Difference between revisions of "Plugins"
Line 7: Line 7:
  
  
−
==Visualization==
+
==Analysis==
  
 
{|style="border: 1px solid lightGray"
 
{|style="border: 1px solid lightGray"
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|-
 
|-
 
|-
 
|-
−
|width="150"|Analysis Panel||Released ||Framework to support numerous, individually loadable analysis methods.
+
|width="150"|ANOVA||Released||Analysis of Variance - detection of significant differences in expression between more than two groups.
 +
|-
 +
|-
 +
|width="150"|Evidence Integration||Development||
 +
|-
 +
|-
 +
|width="150"|Hierarchical Clustering||Released||Clustering of markers and microarrays into hierarchical binary trees. The resulting structures can be visualized in the Dendrogram plugin.
 +
|-
 
|-
 
|-
 +
|width="150"|KNN||Released||k-Nearest Neighbors analysis (from GenePattern).
 
|-
 
|-
−
|width="150"|ANOVA Tabular Viewer||Released||Displays the results of ANOVA analysis of gene expression  data in tabular format.
 
 
|-
 
|-
 +
|width="150"|Mark-Us||Released||Assesses the biochemical function for a given protein structure.
 
|-
 
|-
−
|width="150"|CELImageViewer||Released||Visualization of data in Affymetrix CEL files.
 
 
|-
 
|-
−
|-
+
|width="150"|MatrixReduce||Released||Transcription Factor binding motifs.
−
|width="150"|Color Mosaic||Released||Heat maps for microarray expression data, organized by phenotypic or gene groupings ([[media:Color-mosaic.png|screenshot]]).
 
 
|-
 
|-
 
|-
 
|-
−
|width="150"|Dendrogram||Released||Tree-structured diagrams reflecting the results of hierarchical clustering analysis ([[media:Dendrogram.png|screenshot]]).
+
|width="150"|MEDUSA||Development||The Motif Element Detection Using Sequence Agglomeration is an integrative method for learning motif models of transcription factor binding sites by incorporating promoter sequence and gene expression data (Leslie Lab at MSKCC).
 
|-
 
|-
 
|-
 
|-
−
|width="150"|Evidence Integration Viewer||Development||Displays the results of the Evidence Integration analysis.
+
|width="150"|MRA||Released||Master Regulator Analysis combines regulatory information from interaction networks with differential expression analysis.
−
|-
 
 
|-
 
|-
−
|width="150"|Expression Profiles||Released||Line graph of genes expression profiles across several arrays/ hybridizations ([[media:Expression-profile.png|screenshot]]).
 
−
|-
 
 
|-
 
|-
−
|width="150"|Expression Value Distribution||Released||Distribution plot of marker expression values across one or more microarrays.
+
|width="150"|PCA||Released||Principal Component Analysis (from GenePattern).
 
|-
 
|-
 
|-
 
|-
−
|width="150"|GO Terms Viewer||Released||Displays the results of Gene Ontology Enrichment Analysis.
+
|width="150"|Pudge||Released ||Computational protein structure prediction using sequence homology. It integrates tools used at different stages of the structural prediction process.
−
|-
 
−
|-
 
−
|width="150"|Image Viewer||Released||Visualization of screenshots saved within geWorkbench (e.g. dendrograms).
 
−
|-
 
−
|-
 
−
|width="150"|Jmol||Released || Visualization of 3D protein structures from PDB files.
 
 
|-
 
|-
 
|-
 
|-
−
|width="150"|Mark-Us Browser||Released || Displays the results of a MarkUs analysis.
+
|width="150"|SkyBase||Development||Database of protein structure models produced by SkyLine based on structures solved by the NESG structural genomics consortium.
 
|-
 
|-
 
|-
 
|-
−
|width="150"|MatrixReduce||Released||Visualization of MatrixReduce calculations using logo, chromosomal and tabular displays.
+
|width="150"|SkyLine||Development||Automated high-throughput pipeline for reverse homology-based comparative protein structure modeling based on the input template structure.
 
|-
 
|-
 
|-
 
|-
−
|width="150"|MEDUSA Viewer||Development||Displays the results of a MEDUSA analysis.
+
|width="150"|SOM||Released||Clustering of markers using Self Organizing Maps. The resulting clusters can be visualized in the SOM Clusters Viewer plugin.
−
|-
 
 
|-
 
|-
−
|width="150"|Microarray Viewer||Released||Color-gradient representation of gene expression values ([[media:Microarray-panel.png|screenshot]]).
 
−
|-
 
 
|-
 
|-
−
|width="150"|MINDy Viewer||Released||The results of a MINDy calculation are presented in several different tabular displays and a heat map.
+
|width="150"|SVM||Released||Support Vector Machine is a supervised classification method that computes a maximal separating hyperplane between the expression vectors of different classes or phenotypes (from GenePattern).
−
|-
 
 
|-
 
|-
−
|width="150"|MRA Viewer||Released||Displays the results of the MRA in tablular and graphical form.
 
