New rotating 3-D interactive plot of samples. Axes are user selected Biocarta/Kegg pathways, gene lists or individual gene symbols. This 3-D plot can now be saved and launched in MS PowerPoint.
Re-organized the code related to importing. In this version, averaging replicate spots, background subtraction and common reference design are now part of the filtering options. The importing of Affymetrix multi-chip sets is not supported in this version.
Affymetrix .CEL files
Custom Chip Definition Files (CDF) from the University of Michigan can be used when importing .CEL files.
Additional support has been added to SOURCE annotations for Agilent, Affymetrix and Illumina data.
For single channel data two new methods have been added. The quantile normalization method and an option to normalize each array based on a specified percentile and target intensity.
Lassoed logistic regression plug-in:
This plug-in implements Friedman et al (2008)’s method to fit a logistic regression model to predict a binary class variable using gene expression values and optional standard clinical covariates. It uses a L1 penalized maximum likelihood method and performs complete cross-validation evaluating prediction accuracy of genomic model to clinical model to combined model.
Added an option to scale for single channel data in clustering of genes and samples.
This version of the software will now launch 64-bit version of R in batch mode if it is available for importing and many of the analysis tools.
Importing and annotations:
1: Class Prediction: Fixed an indexing error in the HTML output table for the prediction of new samples in cases where the true class labels were available.
2: Mixed Effects ANOVA: Now allows a total of 4 fixed effects to be used in the model.
3: For paired analysis, the output heatmaps are now produced.
4: The gene set analyses handles recent changes made on the BROAD institute's gene signature databases.
5: Fixed an error when no genes were found in survival risk prediction.
6: The global test option for MDS now runs.
7: GEO importer now handles an additional data type called expression profiling by arrays.
8: Users are now permitted to use non-integer values for the spot size filter.
9: Corrected the code to read array ids with trailing spaces for median normalization in single channel data.
10: Enhanced the dialog in the extract gene expression data plug-in.
11: Fixed an annotation error when the user annotates the project with their own gene ids. The code has been modified to successfully run SOURCE annotations when the project was saved on a different drive than where ArrayTools was installed.
12: Modified the code to support the ArrayTools automatic updating for VISTA and Windows 7 users.
Should you have any problems with automatically updating to v4.1-Beta_3, we recommend that you download the either the FULL or individual installers from /BRB-ArrayTools.html
1. Added a new option to filter genes for single channel based on minimum intensity.
2: Enhanced the 2-D and 3-D scatter plot tools.
3: Fixed a critical error in ST Array importer that affected the normalized log intensity values.
4: Re-compiled the Fortran program for almostRMA to fix a dll problem for windows 7 users.
5: Added gene names to the heatmap zoom/recolor option in clustering.
6: Fixed a time series error that occurred in the heatmap when there was only one array per time point.
7: Fixed a minor error in the RVM when the variance for a give gene was zero.
8: Fixed an error in Affy. cel file importer for the MAS5.0 option, to correctly run the detection call filter in spot filtering.
1. New 2-D and rotating 3-D interactive scatterplot tools have been implemented with a variety of features like multi panels, linking plots, highlighting genes based on pathways etc. To view the enhanced graphics, here is a link to the online demo /PowerPointSlides/Scatterplot.wmv
2. Heatmaps: The clustering heatmaps have been re-designed to handle more genes and arrays. The images have been enhanced with rectangular pixels and class labels have been added. The color palette for the analysis related heatmaps can now be modified.
1. Gene Set Expression Analysis: An optional interaction analysis has been added to find gene sets for which the inter-class differential expression varies among pre-defined groups of samples.
2. Another new feature is the inclusion of gene sets based on lymphoid signatures from the Staudt lab( http://lymphochip.nih.gov/signaturedb/ ). We have also updated all the existing gene sets within ArrayTools.
3. Class comparison: The pair-wise option now permits more than two class levels.
4. Lassoed Principal Components plug-in: We have implemented Witten and Tibshirani�s new method for identifying genes whose expression varies among classes, is correlated with a quantitative trait or is correlated with survival time.
5. Adaboost plug-in: A tool for class prediction using the Adaboost method developed by Freund and Schapire (1996) has been implemented as a plug-in. Classification is based on weighted voting of a set of classification trees.
1. Affymetrix Gene ST Array Importer; A platform specific data importer is provided for human, mouse and rat Gene ST 1.0 arrays.
