Tools to calculate how similar the expression patterns of probes on the Affymetrix array follow that of a "driver" gene of interest.

Analysis options:

  1. Coexpression analysis in the specified experiment
  2. Coexpression analysis over available array experiments
  3. Co-correlation scatter plot
  4. Clique Finder
  5. Word Counter
  6. GO Term Counter
  7. Keyword Search

Need help? See FAQ

1. Coexpression analysis in the specified experiment

Note: Javascript must be enabled. The page may take some time to load.
Select the array type
Gene ID /Probe ID
Choose array experiment(s)

2. Coexpression analysis over available array experiments.

Show Pearson Correlation Coefficients for a probe using 121 AtGenome1 (Exp_ID: 1_1 to 1_21) or 322 ATH1 arrays (Exp_ID: 2_1 to 2_41).

Probe ID (e.g. 254831_at) Look up the probe ID by using ID exchanger.
limited to the first genes in order.
Leave box blank to receive the full correlation list.
Example analysis:
1. Ribosomal protein At4g12600 (254831_at);
2. Heat shock protein At2g20560 (263374_at);
3. Chlorophyll A/B binding protein At3g61470 (251325_s_at);

3. Co-correlation scatter plot (2-D Pearson Correlation Coefficients)

Show Pearson Correlation Coefficients for two probes using 121 AtGenome1 (Exp_ID: 1_1 to 1_21) or 322 ATH1 arrays (Exp_ID: 2_1 to 2_41).

Probe IDs
y-axis probe ID

(e.g. 260978_at)
x-axis probe ID (e.g. 266841_at)
Use ID exchanger to find the probe ID.
Show Co-correlation
Probe IDs to highlight (optional; separate by space)
* Highlighted probe IDs: This is useful to compare the expression patterns of, for example:
- all members of a gene family;
- all genes encoding sub-units of a multi-protein complex, e.g. ribosome;
- a set of genes from your own microarray experiments;
- the genes encoding enzymes of a biochemical pathway;
Please note: There is a small possibility that the scatter plot will re-use the probe ids from the previous query. If you notice this, please refresh the scatter plot page to resend the new probe ids and this should result in an updated scatter plot.

4. Clique Finder over available array experiments.

A tool to find clusters of closely-associated probes within the Pearson correlation coefficient ranked list for a given probe using 121 AtGenome1 (Exp_ID: 1_1 to 1_21) or 322 ATH1 arrays (Exp_ID: 2_1 to 2_41).

Probe ID (e.g. 254831_at) Look up the probe ID by using ID exchanger.
limited to the first genes and edges.
Example analysis:
1. Ribosomal protein At4g12600 (254831_at);
2. Heat shock protein At2g20560 (263374_at);
3. Chlorophyll A/B binding protein At3g61470 (251325_s_at);

5. Word count of Coexpression analysis over available array experiments.

Highlight annotations of the most correlated genes to a probe using 121 AtGenome1 (Exp_ID: 1_1 to 1_21) or 322 ATH1 arrays (Exp_ID: 2_1 to 2_41).

Probe ID (e.g. 254831_at) Look up the probe ID by usingID exchanger.
limited to the first genes in order, with confidence cutoff
Example analysis:
1. Ribosomal protein At4g12600 (254831_at);
2. Heat shock protein At2g20560 (263374_at);
3. Chlorophyll A/B binding protein At3g61470 (251325_s_at);

6. Gene Ontology term count of Coexpression analysis over available array experiments.

Show the GO Terms of the most correlated probes to a probe using 121 AtGenome1 (Exp_ID: 1_1 to 1_21) or 322 ATH1 arrays (Exp_ID: 2_1 to 2_41).

Probe ID (e.g. 254831_at) Look up the probe ID by using ID exchanger.
limited to the first genes in order, with confidence cutoff
Example analysis:
1. Ribosomal protein At4g12600 (254831_at);
2. Heat shock protein At2g20560 (263374_at);
3. Chlorophyll A/B binding protein At3g61470 (251325_s_at);

7. Keyword search of annotations for genes of interest

Keyword (or phrase): e.g. "dehydrogenase"

8. Frequently asked questions

  • How is the correlation coefficient calculated?
  • What equation do you use to calculate the correlation coefficient?
  • How do I interpret the correlation list for my gene?
  • What is the significance of the r-value, p-value and E-values?
  • How do I decide where the cut-off is between significantly correlated genes versus irrelevant genes?
  • What do the results from the Word and GO counting tools tell me?
  • Why is the r-value of the best-correlated gene (other than the driver) so low, e.g. 0.5?
  • My favourite gene is expressed at a very low level; will it be correlated with other (random?) unexpressed genes?
  • What a mixture of genes! Can there be any connection between them?!
  • My gene is correlated with many genes annotated as "hypothetical protein" or "expressed protein" - what does this mean?
  • What tissues and experimental treatments are represented in the ACT database? Does the dataset include data from mutants as well as wild-type plants?
  • What other tools are available on the Web to do similar jobs?
  • How is your correlation tool different from clustering?
  • Why do you use Affymetrix probe IDs as the input for the correlation analysis rather than the AGI codes?
  • What's the difference between the Affymetrix ATH1 and AtGenome arrays?
  • There is much more NASC array data available than you've used in your database; why have you not used it all?
  • Why have you only used NASC/GARNet array data and not other data sets, such as the Stanford microarray data?

    Up to top