−
|-
 
 
|-
 
|-
−
|width="150"|NetBoost Viewer||Development||Displays a Boosting Iteration Graph, Confusion Matrix and Score Table from NetBoost Analysis.
+
|width="150"|T-Test||Released||Identification of markers with statistically significant differential expression between sets of microarrays. ([[media:Volcanoplot.png|screenshot]]).
−
|-
 
 
|-
 
|-
−
|width="150"|Normalization Panel||Released ||Framework to support numerous, individually loadable normalization components.
 
 
|-
 
|-
 +
|width="150"|Weighted Voting||Released||Weighted Voting Analysis (from GenePattern).
 
|-
 
|-
−
|width="150"|PCA Viewer||Released ||Displays PCA results.
 
 
|-
 
|-
 +
|}
 +
 +
 +
==Annotation==
 +
 +
{|style="border: 1px solid lightGray"
 +
!Plugin||Status||Description
 
|-
 
|-
−
|width="150"|Pudge Browser||Released ||Visualization of Pudge results.
 
−
|-
 
 
|-
 
|-
−
|width="150"|Scatter Plot||Released || Pairwise (array vs. array and marker vs. marker) comparison and plotting of expression values ([[media:Scatterplot.png|screenshot]]).
+
|width="150"|Dataset Annotation||Released||Free text format box used to annotate data, images and results. Such annotations persist application invocations and can be used as an online "lab notebook.
−
|-
 
 
|-
 
|-
−
|width="150"|SkyBase Viewer||Development||
 
−
|-
 
 
|-
 
|-
−
|width="150"|SkyLine Output All||Development||Displays all models from the Skyline modeling.
+
|width="150"|Dataset History||Released||Log of data transformations induced by data-modifying operations.
−
|-
 
 
|-
 
|-
−
|width="150"|SkyLine Output Each||Development||Displays each model from the Skyline modeling.
 
−
|-
 
 
|-
 
|-
−
|width="150"|SOM Clusters Viewer||Released||Visualization of gene clusters produced by the self-organizing maps analysis ([[media:Somcluster.png|screenshot]]).
+
|width="150"|Experiment Information||Released||Microarray machine parameters used in an experiment run. If available, high-level experiment information (e.g., purpose of of experiment) are also displayed.
 
|-
 
|-
 
|-
 
|-
−
|width="150"|SVM Viewer||Released||Visualizes results obtained from classifying samples based on SVMs generated using the Gene Pattern v3 SVM service.  
+
|width="150"|Gene Ontology||Released||Enrichment analysis of selected groups of genes against Gene Ontology (http://www.geneontology.org) annotations ([[media:Go_Terms_Panel.png|screenshot]]).
−
|-
 
 
|-
 
|-
−
|width="150"|Tabular Microarray Viewer||Released || Spreadsheet view of all expression measurement in an experiment, one row per individual marker/probe and one column per microarray ([[media:Tabular.png|screenshot]]).
 
 
|-
 
|-
 +
|width="150"|Marker Annotations||Released||Retrieval of gene and pathway information for markers on a microarray.  Includes visualization of BioCarta pathway diagrams ([[media:Cabiopathway.png|screenshot]]).
 
|-
 
|-
−
|width="150"| Volcano Plot||Released  || Visualize fold-change vs significance (P-value) for t-test results.
 
−
|-
 
 
|-
 
|-
 
|}
 
|}
Line 121: Line 106:
  
  
−
==Normalization==
+
==Filtering==
  
 
{|style="border: 1px solid lightGray"
 
{|style="border: 1px solid lightGray"
Line 127: Line 112:
 
|-
 
|-
 
|-
 
|-
−
|width="150"|Array-Based Centering||Released||Subtraction of the mean or median measurement of a microarray from every measurement in that microarray.
+
|width="150"|Affy Detection Call||Released||(''Affymetrix data only)'' Filtering of measurements based on the value of their "detection call" attribute.
 
|-
 
|-
 
|-
 
|-
−
|width="150"|Housekeeping Normalizer||Released|| Normalization of all measurements in a microarray through division by the average expression value of a (user defined) set of housekeeping genes.
+
|width="150"|Deviation Filter||Released|| Filtering of markers with low dynamic range.
 
|-
 
|-
 
|-
 
|-
−
|width="150"|Log2 Normalizer||Released||The log2 transformation is applied to all measurements in a microarray, if all values in all microarrays are positive.
+
|width="150"|Expression Threshold||Released|| Elimination of measurements that fall outside a range of explression values.
 