2. GenePix importer: The data import wizard can now handle single channel GenePix data.
3. Custom Annotations: This release permits import of user supplied gene annotations for custom species/arrays.
4. Annotations: SOURCE annotations can now be imported for 8 different organisms.
An option is provided for selecting a single probe/probe set for each gene represented on the array.
1. A new utility is provided that obtains drug bank information for all genes in a gene list produced by any BRB-ArrayTools analysis. This provides drugs whose targets include protein products of genes on the specified list.
2. Genelists are now created for both positive and negative correlations to a specific gene.
3. The user can now control the heatmap plot options from the preferences option under utilities.
1. The HaarSeg algorithm is provide as an alternative and faster segmentation method. All segmentation is now performed by loading one sample at a time to improve memory handling for large data sets.
2. Pathway enrichment analysis can now be performed for mouse as well as human arrays. Support for rat and mouse arrays in GISTIC analysis and in integrated analysis between copy number and expression is now provided.
3. The identification of frequent copy number aberrations can now run on either arrays of a specified class or on all the arrays.
4. The general importer can now import individual red and green intensities and compute the corresponding log2ratios.
1. Gene-set comparison tool: We fixed an indexing error in the Fortran program related to using the Random Variance Model option.
2. Handling redundant probes within gene set comparison tool: An indexing error has been fixed when the redundant probe option was selected. Also, the Random variance model now uses a filtered list of genes as opposed to the reduced list of genes based on redundant probes.
3. Data Import Wizard: The code has now been modified to correctly read the spot flag string for the Agilent importer.
4. Gene lists: Modified the gene list files that were included as part of the distribution to remove corrupted files in the transcription factor and PFAM protein domain gene sets for mouse.
5. Class comparison: We fixed a problem related to the parallel coordinate plots in specific data sets with missing values where a blocking factor was specified.
6. Fixed a bug in the survival analysis to now display the survival curve when the expression data falls into one group.
7. Quantitative Trait Analysis: When requested the HTML output now shows the permutation p-values.
8. ANOVA plug-in log intensities: The HTML output now displays the geometric means.
9. Annotations: We added support for annotating genes for Xenopus laevis, Xenopus tropicalis.
1: In this version, the genome build information is accurately saved when the user selects to specify a chromosome file at the data import step.
Changes and Bug Fixes since Last 3.8.0 Beta 1 Version:
1. Fixed the bug related to HTML error caused when Gene ontology observed vs expected analysis for class comparison was selected. The Fortran code has been corrected to handle an indexing problem. Also, fixed an error in the Volcano plot that occurred in some instances when the Fortran program wasn't completed but the plot was launched. The code has been modified to appropriately handle the situation when fold change option was selected with univariate permutation. The fold change option is not permitted when the blocking variable is selected.
2. Gene Set Comparison: Modified the code so that the ArrayTools path is no longer hard coded and also adjusted the heatmap plot dimensions.
3. Modified the code for Gene set comparison to display the results when the GSA package failed due to the limit of a total of 110 unique genes.
4. Survival analysis: The code has been modified for the case when no genes were found significant. Corrected the gene list file created from survival analysis.
5. Modified the R code in different tools, to handle the appropriate messages that were previously displayed using the windialog() function. The R code has also been modified to handle the latest impute package developed under Rv2.9.0
6. BROAD web server: Modified the code to use the http link instead of the ftp link based on changes made by the Broad institute.
7. SAM: Modified the Fortran code to handle the situation when the data had too many missing values then the corresponding CDF for the F distribution had negative values. Also, the HTML output has been modified to represent a consistent plot for the positive and negative significant genes.
8. Modified the LARS plug in to use a different random seed. The HTML output has been enhanced to include a table of actual and predicted responses used in the scatter plot. The formula for predicting a new sample has been corrected.
9. Illumina importer: The software now correctly reads files with the underscore character and can import ENTREZ ID as well. The code has been modified to import Target ID when Probe ID is not available.
10. Modified the code for SOURCE annotation to allow users to select ENTREZ ID as one of the identifier to download the annotations.
11. Fixed an erroneous option in the gene identifiers import dialog.
12. Housekeeping gene normalization: Fixed an error in data sets with > 65k rows. Also, maximum number of housekeeping genes in the genelist file has been modified to be larger than 3000 rows.
