Where do the data come from?

CressExpress includes data from all ATH1 (GPL198) microarrays that had CEL files deposited in the Gene Expression Omnibus at the time we collected the data. The data shown in Release 4.0 were harvested in fall of 2013. After obtaining the CEL files, we processed them using tools from the BioConductor suite. CEL files were processed using RMA, which included probe level quantile normalization and log (base 2) transformation.

How do you measure co-expression?

CressExpress calculates Pearson's correlation coefficient using expression data harvested from publicly-available microarray data. When you enter a list of query genes, the tool looks up the corresponding probe set ids and then compares your query's expression values to expression values for all probe sets.

Which queries should I use? Probe set ids or gene ids?

Probe sets are just a collection of probes on the Affymetrix array that measure expression of a target gene. Because the labeled, sample RNAs are anti-sense with respect to the target gene, the probes themselves precisely match the sequence of the target gene. Because most genomes contain many duplicated sequence segments, many probe sets are non-specific and can interrogate more than one gene. And of course, some genes are not represented on some array platforms; it depends on when the gene was discovered, when the array was designed, and other factors. For these reasons, we strongly recommend using probe sets ids, rather than gene ids, as inputs to the co-expression analysis tool. However, if you prefer to enter gene ids, the tool will attempt to match gene ids you entered with probe set ids and expression values. Regardless, the tool output will report a pairing between target gene ids and probe set ids. We get these from Affymetrix or from the TAIR Web site.

How do I search for experiments?

If you know some keywords that describe an experiment, you can use them to search for experiments. When you enter keywords, a search is initiated which looks up those keywords in the title or the summary of the experiments stored in the database. If a match is found, that experiment is added to the search result and finally the results of search are returned. -What is PLC (pathway-level co-expression) analysis? PLC identifies genes and probe sets that are co-expressed with all or some of the query genes/probe sets you entered in Step 2. PLC and how it works is described in detail in Wei et al. [ PMID: 16920875 / DOI: 10.1104/pp.106.080358 ]PLC uses the output from the co-expression linear regression analysis to identify probe sets and target genes that are co-expressed with two or more of your query genes. PLC then reports these co-expression partners in order of the number of query genes with which they are co-expressed and, then, to break ties, in order of average r-squared values.

In essence, PLC analysis identifies the part of the overall co-expression network that directly neighbors two or more of your query genes or probe sets. The co-expression tool doesn't actually compute the entire network; it knows enough about the network to find the shared neighbors for all your query genes.

Why do I need to enter my email in Step 5?

CressExpress analyses will typically take a few minutes (possibly more) to finish. When your analysis run completes, the tool will send you an email with a URL telling you where you can obtain your results files.