|-
 
|-
 
|-
 
|-
−
|width="150"|Marker-Based Centering||Released||Subtraction of the mean or median measurement of a marker profile from every measurement in the profile.
+
|width="150"|2-channel Threshold||Released||(''Genepix data only)'' Same as "Expression Threshold" filter but different threshold ranges can be specified for each channel.
 
|-
 
|-
 
|-
 
|-
−
|width="150"|Mean-Variance Normalizer||Released||Transformation of expression measurements to standard units: for every marker, the mean measurement of the marker profile (across all microarrays in an experiment) is subtracted from each measurement in the profile and the resulting value is divided by the standard deviation of the profile.
+
|width="150"|Genepix Flag Filter||Released|| ''(Genepix data only)'' Filtering of measurements based on the value of their "Flags" attribute.
 
|-
 
|-
 
|-
 
|-
−
|width="150"|Missing Value Normalizer||Released||Replacement of missing values with consensus values.
+
|width="150"|Missing Value Filter||Released|| Discards all markers that have missing measurements in more than a user specified number N of microarrays.
−
|-
 
−
|-
 
−
|width="150"|Quantile Normalizer||Released|| Expression measurements in each microarray are adjusted so that  the distribution of values is the same across all microarrays in an experiment.
 
−
|-
 
−
|-
 
−
|width="150"|Threshold Normalizer||Released||Adjustment of values that fall outside a user-specified threshold.
 
 
|-
 
|-
 
|-
 
|-
Line 154: Line 133:
  
  
−
==Filtering==
+
==Network Generation, Networking==
  
 
{|style="border: 1px solid lightGray"
 
{|style="border: 1px solid lightGray"
Line 160: Line 139:
 
|-
 
|-
 
|-
 
|-
−
|width="150"|Affy Detection Call||Released||(''Affymetrix data only)'' Filtering of measurements based on the value of their "detection call" attribute.
+
|width="150"|ARACNe||Released||The Algorithm for the Reconstruction of Accurate Cellular Networks analyses large amount of microarray data (typically 100-500 microarrays) to reverse engineer underlying gene regulatory networks ([[media:Reverseengineering.png|screenshot]]).
 +
|-
 +
|-
 +
|width="150"|caArray||Released||Search and download of gene expression data from instances of caArray (NCI microarray database product).
 +
|-
 +
|-
 +
|width="150"|Cancer GEMS||Development||Interface to the NCI Cancer Genetic Markers of Susceptibility project.
 
|-
 
|-
 
|-
 
|-
−
|width="150"|Deviation Filter||Released|| Filtering of markers with low dynamic range.
+
|width="150"|Cellular Networks Knowledge Base||Released||Queries a local database housed at Columbia University which combines locally generated B-cell interaction network data with information from external databases.  Builds a network of interactions for selected genes.
 
|-
 
|-
 
|-
 
|-
−
|width="150"|Expression Threshold||Released|| Elimination of measurements that fall outside a range of explression values.
+
|width="150"|Cytoscape||Released||Visualization of gene regulatory network created in Reverse Engineering using [http://www.cytoscape.org/ Cytoscape 1.0]([[media:Cytoscape.png|screenshot]]).
 
|-
 
|-
 
|-
 
|-
−
|width="150"|2-channel Threshold||Released||(''Genepix data only)'' Same as "Expression Threshold" filter but different threshold ranges can be specified for each channel.
+
|width="150"|genSpace||Released||It logs information about the analysis tools that geWorkbench users run, so as to answer such questions as "what are the most commonly used analysis tools?" or "which analysis tools are most commonly used together?".
 
|-
 
|-
 
|-
 
|-
−
|width="150"|Genepix Flag Filter||Released|| ''(Genepix data only)'' Filtering of measurements based on the value of their "Flags" attribute.
+
|width="150"|MINDy||Released||The Modulator Inference by Network Dynamics algorithm extends ARACNe to include detecting the influence of modulators of transcription factor activity.
 
|-
 
|-
 
|-
 
|-
−
|width="150"|Missing Value Filter||Released|| Discards all markers that have missing  measurements in more than a user specified number N of microarrays.
+
|width="150"|NetBoost||Development||NetBoost is a network characterization algorithm.
 
|-
 
|-
 
|-
 
|-
Line 181: Line 166:
  
  
−
==Annotation==
+
==Normalization==
  
 
{|style="border: 1px solid lightGray"
 