13. The cancel button when creating the project workbook or now cleans up the appropriate files.
14. Modified the VBA code to use http instead of ftp for updating ArrayTools from the linus server.
1. Fixed a bug caused when the sample ids had numeric values.
2. Made minor changes in the code to appropriately prompt the user to open a CGH project on clicking different menu options.
3. Added information to the HTML on the gain and loss thresholds used Pathway, GISTIC and correlation analysis.
The new release introduces many new features including additional analyses tools for the analysis of array Comparative Genomic Hybridization data.
3. Enhanced class comparison: The output of class comparison between groups of arrays includes a heat map of the significant genes as well volcano plots (for 2 class levels)/parallel coordinate plots (more than 2 class levels). An option to restrict the genes by Fold threshold is also implemented.
4. Gene Set Comparison: Added an option to handle redundant probes that correspond to the same gene. Enhanced the output to provide heat maps for the significant gene sets.
5. Time course analysis: Enhanced the output by providing a heat map for significant genes.
6. NMF plug-in: A new clustering method using non negative matrix factorization method has been included as a plug-in tool in this release.
7. Least Angle Regression (LARS): Implemented a new tool for prediction of a continuous response variable.
8. Utility: Added an option to automatically download packages from CRAN/Bioconductor that are needed for analysis. This will permit the user to perform various analyses even when not connected to the internet.
9. Importer: Added an option to import and normalize Illumina data using the 'lumi' package.
10. This version has the capability to download annotations for additional species from Bioconductor.
11. The ANOVA plug-in has been modified such that Table 2 for the fixed and mixed effects model has been removed to simplify the output.
12. Modified the installer so as not to register the shdocvw.dll
13. Fixed a VBA inconsistency when picking the median array for even number of arrays to always pick the left array.
1. Added an option to import inferred copy number data using the general importer.
2. Individual HTML outputs are generated for Segmentation and gain/loss analysis in this release.
3. Gain/Loss Analysis: Added options for user to determine gain and loss based on arbitrary segmentation log ratios or the MAD factor multiplied by the segmentation mean log ratios as well enhanced the output by adding frequency plots.
4. Implemented the GISTIC tool to systemically identify regions with frequent and significant copy number aberration.
5. Capability to assign summarized values on unique gene symbols for each array based on the inferred integer copy numbers or segmentation data.
6. Implemented a pathway enrichment analysis tool using this gene data.
7. Added an option to create an expression project( BRB-ArrayTools project) from the gene data such that further expression analyses can be performed using ArrayTools.
8. Added a feature to integrate gene expression project data with CGH data by performing a correlation analysis.
Version 3.7.0 stable release contains the following bug fixes and improvements:
1. Fixed a run time error in the 'zoom and re-color' button for clustering of genes and samples.
2. Fixed an error in single channel normalization using median across groups of arrays.
3. The utility to download a genelist to a file now works for scatterplot experiment vs experiment tool.
4. Corrected the redundant message that appeared when Lowess normalization is selected.
5. Updated the code for source annotation, as SOURCE has now replaced locuslink Id with geneID.
6. Modified the Fortran code for class comparison to use 100,000 as the number of permutations in the approximation method. The HTML output now correctly reflects p-value < .00001 instead of <.0000001 if the permutation p-value is zero.
7. Modified code to run annotations on yeast and download corresponding Gene ontology data using the Bioconductor packages.
8. Fixed an error in the quantitative trait analysis tool that only happened if there was a perfect correlation among some of the genes.
9. Fixed an error in the Fortran code of the class comparison tool that occurred in certain data sets. The program failed for the randomized block design when there was missing data.
10. Fixed an error in cluster that was caused when the worksheet name was not appropriately updated.
11. For Affymetrix data, expanded the option to also allow importing separate annotation files.
12. Modified the R code so as to be compatible with latest Rv2.8.0 release and Bioconductor v2.3.
The new release introduces many new features including a first version of CGHTools for the analysis of array Comparative Genomic Hybridization data.
