Index Page

ZENBU Interfaces

 * ZENBU Genome Browser
 * Views are collections of Tracks
 * Tracks for data Visualization and Processing
 * Track visualization styles
 * Configuring Tracks
 * changing the region location
 * Data Explorer (DEX)
 * View config section
 * Track config section
 * Expression Experiments section
 * Annotation data source section
 * Scripts section
 * User profile system
 * Collaborations for data sharing
 * Creating new collaborations
 * Joining collaborations & inviting users
 * Sharing data with a collaboration
 * Public sharing of data and configs
 * Data uploading
 * BED files
 * BAM & SAM files
 * GFF GFF2 GTF files
 * OSCtable files
 * Data download : processed or raw data export

Data stream processing

 * ZENBU on demand data processing
 * ZENBU internal data model
 * Data stream pooling (merging data on demand)
 * signal processing scripting system
 * Processing modules
 * Infrastructure modules
 * Proxy: provide security-checked access to data sources loaded into ZENBU
 * FeatureEmitter:  create regular grids of features dynamically
 * Clustering and collation
 * TemplateCluster: use side-chain-stream as template to collate expression.
 * UniqueFeature: cluster and count features matching 'unique' criteria
 * Paraclu: hierarchical clustering algorithm http://www.cbrc.jp/paraclu/
 * Filtering
 * TemplateFilter: use side-chain-stream as mask to filter primary stream features
 * CutoffFilter: filter features using simple cutoff filters (high pass, low pass, band pass)
 * ExpressionDatatypeFilter: filter expression from features based on datatype
 * FeatureLengthFilter:
 * TopHits:
 * NeighborCutoff: noise filtering relative to strongest signal within a neighborhood
 * Data normalization and rescaling
 * NormalizeByFactor:
 * NormalizePerMillion:
 * NormalizeRPKM:
 * RescalePseudoLog:
 * General manipulation
 * CalcFeatureSignificance:
 * CalcInterSubfeatures:
 * StreamSubfeatures:
 * FilterSubfeatures: rebuild a feature/subfeature structure by filtering subfeatures
 * ResizeFeatures:
 * MakeStrandless:
 * RenameExperiments:
 * FeatureRename:

Metadata and search systems

 * Metadata searching
 * Metadata editing interface

Track, View and Script configurations

 * Configuration system
 * Track configs
 * View configs
 * Script configs
 * Saving and sharing configs

Experimental data types

 * Experimental data commonly loaded into ZENBU
 * Genome mapped sequence experiments
 * Genome annotations / analysis annotations
 * Microarray expression experiments
 * Novel genomes

Case studies

 * Case studies overview
 * Uploading annotation from other sources : UCSC repetitive elements track
 * RNAseq overview
 * using gene model to mask only known exonic expression signal
 * using gene model to collate exonic expression signal for display or download
 * shortRNA overview
 * using mirBase model to collate expression signal for display or download
 * using paraclu to delineate small RNA strucure and expression levels from mapping data
 * CHiP-seq overview
 * Processing CAGE data
 * Clustering CAGE along predefined regions In this case study we will illustrate how to vizualize CAGE based expression (yellow background track) along predefined clusters (blue background track) and collate expression onto themc (green background track). The example below uses the FANTOM4 CAGE data and significant clusters boundaries geenrated by the FANTOM4 consortium in The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line Nat Genet. 2009 May;41(5):553-62. http://fantom.gsc.riken.jp/zenbu/gLyphs/#config=hXV1oi_zCdOjH3oPeHd2VC;loc=hg18::chr19:54860670..54861358 [[image:Clustering CAGE along predefined region.png|400px]]
 * Clustering CAGE along gene models
 * de-novo CAGE signal clustering with "Paraclu"
 * Repeat associated Transcription Start Sites
 * Combining multi datatypes into a meta-analysis