tag:crantastic.org,2005:/authors/423Latest activity for Katherine S. Pollard2011-04-26T19:30:48Zcrantastic.orgtag:crantastic.org,2005:TimelineEvent/144372011-07-09T18:17:39Z2011-07-09T18:17:39Zkrisrs1128 uses multtest<a href="/users/698">krisrs1128</a> <span class="action">uses</span> <a href="/packages/multtest">multtest</a>krisrs1128tag:crantastic.org,2005:TimelineEvent/131982011-04-26T19:30:48Z2011-04-26T19:30:48Zmulttest was upgraded to version 2.8.0<a href="/packages/multtest">multtest</a> was <span class="action">upgraded</span> to version <a href="/packages/multtest/versions/12081">2.8.0</a><br /><h3>Package description:</h3><p>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.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/131942011-04-26T19:30:36Z2011-04-26T19:30:36Zhopach was upgraded to version 2.12.0<a href="/packages/hopach">hopach</a> was <span class="action">upgraded</span> to version <a href="/packages/hopach/versions/12077">2.12.0</a><br /><h3>Package description:</h3><p>The HOPACH clustering algorithm builds a hierarchical tree of clusters by recursively partitioning a data set, while ordering and possibly collapsing clusters at each level. The algorithm uses the Mean/Median Split Silhouette (MSS) criteria to identify the level of the tree with maximally homogeneous clusters. It also runs the tree down to produce a final ordered list of the elements. The non-parametric bootstrap allows one to estimate the probability that each element belongs to each cluster (fuzzy clustering).</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/112502011-02-03T09:10:21Z2011-02-03T09:10:21Zmulttest was upgraded to version 2.7.1<a href="/packages/multtest">multtest</a> was <span class="action">upgraded</span> to version <a href="/packages/multtest/versions/10518">2.7.1</a><br /><h3>Package description:</h3><p>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.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/95512010-10-27T11:20:59Z2010-10-27T11:20:59Zmulttest was upgraded to version 2.6.0<a href="/packages/multtest">multtest</a> was <span class="action">upgraded</span> to version <a href="/packages/multtest/versions/9299">2.6.0</a><br /><h3>Package description:</h3><p>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.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/95332010-10-27T11:20:23Z2010-10-27T11:20:23Zhopach was upgraded to version 2.10.0<a href="/packages/hopach">hopach</a> was <span class="action">upgraded</span> to version <a href="/packages/hopach/versions/9281">2.10.0</a><br /><h3>Package description:</h3><p>The HOPACH clustering algorithm builds a hierarchical tree of clusters by recursively partitioning a data set, while ordering and possibly collapsing clusters at each level. The algorithm uses the Mean/Median Split Silhouette (MSS) criteria to identify the level of the tree with maximally homogeneous clusters. It also runs the tree down to produce a final ordered list of the elements. The non-parametric bootstrap allows one to estimate the probability that each element belongs to each cluster (fuzzy clustering).</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/79472010-07-30T05:22:36Z2010-07-30T05:22:36Zmulttest was upgraded to version 2.5.14<a href="/packages/multtest">multtest</a> was <span class="action">upgraded</span> to version <a href="/packages/multtest/versions/8278">2.5.14</a><br /><h3>Package description:</h3><p>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.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/73322010-07-16T10:47:47Z2010-07-16T10:47:47Zmulttest was upgraded to version 2.4.0<a href="/packages/multtest">multtest</a> was <span class="action">upgraded</span> to version <a href="/packages/multtest/versions/7780">2.4.0</a><br /><h3>Package description:</h3><p>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.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/72222010-07-16T10:42:01Z2010-07-16T10:42:01Zhopach was upgraded to version 2.9.1<a href="/packages/hopach">hopach</a> was <span class="action">upgraded</span> to version <a href="/packages/hopach/versions/7670">2.9.1</a><br /><h3>Package description:</h3><p>The HOPACH clustering algorithm builds a hierarchical tree of clusters by recursively partitioning a data set, while ordering and possibly collapsing clusters at each level. The algorithm uses the Mean/Median Split Silhouette (MSS) criteria to identify the level of the tree with maximally homogeneous clusters. It also runs the tree down to produce a final ordered list of the elements. The non-parametric bootstrap allows one to estimate the probability that each element belongs to each cluster (fuzzy clustering).</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/58042010-05-01T13:11:56Z2010-05-01T13:11:56Zhopach was upgraded to version 2.8.0<a href="/packages/hopach">hopach</a> was <span class="action">upgraded</span> to version <a href="/packages/hopach/versions/7284">2.8.0</a><br /><h3>Package description:</h3><p>The HOPACH clustering algorithm builds a hierarchical tree of clusters by recursively partitioning a data set, while ordering and possibly collapsing clusters at each level. The algorithm uses the Mean/Median Split Silhouette (MSS) criteria to identify the level of the tree with maximally homogeneous clusters. It also runs the tree down to produce a final ordered list of the elements. The non-parametric bootstrap allows one to estimate the probability that each element belongs to each cluster (fuzzy clustering).</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/36092010-01-05T10:13:24Z2010-01-05T10:13:24Zhopach was upgraded to version 2.7.1<a href="/packages/hopach">hopach</a> was <span class="action">upgraded</span> to version <a href="/packages/hopach/versions/6215">2.7.1</a><br /><h3>Package description:</h3><p>The HOPACH clustering algorithm builds a hierarchical tree of clusters by recursively partitioning a data set, while ordering and possibly collapsing clusters at each level. The algorithm uses the Mean/Median Split Silhouette (MSS) criteria to identify the level of the tree with maximally homogeneous clusters. It also runs the tree down to produce a final ordered list of the elements. The non-parametric bootstrap allows one to estimate the probability that each element belongs to each cluster (fuzzy clustering).</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/28812009-11-13T11:14:13Z2009-11-13T11:14:13Zmulttest was upgraded to version 2.2.0<a href="/packages/multtest">multtest</a> was <span class="action">upgraded</span> to version <a href="/packages/multtest/versions/5668">2.2.0</a><br /><h3>Package description:</h3><p>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.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/28762009-11-13T11:13:15Z2009-11-13T11:13:15Zhopach was upgraded to version 2.6.0<a href="/packages/hopach">hopach</a> was <span class="action">upgraded</span> to version <a href="/packages/hopach/versions/5663">2.6.0</a><br /><h3>Package description:</h3><p>The HOPACH clustering algorithm builds a hierarchical tree of clusters by recursively partitioning a data set, while ordering and possibly collapsing clusters at each level. The algorithm uses the Mean/Median Split Silhouette (MSS) criteria to identify the level of the tree with maximally homogeneous clusters. It also runs the tree down to produce a final ordered list of the elements. The non-parametric bootstrap allows one to estimate the probability that each element belongs to each cluster (fuzzy clustering).</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/24442009-10-22T19:13:02Z2009-10-22T19:13:02Zmulttest was upgraded to version 2.1.3<a href="/packages/multtest">multtest</a> was <span class="action">upgraded</span> to version <a href="/packages/multtest/versions/5329">2.1.3</a><br /><h3>Package description:</h3><p>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.</p>crantastic.org