1. ANOVA plug-in on log intensities: Added an option for evaluating pairwise contrasts. 2. A Plugin for planning the number of arrays needed for identifying genes differentially expressed between 2 classes 3. Gene Set Comparison: Added Efron-Tibshirani's GSA maxmean test and Goeman's global test. The structure of the HTML output is simplified to give a comparison of results for all tests. The Hotelling test was dropped. 4. BROAD gene set Updated access to the Broad Institute Molecular Signature Database (MSigDB) including positional, curated, motif, and computed gene sets. Added 'rat' and mouse species for the curated gene sets group. 5. Class prediction Added a cross-validated ROC curve to the HTML output for the Bayesian compound covariate predictor. 6. ScatterPlot: Added a button to export the genelist. Also, modified the name of the scatterplot for phenotype averages to reflect the class variable. 7. Clustering: Heatmap Enhanced the heatmap to provide a color gradient option that the user can select from a color pallet. Also, modified the heatmap zoom-in feature to allow the user to specify the gene identifier to be displayed. 8. Normalization for Single Channel: Modified the code to allow the user to normalize the data by groups of arrays. 9. GO download: Modified the code to obtain the Gene Ontology files from Bioconductor. 10. Affymetrix annotations: Modified the code to download the Affy annotations from Bioconductor. 11. DrugBank Link: Added to the "info" link in the HTML output, a link to query using gene symbol. 12. Updated the import wizard: The automatic importers for Affy, Agilent, Genepix and mAdb can now be accessed using the data import wizard.
Version 3.6.0 stable release contains the following bug fixes and improvements:
1) Class Prediction: Fixed a bug in the class prediction output where the t-statistic column had 1e-07 values instead of negative values. Also, for the CCP and DLDA prediction methods modified the code to handle missing values when computing the weights and threshold.
2) Random Variance Model: Increased the limit on the number of genes to 500K as well as increased the corresponding stack size.
3) Quantitative Trait analysis: Fixed a bug where the HTML output showed 1e-07 instead of negative values for correlation coefficients.
4) Zoom and recolor clustering: Previously, the user specified class column to label the experiments was not displayed but this has been fixed in this release.
5) Survival gene set comparison: Fixed an error that was caused when incorrectly loading the default parameter file.
6) Modified the gene index in the Fortran code to handle more than 9 digits in various analyses.
7) Survival Risk Prediction: Modified the tool for the special case when no genes are selected in the combined model such that when cross-validating the model the gene with the smallest p-value together with clinical covariates will be used in the Cox regression and prediction.
1) The system architecture has been modified in this version of BRB-Arraytools to handle more than the Excel limit of 65,000 rows. The gene identifier and gene annotation information in now stored binary files.
2) This version of BRB-ArrayTools is compatible with MS Vista and Excel 2003.
3) Data Import
GEO importer: This tool allows users to automatically import a GDS dataset from the NCBI Gene Expression Omnibus (GEO) database into BRB-ArrayTools.
Agilent importer: The data import wizard now automatically recognizes the format for dual channel Agilent data and directly imports the background subtracted intensities and annotations.
Affymetrix .CEL files: (i) For large number of .CEL files (greater than 100), to avoid memory problems, we have implemented a new method called 'almostRMA'. This method uses a subset of arrays to compute the quantile normalization and probe effects model and then applies these to all the arrays in the data set. (ii) A new option to compute MAS5.0 probe set summaries from .CEL files has been included.
4) Analysis Tools:
Gene Set Expression Comparison: We created two new families of gene sets that can be used within the Gene Set Expression Comparison tool. One family contains the set of genes that are targets of a transcription factor; one set for each TF, with the option to use experimentally verified targets or computationally determined putative targets. The second family contains a set of computationally determined putative targets for each microRNA.
Survival Gene set Expression Analysis: This analysis tool finds sets of genes for which the expression levels are correlated to survival. Similar to the Gene Set Expression comparison tool, this tool can be used to analyze Gene Ontology categories, Pathways, micro RNA targets, transcription factor targets and user defined gene lists.
Enhanced plug-in ANOVA of log intensities: This enhanced plug-in replaces the Class comparison tool between Red and Green channels. The plug-in is used for finding genes differentially expressed between two classes for two-color arrays without a common reference sample. It can also be used to compare samples of one class with the reference samples in the common reference design.
Class Prediction: We have implemented a new option for gene selection based on recursive feature elimination. The user specifies the number of genes to include. Starting with a full model the method excludes genes whose correlation with outcome is minimal. This reduction continues until the target number of genes is reached. The recursive feature elimination is applied from scratch within each cross-validated training set. Although recursive feature elimination is based on a support vector machine model, any type of classifier can be used for the genes selected for the training set.