{|style="border: 1px solid lightGray"
Line 187: Line 172:
 
|-
 
|-
 
|-
 
|-
−
|width="150"|Dataset Annotation||Released||Free text format box used to annotate data, images and results. Such annotations persist application invocations and can be used as an online "lab notebook.
+
|width="150"|Array-Based Centering||Released||Subtraction of the mean or median measurement of a microarray from every measurement in that microarray.
 +
|-
 +
|-
 +
|width="150"|Housekeeping Normalizer||Released|| Normalization of all measurements in a microarray through division by the average expression value of a (user defined) set of housekeeping genes.
 +
|-
 +
|-
 +
|width="150"|Log2 Normalizer||Released||The log2 transformation is applied to all measurements in a microarray, if all values in all microarrays are positive.
 +
|-
 +
|-
 +
|width="150"|Marker-Based Centering||Released||Subtraction of the mean or median measurement of a marker profile from every measurement in the profile.
 
|-
 
|-
 
|-
 
|-
−
|width="150"|Dataset History||Released||Log of data transformations induced by data-modifying operations.
+
|width="150"|Mean-Variance Normalizer||Released||Transformation of expression measurements to standard units: for every marker, the mean measurement of the marker profile (across all microarrays in an experiment) is subtracted from each measurement in the profile and the resulting value is divided by the standard deviation of the profile.
 
|-
 
|-
 
|-
 
|-
−
|width="150"|Experiment Information||Released||Microarray machine parameters used in an experiment run. If available, high-level experiment information (e.g., purpose of of experiment) are also displayed.
+
|width="150"|Missing Value Normalizer||Released||Replacement of missing values with consensus values.
 
|-
 
|-
 
|-
 
|-
−
|width="150"|Gene Ontology||Released||Enrichment analysis of selected groups of genes against Gene Ontology (http://www.geneontology.org) annotations ([[media:Go_Terms_Panel.png|screenshot]]).
+
|width="150"|Quantile Normalizer||Released|| Expression measurements in each microarray are adjusted so that  the distribution of values is the same across all microarrays in an experiment.
 
|-
 
|-
 
|-
 
|-
−
|width="150"|Marker Annotations||Released||Retrieval of gene and pathway information for markers on a microarray.  Includes visualization of BioCarta pathway diagrams ([[media:Cabiopathway.png|screenshot]]).
+
|width="150"|Threshold Normalizer||Released||Adjustment of values that fall outside a user-specified threshold.
 
|-
 
|-
 
|-
 
|-
Line 205: Line 199:
  
  
−
==Network Generation, Networking==
+
== Sequence Analysis & Visualization ==
  
 
{|style="border: 1px solid lightGray"
 
{|style="border: 1px solid lightGray"
Line 211: Line 205:
 
|-
 
|-
 
|-
 
|-
−
|width="150"|ARACNe||Released||The Algorithm for the Reconstruction of Accurate Cellular Networks analyses large amount of microarray data (typically 100-500 microarrays) to reverse engineer underlying gene regulatory networks ([[media:Reverseengineering.png|screenshot]]).
+
|width="150"|Alignment Results||Released||It parses and displays the results of sequence similarity searches which were run on the NCBI BLAST service.
 
|-
 
|-
 
|-
 
|-
−
|width="150"|caArray||Released||Search and download of gene expression data from instances of caArray (NCI microarray database product).
+
|width="150"|Pattern  Discovery||Released|| Discovery of sequence motifs in sets of DNA and protein sequences.
 
|-
 
|-
 
|-
 
|-
−
|width="150"|Cancer GEMS||Development||Interface to the NCI Cancer Genetic Markers of Susceptibility project.
+
|width="150"|Position Histogram ||Released|| Visualization of results from the Pattern Discovery plugin. Motif/pattern support is plotted against relative sequence position of the motif match ([[media:Histogram.png|screenshot]]).  
 
|-
 
|-
 
|-
 
|-
−
|width="150"|Cellular Networks Knowledge Base||Released||Queries a local database housed at Columbia University which combines locally generated B-cell interaction network data with information from external databases. Builds a network of interactions for selected genes.
+
|width="150"|Promoter Analysis||Released||Identification of putative transcription factor binding sites in DNA sequences ([[media:Promoterpanel.png|screenshot]]). The analysis use the profiles in the [http://jaspar.cgb.ki.se/cgi-bin/jaspar_db.pl JASPAR Transcription Factor Binding Profile Database.]
 
|-
 
|-
 
|-
 
|-
−
|width="150"|Cytoscape||Released||Visualization of gene regulatory network created in Reverse Engineering using [http://www.cytoscape.org/ Cytoscape 1.0]([[media:Cytoscape.png|screenshot]]).
+
|width="150"|Sequence Alignment||Released||Run jobs on the NCBI BLAST servers directly within geWorkbench.  
 
|-
 
|-
 
|-
 
|-
−
|width="150"|genSpace||Released||It logs information about the analysis tools that geWorkbench users run, so as to answer such questions as "what are the most commonly used analysis tools?" or "which analysis tools are most commonly used together?".
+
|width="150"|Sequence Panel ||Released|| Visualization of results from the Pattern Discovery plugin, displaying the motif match location over each sequence from the input data set.
 
