Thank you for your quick response. I did the single expression module for this one and it worked well. I wanted to do the multiple module with my three tables which have the same form as the uploaded table. I could not figure out the differences between mine and examples from the tutorial. I thought that I used many ‘single tables’ on the multiple module.
In addition, I wonder that others work well with data using Seq2Fun Ortholog ID as ID type.
Please let me know. Thanks again.
Below is an example dataset on the multiple expression module of ExpressAnalysit, which I could not come across differences from mine.
It looks like we introduced a bug to the meta-analysis module when we updated ExpressAnalyst in the last few days. I just tried directly uploading the example data (three tables, model organism, Entrez ID) and I get the same error as you. It was working about a week ago. We will fix the bug and let you know when it is updated!
Thank you for the maintenance. Unfortunately, another error occurred. I am not sure why the below content is an error. Is there a restriction of feature numbers in the multiple expression table? The number of your example’s features is 4498, and there is no error.
Here is the information, followed by post guidelines.
Which tool and which module
ExpressAnalyst-Multiple expression tables
Provide a copy of your data
Attached test2.txt (1.4 MB) test1.txt (1.4 MB)
(FYI, The upload datasets were aligned by Seq2Fun 2.0.5 locally and normalized through the online version of Expressanalyst using Single Expression Module. )
Thank you for letting me know. I am wondering if the matter is able to be addressed. If you don’t have enough time to handle it, I would like to explore alternative options. Thank you.
Thank you very much. It is currently functioning effectively. I have an additional query. Is there a specific rationale for limiting the number of datasets to 10 for the multiple expression module? In the event that I have more than 10 files to process, what would be the recommended course of action?
It is partly because very large analyses slow down the server, decreasing the performance for the many other researchers who are using it at the same time. Another is that some of the visualizations are not meant to handle this many datasets. The legends get very large, they look bad, and need a long time to load.
We make the R code from ExpressAnalyst available as the ExpressAnalystR package (there is a tab on the website). You may have to modify the code a bit to make it work well for many datasets, but this is how I would approach it.
For your context: I sent the 1st file first and able it able to identify the #Sig immediately and able to run with the ID type. Suddenly as I sent the 2nd it doesnt detect it, so i resend the same file as the 1st it completely have the same problem
