I used “S2fid_abundance_table_all_samples_submit_2_expressanalyst.txt” from Seq2Fun 2.0.5. But it generated errors.
I tried all types of Gene-level summarization just in case, but it did not work and made the same error as the screenshot
It appears that you try to upload a single gene expression table, but using the multiple expression tables interface?
If this is the case, please read our tutorials first
If this is not the case, please follow our post guidelines
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Which tool and which module
Multiple expression tables -
Provide a copy of your data
Attached
data.csv (2.9 MB) -
If it is about raw data processing, please describe how the data were collected (instrumentation, etc).
Using Seq2Fun v2.0.5 with parameters “–mismatch 2 --minlength 19 --minscore 80 -w 4 --profiling -V”
As your data is indeed a single table, have you tried the single gene expression module?
If this is unclear, read the tutorials posted above
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!
Hello Sun,
I have fixed the issue with data upload, you can try again.
Guangyan
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.
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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 and sorry for many questions.
Dear Sun Woo,
The issue should be fixed now, there were some bugs related to seq2fun id mapping in the meta-analysis module.
Guangyan
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.
Yes, the matters were addressed.
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?
Hello Tart0,
I have removed a function by mistake in the last update. I am updating the server in 5mins, it will be fixed.
Guangyan
1 Like
Ok thank you for the quick reply, looking forward for the update!
May i know why is this a problem
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.
Have you specified the right gene id type to annotate your data?