes in DNA microarray experiments.
PackageMaintainer	Debian R Packages Maintainers <r-pkg-team@alioth-lists.debian.net>
PackageName	r-bioc-multtest
PackageSection	gnu-r
PackageVersion	2.48.0-1
SHA-1	E6671BCD0617196B956B362D5E4AB1189BEFD523
SHA-256	C0A13577005202720E240374D8F23F4C25C0A89F6FD94E6E167D34E67A612C9B