|-
 
|-
 
|-
 
|-
−
|width="150"|MINDy||Released||The Modulator Inference by Network Dynamics algorithm extends ARACNe to include detecting the influence of modulators of transcription factor activity.
+
|width="150"|Sequence Retriever||Released||Retrieve sequences for annotated markers from Santa Cruz (nucleotide sequences) and EBI (proteins sequences).  
 
|-
 
|-
 
|-
 
|-
−
|width="150"|NetBoost||Development||NetBoost is a network characterization algorithm.
+
|width="150"|Synteny||Discontinued|| Comparison of sequence similarity between two genomic regions. The comparison results are represented as a dot matrix augmented with detailed annotation for both regions ([[media:Synteny Dotmatrix.png|screenshot]]).
 
|-
 
|-
 
|-
 
|-
Line 238: Line 232:
  
  
−
==Analysis==
+
==Visualization==
  
 
{|style="border: 1px solid lightGray"
 
{|style="border: 1px solid lightGray"
Line 244: Line 238:
 
|-
 
|-
 
|-
 
|-
−
|width="150"|ANOVA||Released||Analysis of Variance - detection of significant differences in expression between more than two groups.
+
|width="150"|Analysis Panel||Released ||Framework to support numerous, individually loadable analysis methods.
 
|-
 
|-
 
|-
 
|-
−
|width="150"|Evidence Integration||Development||
+
|width="150"|ANOVA Tabular Viewer||Released||Displays the results of ANOVA analysis of gene expression  data in tabular format.
 
|-
 
|-
 
|-
 
|-
−
|width="150"|Hierarchical Clustering||Released||Clustering of markers and microarrays into hierarchical binary trees. The resulting structures can be visualized in the Dendrogram plugin.
+
|width="150"|CELImageViewer||Released||Visualization of data in Affymetrix CEL files.
 
|-
 
|-
 +
|-
 +
|width="150"|Color Mosaic||Released||Heat maps for microarray expression data, organized by phenotypic or gene groupings ([[media:Color-mosaic.png|screenshot]]).
 
|-
 
|-
−
|width="150"|KNN||Released||k-Nearest Neighbors analysis (from GenePattern).
 
 
|-
 
|-
 +
|width="150"|Dendrogram||Released||Tree-structured diagrams reflecting the results of hierarchical clustering analysis ([[media:Dendrogram.png|screenshot]]).
 
|-
 
|-
−
|width="150"|Mark-Us||Released||Assesses the biochemical function for a given protein structure.
 
 
|-
 
|-
 +
|width="150"|Evidence Integration Viewer||Development||Displays the results of the Evidence Integration analysis.
 +
|-
 
|-
 
|-
−
|width="150"|MatrixReduce||Released||Transcription Factor binding motifs.
+
|width="150"|Expression Profiles||Released||Line graph of genes expression profiles across several arrays/ hybridizations ([[media:Expression-profile.png|screenshot]]).
 +
|-
 
|-
 
|-
 +
|width="150"|Expression Value Distribution||Released||Distribution plot of marker expression values across one or more microarrays.
 
|-
 
|-
−
|width="150"|MEDUSA||Development||The Motif Element Detection Using Sequence Agglomeration is an integrative method for learning motif models of transcription factor binding sites by incorporating promoter sequence and gene expression data (Leslie Lab at MSKCC).
 
 
|-
 
|-
 +
|width="150"|GO Terms Viewer||Released||Displays the results of Gene Ontology Enrichment Analysis.
 +
|-
 +
|-
 +
|width="150"|Image Viewer||Released||Visualization of screenshots saved within geWorkbench (e.g. dendrograms).
 +
|-
 +
|-
 +
|width="150"|Jmol||Released || Visualization of 3D protein structures from PDB files.
 +
|-
 
|-
 
|-
−
|width="150"|MRA||Released||Master Regulator Analysis combines regulatory information from interaction networks with differential expression analysis.
+
|width="150"|Mark-Us Browser||Released || Displays the results of a MarkUs analysis.
 +
|-
 
|-
 
|-
 +
|width="150"|MatrixReduce||Released||Visualization of MatrixReduce calculations using logo, chromosomal and tabular displays.
 +
|-
 
|-
 
|-
−
|width="150"|PCA||Released||Principal Component Analysis (from GenePattern).
+
|width="150"|MEDUSA Viewer||Development||Displays the results of a MEDUSA analysis.
 +
|-
 
|-
 
|-
 +
|width="150"|Microarray Viewer||Released||Color-gradient representation of gene expression values ([[media:Microarray-panel.png|screenshot]]).
 +
|-
 
|-
 
|-
−
|width="150"|Pudge||Released ||Computational protein structure prediction using sequence homology. It integrates tools used at different stages of the structural prediction process.
+
|width="150"|MINDy Viewer||Released||The results of a MINDy calculation are presented in several different tabular displays and a heat map.
 
