Key | Value |
---|---|
FileName | ./usr/lib/R/site-library/multtest/html/00Index.html |
FileSize | 8814 |
MD5 | 129FFBDACD77E285B000E3097CB0B8C7 |
SHA-1 | 5D3E3C77307B39DE26F8FF7F6E15F7377D3D5040 |
SHA-256 | C59A97E206AA92B4645F7F12D482F8060755BCE965697709556D9372D42C5696 |
SSDEEP | 96:1zix3K4Jks5M4jnzrFnzrcnzE5MuJi+ZFHonzrKnzrmnzrxnzr/nzr5nzrInzk5Z:Ix6+kkMgMouMlMdFF6GOMYg |
TLSH | T1E5026883E1D3563C0619436E86952DBD53A902E127626F80CF7BA8F7EB426F183212D7 |
hashlookup:parent-total | 10 |
hashlookup:trust | 100 |
The searched file hash is included in 10 parent files which include package known and seen by metalookup. A sample is included below:
Key | Value |
---|---|
FileSize | 838772 |
MD5 | 685AF2E68CE4B3FBC2FC2AF8C08FBCF6 |
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 | 2.46.0-1 |
SHA-1 | 57F7DF26C6E110785178D67736F8ED074CF4D1F0 |
SHA-256 | C224019E1FAC797DCBE7FD7BE8625C143EA9A6A69DB0412D113FC74CA18A00EB |
Key | Value |
---|---|
FileSize | 846432 |
MD5 | 9481ABE6B47F29ADCC531BFA13232421 |
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 | 2.46.0-1 |
SHA-1 | C7F45106FB171871883C025E20D5C66A14AB8002 |
SHA-256 | EAC8D7FFB085E50A0773E7677BDC197B0DD856C7B581AC6D27FAE8FD18B01EAF |
Key | Value |
---|---|
FileSize | 840380 |
MD5 | AC78883C4BEE4B263EC7B8727CF8FF45 |
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 | 2.46.0-1 |
SHA-1 | 13E6FDB6DF1A29022B80B19DFF95CC3920760B8C |
SHA-256 | 7FB108AE9C077A49FD5AE5A40A2FB47895D127CB1E17C04F39F7619C6C4170DF |
Key | Value |
---|---|
FileSize | 843460 |
MD5 | 6A33EE6E279313074B8C50D505E86E40 |
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 | 2.46.0-1 |
SHA-1 | F1BD027013A661CEF6FBF8BABF390BB6957CBE7A |
SHA-256 | BA413906BD844F8DD8F120CA7351602DF05B6CE2C00854217FCB9015EABB28C0 |
Key | Value |
---|---|
FileSize | 840968 |
MD5 | 0CCD30EE59F48C8019DB70CBEC867F0C |
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 | 2.46.0-1 |
SHA-1 | C2094277A1883CF737440BA2916AC8A4FCE1A859 |
SHA-256 | 8E5468537A1F3A92DB838BC6FE305728A222E56FF594D9E50EBC855A0D4A5BA1 |
Key | Value |
---|---|
FileSize | 841584 |
MD5 | F622478CA8478BC6AACD99939809B630 |
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 | 2.46.0-1 |
SHA-1 | 904B2322829C50BCF5237CDFCE1BCB104DA8E3F0 |
SHA-256 | A8D1CDBEFBB7CD9F649ED88A0ECA74A9C87EC4F18A5C6424A0ECD62AA513AE2C |
Key | Value |
---|---|
FileSize | 840636 |
MD5 | 6489FD54297DF1BE82530C17094667E1 |
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 | 2.46.0-1 |
SHA-1 | B115B08ACA51BD2D8628FE95720364CD82D35E31 |
SHA-256 | A0A3EA9266D9C893000FD773702157AC364EF96BA90226ACB202C9952F5B1BE3 |
Key | Value |
---|---|
FileSize | 842412 |
MD5 | 9C9DC67828A421D01A80232E3DC9B4E0 |
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 | 2.46.0-1 |
SHA-1 | CFECA2A6EBF091E018DCE3B0D5A62668FB897367 |
SHA-256 | C3473FFE434F39D99D57DD8294695E3F59F18E0C46964400701D97F30B669417 |
Key | Value |
---|---|
FileSize | 841328 |
MD5 | 22CF08E954CEB37ED98700670CE28002 |
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 | 2.46.0-1 |
SHA-1 | 4B7DAF7E0A9E5889F86C4DC130A25BD478B5C4E8 |
SHA-256 | 49E0505270C2E3CF0E5D26022E35957518C9B471DE03F79C91424F5C776908B6 |
Key | Value |
---|---|
FileSize | 841848 |
MD5 | F02AD7B98F04BD2D81B1EE764CEC95F2 |
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 | Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com> |
PackageName | r-bioc-multtest |
PackageSection | gnu-r |
PackageVersion | 2.46.0-1 |
SHA-1 | 00A65172403674A5F7B0BC54A6A49E74BEF36F9E |
SHA-256 | 171BA994859F47E7979CA26EE147A859B38A78EE8F71DFA6F06EE42AE8685FA3 |