Bayesian compound covariate predictor: We added an option of not predicting any class if the greatest posterior probability does not exceed a user-specified threshold. The HTML output now also displays the predicted probability.
5) We provide a new utility to create and save for further analysis a list of genes that are correlated to a user-specified gene based on a user-specified threshold.
6) We modified the format of the genelists that get generated from an analysis tool to include gene annotation information whenever available. This facilitates use of such gene lists with data from different projects or with different platforms.
7) This version has the capability to simultaneously run more than one analysis tool within a project.
Version 3.5.0 stable release contains the following bug fixes and improvements:
1) Gene Set Expression Comparison: Fixed a bug that occurred when the Random Variance Model option was selected; it was not used in the analysis of GO categories and Pathways.
2) False Discovery Rate(FDR): The False discovery rate reported in the HTML output has been corrected. The magnitude of difference to the previously reported FDR values appears small (e.g 10^(-2)).
3) Broad/MIT Pathways: Modified the code to accommodate for the changes made on the Broad/MIT web page. Enhanced the HTML output by providing hyper-links for some of the gene sets.
What's New in BRB-ArrayTools Version 3.5 � Beta Release
1) Data Import Wizard
We have added a new data import wizard to assist users through the process of importing their data into BRB-ArrayTools.
In this version, the GC-RMA method for computing probe set summaries from .CEL files has been implemented.
3) Analysis Wizard
An analysis wizard has been added to guide users with selecting the appropriate analysis tool based on their research question and experimental design.
4) Survival Risk Prediction
We have enhanced the Survival Risk Prediction tool to allow up to 3 risk groups and 3 clinical covariates.
5) Class Prediction
A new method called the 'Bayesian Compound Covariate predictor' has been included for two classes. The Top Scoring Pair class prediction plug-in has been extended to use multiple pairs of 'synergistic' genes. Additionally, for the greedy pairs option we have enhanced the output to include the gene pair information.
6) 0.632+ bootstrap Cross-validation
The 0.632+ bootstrap method of cross validation replaces the 0.632 method for estimating prediction error.
7) Gene Set Expression Comparison
An additional test called the Hotelling's T square test, has been implemented for finding significant gene sets.
8) Affymetric Quality Control Plots for .CEL files
We have added a utility to provide quality control plots and RNA degradation plots for projects imported using Affymetrix CEL files.
We have improved the color scale for the heatmap in BRB-ArrayTools. We have also added an option to median center single channel data when using the Cluster 3.0/Treeview tools.
Added a preference menu option to allow users to modify certain preference parameters for BRB-ArrayTools.
11) Log File
A new log file has been added which records the parameter options used at the time of importing the data and performing an analysis.
12) Mac Users
This version has been successfully tested with Windows XP professional running on Apple macbook pro machine. The windows XP professional was installed with Apple's bootcamp software.
Version 3.4.0 stable release contains the following bug fixes and improvements:
1) Random Variance Model: Modified the code to handle missing values consistently in various tools.
2) Time Series Plug-in: Modified the code to pass the 'time' variable as a numeric instead of a factor.
3) Class Prediction: Fixed the SVM error message when the optimization process did not end.
4) Quantitative Trait: Corrected the HTML output by removing Global test p-value from the HTML output.
5) Horizontally aligned file format: Fixed the run time error caused due to long header lines.
6) Click to display: Fixed an error on the "Filtered log ratio/intensity" worksheet to use a numeric sort.
7) Non-English Language Users: Implemented a fix for non-English language users
What's New in BRB-ArrayTools Version 3.4 Beta Release
1) Re-designed the architecture of BRB-ArrayTools so that there is no longer any restriction on the number of arrays that a project can contain.
2) Survival Risk Group Prediction
3) Gene Set Expression Comparison Using Broad/Whitehead Signatures and Pathways
4) Create User Defined Gene List Based on GO Terms
5) Top Scoring Pairs Class Prediction
6) BRB-ArrayTools Archive of Human Tumor Projects
7) Improvement of User Dialogs
Version 3.3.0 Stable Release contains the following bug fixes:
1) Added an option for background adjustment,fixed bug for reverse fluor in GenePix Importer.
2) Fixed the bug using CGAP,Biocarta and KEGG pathways in Gene Subset.