|-
 
|-
 
|-
 
|-
−
|width="150"|SkyBase||Development||Database of protein structure models produced by SkyLine based on structures solved by the NESG structural genomics consortium.
+
|width="150"|MRA Viewer||Released||Displays the results of the MRA in tablular and graphical form.
 
|-
 
|-
 
|-
 
|-
−
|width="150"|SkyLine||Development||Automated high-throughput pipeline for reverse homology-based comparative protein structure modeling based on the input template structure.
+
|width="150"|NetBoost Viewer||Development||Displays a Boosting Iteration Graph, Confusion Matrix and Score Table from NetBoost Analysis.
 
|-
 
|-
 
|-
 
|-
−
|width="150"|SOM||Released||Clustering of markers using Self Organizing Maps. The resulting clusters can be visualized in the SOM Clusters Viewer plugin.
+
|width="150"|Normalization Panel||Released ||Framework to support numerous, individually loadable normalization components.
 
|-
 
|-
 
|-
 
|-
−
|width="150"|SVM||Released||Support Vector Machine is a supervised classification method that computes a maximal separating hyperplane between the expression vectors of different classes or phenotypes (from GenePattern).
+
|width="150"|PCA Viewer||Released ||Displays PCA results.
 
|-
 
|-
 
|-
 
|-
−
|width="150"|T-Test||Released||Identification of markers with statistically significant differential expression between sets of microarrays. ([[media:Volcanoplot.png|screenshot]]).
+
|width="150"|Pudge Browser||Released ||Visualization of Pudge results.
 +
|-
 
|-
 
|-
 +
|width="150"|Scatter Plot||Released || Pairwise (array vs. array and marker vs. marker) comparison and plotting of expression values ([[media:Scatterplot.png|screenshot]]).
 +
|-
 
|-
 
|-
−
|width="150"|Weighted Voting||Released||Weighted Voting Analysis (from GenePattern).
+
|width="150"|SkyBase Viewer||Development||
 +
|-
 
|-
 
|-
 +
|width="150"|SkyLine Output All||Development||Displays all models from the Skyline modeling.
 +
|-
 
|-
 
|-
−
|}
+
|width="150"|SkyLine Output Each||Development||Displays each model from the Skyline modeling.
−
 
+
|-
−
 
 
−
== Sequence Analysis & Visualization ==
 
−
 
 
−
{|style="border: 1px solid lightGray"
 
−
!Plugin||Status||Description
 
 
|-
 
|-
−
|-
+
|width="150"|SOM Clusters Viewer||Released||Visualization of gene clusters produced by the self-organizing maps analysis ([[media:Somcluster.png|screenshot]]).
−
|width="150"|Alignment Results||Released||It parses and displays the results of sequence similarity searches which were run on the NCBI BLAST service.
 
 
|-
 
|-
 
|-
 
|-
−
|width="150"|Pattern  Discovery||Released|| Discovery of sequence motifs in sets of DNA and protein sequences.
+
|width="150"|SVM Viewer||Released||Visualizes results obtained from classifying samples based on SVMs generated using the Gene Pattern v3 SVM service.  
 +
|-
 
|-
 
|-
 +
|width="150"|Tabular Microarray Viewer||Released || Spreadsheet view of all expression measurement in an experiment, one row per individual marker/probe and one column per microarray ([[media:Tabular.png|screenshot]]).
 
|-
 
|-
−
|width="150"|Position Histogram ||Released|| Visualization of results from the Pattern Discovery plugin. Motif/pattern support is plotted against relative sequence position of the motif match ([[media:Histogram.png|screenshot]]).
 
−
|-
 
−
|-
 
−
|width="150"|Promoter Analysis||Released||Identification of putative transcription factor binding sites in DNA sequences ([[media:Promoterpanel.png|screenshot]]). The analysis use the profiles in the [http://jaspar.cgb.ki.se/cgi-bin/jaspar_db.pl JASPAR Transcription Factor Binding Profile Database.]
 
−
|-
 
−
|-
 
−
|width="150"|Sequence Alignment||Released||Run jobs on the NCBI BLAST servers directly within geWorkbench.
 
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|width="150"|Sequence Panel ||Released|| Visualization of results from the Pattern Discovery plugin, displaying the motif match location over each sequence from the input data set.
 
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|width="150"|Sequence Retriever||Released||Retrieve sequences for annotated markers from Santa Cruz (nucleotide sequences) and EBI (proteins sequences).
 
