Key | Value |
---|---|
FileName | ./usr/lib/R/site-library/multtest/Meta/links.rds |
FileSize | 898 |
MD5 | C47AA442E2E2D108DFE010E13E8CC8C9 |
SHA-1 | 7133B821BC32108EC39DDD64CF8483AA08917DCF |
SHA-256 | 47D1E8752489213D9DE057EA0495E96C4199EF59D1951C270BBB88DB389A98AD |
SSDEEP | 24:XE2D+ly+nzo4JtZ1OuR4Nca0OkAql7fNDk:XE2Yt3Rwxs7Nk |
TLSH | T1AC1196A24779D908C26DE6F411D7F36D6540E6EC07834099DB2A3A07F907D915E93067 |
hashlookup:parent-total | 9 |
hashlookup:trust | 95 |
The searched file hash is included in 9 parent files which include package known and seen by metalookup. A sample is included below:
Key | Value |
---|---|
FileSize | 841396 |
MD5 | 6E1FF693E612FCACD45F0B9ACB8E96AF |
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 | 397C7D8C52D7A24758F199E3188380409AA1D370 |
SHA-256 | 9A17D02F20F09EF761B9C5630F3FBE5DAFCFA7FF16A4B568E26766E68966596B |
Key | Value |
---|---|
FileSize | 847216 |
MD5 | 04B7E9498DFC4081929F297F963B76BB |
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 | E03953E42A0288C988FD4A1E0BB92614CB233F76 |
SHA-256 | 3EE89D533C69E300D32474D738CD131EBE06D889D93D4B50FEE61015556332AF |
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 | 842140 |
MD5 | 9FD27B1BE938032E42C509549EE6B64E |
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 | 594C5A87BE8D898C0B6D1AEFC5477F036CA18BFD |
SHA-256 | AFF410A20749C3BB8E3CF5ABEA2149E6B42E884886F27E7369E0B4C62D52BE01 |
Key | Value |
---|---|
FileSize | 839652 |
MD5 | 02F350C384A2C51F35202C479E3586B8 |
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 | 049020163976F814E7A69DF03F5CA2B63BA54154 |
SHA-256 | F6FC57B34F0B370BD2D42B7F7FDF4ED0294A17C6B9E10229A041B188ADD80F03 |
Key | Value |
---|---|
FileSize | 843020 |
MD5 | F5863BC872B8CEF7BAA18C32F7D149F8 |
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 | 8BB7F9805D4974651D3B0949CFB4A80202F88E43 |
SHA-256 | B166B8905063D1604B86664FC410534861A83A7BD074977D757762CA852BF1F8 |
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 | 843508 |
MD5 | 22B595CC17624C8C672DED09C6F6808E |
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 | 792A919C4FEB050A7FE2E40116D3C73F21D01D59 |
SHA-256 | 29E8FB46D21017052EB06CCE7B147C1CBA29ECC4EFD6347CEC5870F6EB623529 |
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 |