Overview
VTCdb offers an online platform for grapevine transcriptional regulatory inference
for the cultivated grapevine.
VTCdb provides users to query gene(s), modules or biological processes of interests
in several ways.Querying a gene(s) gives a ranked list of co-expressed genes, functional annotations
and its associated module. Alternatively, browsing of modules of interests retrieves
hierarchical optimized Gene Ontology enrichment and tissue/condition specificity
genes within the module along with interactive network visualisation and analysis
via CytoscapeWeb.
Platform & updates
17.04.2014>> Empirical Bayes conditional independence grapevine gene network (condition-indepedent or "All") added (Beta). (Click
to see example)
01.10.2013>> Major updates:
Queries are now made with the VIT_ code of the V1 grapevine annotation. The
Condition-independent (All datasets) and -
dependent (Berry and stress)
co-expression analysis (guide gene and graph clustering) added. Co-expression
stability of co-expressed genes in
various conditions can be examined (Click
to see example)
01.09.2013>> 63 new 29K Nimblegen datasets,
functional (GO) enrichment analysis and module identication using MCL added
01.07.2013>> Nimblegen Grape Whole-Genome Microarray 29K 090918-MD 418
arrays; 8 experiments
01.06.2013>> Affymetrix GeneChip 16K Vitis vinifera Genome Array 403 arrays;
20 experiments
Note: we are constantly updating and improving VTCdb for better grapevine transcriptional
analysis as soon as new data is available. We appreciate any comments and
suggestions for current and future releases (Email here).
Reference
For a detailed description on how to use VTCdb, please refer to the accompanying
paper here [pdf] or
the reference below. If you find this resource
useful, please cite reference below.
Wong
DCJ, Sweetman C, Drew DP and Ford CM.
VTCdb: a gene co-expression database for the crop
species Vitis vinifera (grapevine).
BMC Genomics 2013, 14:882 (VTCdb tools)
Sweetman C, Wong DCJ, Ford CM and Drew DP.
Transcriptome analysis at four developmental stages of grape berry (Vitis vinifera cv. Shiraz) provides insights into regulated and coordinated gene expression.
BMC Genomics 2012, 13:691 (Additional tools: RNA-SeqQuery for grapevine berry development)
Bulk download
Compendium |
Features
|
Condition
|
No. of arrays/
experiments
|
No. of
probesets*
|
Co-expression
measure
|
Platform
|
Notes
|
2.1
|
All
|
480(451)/(9)
|
45000
|
HRR, MR, PCC, ELMM
|
GPL13936
GPL1320
|
Condition-independent (All datasets) co-expression analysis for both 29K Grape Whole-genome
and 16K Affymetrix microarray.
|
|
Berry
|
305
|
28811
|
HRR, MR, PCC
|
GPL13936
|
Condition-dependent (Berry datasets) co-expression analysis using berry-related
samples.
|
|
Stress
|
59
|
28811
|
HRR, MR, PCC
|
GPL13936
|
Condition-dependent (Stress datasets) co-expression analysis using stress-related/associated
samples
|
1.0
|
16K
Affymetrix
|
403(451)/(20)
|
16000
|
HRR, PCC
|
GPL1320
|
Greater variety of stress conditions (abiotic, biotic, chemical, hormone). Limited
transcriptome coverage (~33%)
|

Searches may take up to 2-3 minutes, thanks for your patience...
CoexQuery
To search for genes co-expressed with your gene(s)
of interests,
(i) input the unique gene identifiers for your gene [i.e.
VIT_16s0100g00290, VIT_12s0028g03100(V1 grapevine annotation) or 1616094_at(Affymetrix)]
(ii) Select predefined datasets
All arrays
(Condition-independent)
Berry
(Various developmental series; condition-dependent)
Stress
(Biotic, abiotic, etc; condition-dependent)
(iii) Select co-expression measure
Notes:
The 'HRR' method is the preferred co-expression measure.
Highest reciprocal rank (HRR): Highest reciproral PCC rank from gene A to gene B
and that of gene B to gene A.
Mutual rank (MR): Geometric average of the PCC rank from gene A to gene B and that
of gene B to gene A.
Empirical Light Mutual Min (ELMM): Empirical Bayes conditional dependence (with heurestic relaxation) between gene A to gene B and that of gene B to A. (See Mahdi et al. (2012))
Browse the inter-module co-expression network directly below. Nodes
presents modules while edges represents inter-module connectivity between modules.
Purple, Blue, Red, Yellow, Cyan, Green -colored modules represent meta-networks
of Berry_HRR_MCL, All_HRR_MCL, Stress_HRR_MCL, All_HRR_HCCA, Stress_HRR_HCCA, Berry_HRR_HCCA,
respectively.Right-click to select meta-network of interest (i.e. All_HRR_HCCA).
Upon selection, click selected node (module) or edges to preview enriched GO BP
terms and connectivity score (P<0.01) between modules, respectively. Double-click
node to go to module page for additional information (e.g. list of gene belonging
in module, visualisation of intra-module network, detailed information on enriched
terms and expression specificity inferred from the module.