3) Fixed the bug in print-tip Lowess normalization,using housekeeping genes for single channel.
4) Class Prediction: Progress bar now works when permutation test option is selected. Also, corrected the expression data table in HTML output.
5) PAM: Added a warning message about the impute function.
6) Plugins:The following plugins may have passed incorrect data. For 1-color data: Histogram and Smoothed CDF and 2 color data:ANOVA on log intensities, Histograms, Pairwise Correlation Plot, MA plot and Smoothed CDF.
What's New in BRB-ArrayTools 3.3 beta
1) Enhanced heat map
more color coding options including multi-color rainbow
zoom in and out
labeling of genes
2) Pathway annotation of gene lists
3) Class comparison based on pathways rather than individual genes
4) Fast Fortran implementation of SAM
Approximately 7x faster than other implementations
5) Normalization of data separately by grid (print tip) for printed arrays
6) Direct import of GenePix data
7) Enhancements to Class Prediction analysis
Optimization of significance threshold for gene selection
New algorithm for selecting effective pairs of genes
Addition of shrunken centroid (PAM) classifier
8) New re-sampling methods for estimating prediction error
K-fold repeated cross-validation and .632 bootstrap options
9) Utility to compare gene lists
10) Plug-in for Random Forest classification
11) Plug-in for regression analysis of time series data to find regulated and differentially regulated genes
Version 3.2.1 is the stable release of version 3.2. Various bug fixes have been made. For details, please see the Readme file.
What's New in Version 3.2
1) Automatic importation of Affymetrix CEL files. Calculation of Affymetrix probe set summaries and normalization using RMA function of Bioconductor.
2) Importation of either log-transformed or not log-transformed data.
3) Class comparison to determine significance of Gene Ontology categories.
4) Class comparison to determine significance of user-defined genelists.
5) Extended class comparison for use in red-to-green comparisons with common reference.
6) Significance Analysis of Microarrays (SAM).
7) Speeded-up binary tree prediction tool using K-fold cross-validation.
8) ANOVA plugins tools:
- Fixed effect model for log-ratio or log-signal with up to 4 factors.
- Random effects model for log ratio or log signal.
- ANOVA for single channel intensities for dual-label arrays using non-common-reference design.
9) Optional parameters in 'Preferences.txt' file (in Prefs folder of ArrayTools installation folder) to control size of dendrogram plots produced by clustering tools.
10) Sample statistical considerations sections for publications included in Help documents.
What's new in release 3.1
1) New collation wizard simplifies the importation of expression data.
2) Automatic importation of Affymetrix annotations.
3) Data can now be directly ported to Cluster and TreeView for further analysis.
4) New class comparison tool for dual-label arrays that do not use common reference design.
5) New quantitative traits analysis tool allows selection of genes which are significantly correlated with a quantitative (numeric) trait.
6) New binary tree prediction tool for class prediction with more than two classes by forming a tree of binary classifiers.
7) The class prediction tool has two new options for the gene selection criteria and the randomized variance method has now been implemented as an option in the class prediction tool.
8) Improved gene ontology analysis of gene lists produced by class comparison, class prediction, survival and quantitative traits tools.
9) Users may now subset the data globally for any analysis by selecting a set of defined genelists.
10) If the user is connected to the Internet, then BRB-ArrayTools will automatically check the BRB server for software updates every seven days (unless the user changes the UpdateInterval parameter in the Preferences.txt file).
Changes since the previous version (3.0.2e):
1) BRB-ArrayTools now uses version 1.2 of the RCOM. If the user does not yet have the RCOM 1.2 installed, then the BRB-ArrayTools installer will automatically try to install it. The user may still use any version of R later than or equal to version 1.6.1.
2) The collation wizard now offers the option of whether or not to average over multiply-spotted clones during collation. Previous versions automatically averaged over multiply-spotted clones when the original input data were in separate files for each array, but did not do the averaging when the original input data were horizontally aligned in one single file.
3) The order of appearance of the arrays in the "Filtered log ratio" or "Filtered log intensity" worksheet of the project workbook now matches the order of appearance of the arrays in the experiment descriptor file, if the user has provided one.
4) Permutation tests now use a complete enumeration of permutations when the number of possible permutations is less than 1000, and only uses randomly selected permutations when the number of permutations exceeds 1000.
5) The default confidence interval for the multivariate permutation test is now 90%.
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