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|width="150"|Synteny||Discontinued|| Comparison of sequence similarity between two genomic regions. The comparison results are represented as a dot matrix augmented with detailed annotation for both regions ([[media:Synteny Dotmatrix.png|screenshot]]).
 
 
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|width="150"| Volcano Plot||Released  || Visualize fold-change vs significance (P-value) for t-test results.
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Revision as of 20:05, 11 February 2010

The geWorkbench platform employs a component repository infrastructure to manage a large collection of pluggable components that can be used to customize the application's graphical user interface. This (ever growing) list of plug-in components covers a wide range of fucntionality for a number of different genomic data modalities.



Analysis

Plugin Status Description
ANOVA Released Analysis of Variance - detection of significant differences in expression between more than two groups.
Evidence Integration Development
Hierarchical Clustering Released Clustering of markers and microarrays into hierarchical binary trees. The resulting structures can be visualized in the Dendrogram plugin.
KNN Released k-Nearest Neighbors analysis (from GenePattern).
Mark-Us Released Assesses the biochemical function for a given protein structure.
MatrixReduce Released Transcription Factor binding motifs.
MEDUSA Development The Motif Element Detection Using Sequence Agglomeration is an integrative method for learning motif models of transcription factor binding sites by incorporating promoter sequence and gene expression data (Leslie Lab at MSKCC).
MRA Released Master Regulator Analysis combines regulatory information from interaction networks with differential expression analysis.
PCA Released Principal Component Analysis (from GenePattern).
Pudge Released Computational protein structure prediction using sequence homology. It integrates tools used at different stages of the structural prediction process.
SkyBase Development Database of protein structure models produced by SkyLine based on structures solved by the NESG structural genomics consortium.
SkyLine Development Automated high-throughput pipeline for reverse homology-based comparative protein structure modeling based on the input template structure.
SOM Released Clustering of markers using Self Organizing Maps. The resulting clusters can be visualized in the SOM Clusters Viewer plugin.
SVM Released Support Vector Machine is a supervised classification method that computes a maximal separating hyperplane between the expression vectors of different classes or phenotypes (from GenePattern).
T-Test Released Identification of markers with statistically significant differential expression between sets of microarrays. (screenshot).
Weighted Voting Released Weighted Voting Analysis (from GenePattern).


Annotation

Plugin Status Description
Dataset Annotation Released Free text format box used to annotate data, images and results. Such annotations persist application invocations and can be used as an online "lab notebook.
Dataset History Released Log of data transformations induced by data-modifying operations.
Experiment Information Released Microarray machine parameters used in an experiment run. If available, high-level experiment information (e.g., purpose of of experiment) are also displayed.
Gene Ontology Released Enrichment analysis of selected groups of genes against Gene Ontology (http://www.geneontology.org) annotations (screenshot).
Marker Annotations Released Retrieval of gene and pathway information for markers on a microarray. Includes visualization of BioCarta pathway diagrams (screenshot).


Data Management

Plugin Status Description
Marker Component Released Definition of data views consisting of marker subgroups. The views control the amount of data displayed.
Phenotype/Array Component Released Definition of data views consisting of microarray subgroups. The views control the amount of data displayed.
Project Component Released Manages projects and workspaces of the user.


Filtering

Plugin Status Description
Affy Detection Call Released (Affymetrix data only) Filtering of measurements based on the value of their "detection call" attribute.
Deviation Filter Released Filtering of markers with low dynamic range.
Expression Threshold Released Elimination of measurements that fall outside a range of explression values.
2-channel Threshold Released (Genepix data only) Same as "Expression Threshold" filter but different threshold ranges can be specified for each channel.
Genepix Flag Filter Released (Genepix data only) Filtering of measurements based on the value of their "Flags" attribute.
Missing Value Filter Released Discards all markers that have missing measurements in more than a user specified number N of microarrays.


Network Generation, Networking

Plugin Status Description
ARACNe Released The Algorithm for the Reconstruction of Accurate Cellular Networks analyses large amount of microarray data (typically 100-500 microarrays) to reverse engineer underlying gene regulatory networks (screenshot).
caArray Released Search and download of gene expression data from instances of caArray (NCI microarray database product).
Cancer GEMS Development Interface to the NCI Cancer Genetic Markers of Susceptibility project.
Cellular Networks Knowledge Base Released Queries a local database housed at Columbia University which combines locally generated B-cell interaction network data with information from external databases. Builds a network of interactions for selected genes.
Cytoscape Released Visualization of gene regulatory network created in Reverse Engineering using Cytoscape 1.0(screenshot).
genSpace Released It logs information about the analysis tools that geWorkbench users run, so as to answer such questions as "what are the most commonly used analysis tools?" or "which analysis tools are most commonly used together?".
MINDy Released The Modulator Inference by Network Dynamics algorithm extends ARACNe to include detecting the influence of modulators of transcription factor activity.
NetBoost Development NetBoost is a network characterization algorithm.


Normalization

Plugin Status Description
Array-Based Centering Released Subtraction of the mean or median measurement of a microarray from every measurement in that microarray.
Housekeeping Normalizer Released Normalization of all measurements in a microarray through division by the average expression value of a (user defined) set of housekeeping genes.
Log2 Normalizer Released The log2 transformation is applied to all measurements in a microarray, if all values in all microarrays are positive.
Marker-Based Centering Released Subtraction of the mean or median measurement of a marker profile from every measurement in the profile.
Mean-Variance Normalizer Released Transformation of expression measurements to standard units: for every marker, the mean measurement of the marker profile (across all microarrays in an experiment) is subtracted from each measurement in the profile and the resulting value is divided by the standard deviation of the profile.
Missing Value Normalizer Released Replacement of missing values with consensus values.
Quantile Normalizer Released Expression measurements in each microarray are adjusted so that the distribution of values is the same across all microarrays in an experiment.
Threshold Normalizer Released Adjustment of values that fall outside a user-specified threshold.


Sequence Analysis & Visualization

Plugin Status Description
Alignment Results Released It parses and displays the results of sequence similarity searches which were run on the NCBI BLAST service.
Pattern Discovery Released Discovery of sequence motifs in sets of DNA and protein sequences.
Position Histogram Released Visualization of results from the Pattern Discovery plugin. Motif/pattern support is plotted against relative sequence position of the motif match (screenshot).
Promoter Analysis Released Identification of putative transcription factor binding sites in DNA sequences (screenshot). The analysis use the profiles in the JASPAR Transcription Factor Binding Profile Database.
Sequence Alignment Released Run jobs on the NCBI BLAST servers directly within geWorkbench.
Sequence Panel Released Visualization of results from the Pattern Discovery plugin, displaying the motif match location over each sequence from the input data set.
Sequence Retriever Released Retrieve sequences for annotated markers from Santa Cruz (nucleotide sequences) and EBI (proteins sequences).
Synteny Discontinued Comparison of sequence similarity between two genomic regions. The comparison results are represented as a dot matrix augmented with detailed annotation for both regions (screenshot).


Visualization

Plugin Status Description
Analysis Panel Released Framework to support numerous, individually loadable analysis methods.
ANOVA Tabular Viewer Released Displays the results of ANOVA analysis of gene expression data in tabular format.
CELImageViewer Released Visualization of data in Affymetrix CEL files.
Color Mosaic Released Heat maps for microarray expression data, organized by phenotypic or gene groupings (screenshot).
Dendrogram Released Tree-structured diagrams reflecting the results of hierarchical clustering analysis (screenshot).
Evidence Integration Viewer Development Displays the results of the Evidence Integration analysis.
Expression Profiles Released Line graph of genes expression profiles across several arrays/ hybridizations (screenshot).
Expression Value Distribution Released Distribution plot of marker expression values across one or more microarrays.
GO Terms Viewer Released Displays the results of Gene Ontology Enrichment Analysis.
Image Viewer Released Visualization of screenshots saved within geWorkbench (e.g. dendrograms).
Jmol Released Visualization of 3D protein structures from PDB files.
Mark-Us Browser Released Displays the results of a MarkUs analysis.
MatrixReduce Released Visualization of MatrixReduce calculations using logo, chromosomal and tabular displays.
MEDUSA Viewer Development Displays the results of a MEDUSA analysis.
Microarray Viewer Released Color-gradient representation of gene expression values (screenshot).
MINDy Viewer Released The results of a MINDy calculation are presented in several different tabular displays and a heat map.
MRA Viewer Released Displays the results of the MRA in tablular and graphical form.
NetBoost Viewer Development Displays a Boosting Iteration Graph, Confusion Matrix and Score Table from NetBoost Analysis.
Normalization Panel Released Framework to support numerous, individually loadable normalization components.
PCA Viewer Released Displays PCA results.
Pudge Browser Released Visualization of Pudge results.
Scatter Plot Released Pairwise (array vs. array and marker vs. marker) comparison and plotting of expression values (screenshot).
SkyBase Viewer Development
SkyLine Output All Development Displays all models from the Skyline modeling.
SkyLine Output Each Development Displays each model from the Skyline modeling.
SOM Clusters Viewer Released Visualization of gene clusters produced by the self-organizing maps analysis (screenshot).
SVM Viewer Released Visualizes results obtained from classifying samples based on SVMs generated using the Gene Pattern v3 SVM service.
Tabular Microarray Viewer Released Spreadsheet view of all expression measurement in an experiment, one row per individual marker/probe and one column per microarray (screenshot).
Volcano Plot Released Visualize fold-change vs significance (P-value) for t-test results.
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