Hi there,
Could anybody tell me why my bigwig file can’t be opened in UCSC browser, but only visualized in IGB or IGV? I know how to open the file in IGB, but personally I just feel the display in UCSC genome browser is way clear.
Sherry
Hi @Sherry
Hopefully I can explain how this works!
Some background
UCSC can only display data that is based on a reference genome assembly that they already host. These assemblies have a dbkey key. That same label can be used in Galaxy for the database key. When these “match”, a link to UCSC will be available. The key represents a fasta index, the string of bases on the underlying assembly. Mapping data has coordinates for positions on that assembly – this is what the display is showing in a graphical way.
Practical usage in Galaxy
Mapping tools will assign the database automatically for you when you use a built-in reference genome assembly. If that built-in reference was originally sourced from UCSC, then the links to UCSC are available.
When UCSC is not available, you can use the other display applications, and IGV in particular is a common choice.
There are a few ways to use IGV that I can explain, or you can search this forum with IGV or see igv. You can use it inside of Galaxy or with a local IGV. If just one file, and you don’t need the reference bases, this is automatic. If you have multiple files, or do want the reference bases, then you’ll need to set up your custom genome within IGV and Galaxy can communicate with it through your custom dbkey/database assignment on the data (we call this a custom-build).
With that context .. how do you plan to view your data? One file? Multiple? What is your custom reference genome? Where did you source it?
Thanks and let’s start there! 
Hi Jennaj,
Thank you so much for your excellent explanation to my question. However, I am still a little confused.
As in the screenshot I sent, my data clearly indicates that it’s a binary UCSC bigwig file, but why it can’t be displayed in UCSC genome browser in the galaxy.
To reply to your other questions, this data was sourced from a paper’s data set published online. The reference genome they used was mouse NCBI37/mm9. Again, I believer UCSC host this mouse reference genome in its database. I do want to open multiple chip-seq files other than the one I showed here and eventually I want align all of them together with the same reference genome to differentiate the binding patterns within different transcription factors. What would be a good visualizing tool for me to do that job?
Tnx again for your kind help!
Sherry
Hi @Sherry
Thanks for explaining more! Very helpful!
If you are certain that your uploaded data is based on the NCBI37/mm9 reference genome build, you can directly assign that database key to your dataset. This is what informs Galaxy that your data is based on this assembly, and the associated underlying fasta index, allowing the link to UCSC to then show up!
How to do this. → FAQ: Changing database/build (dbkey)
In short, click on the ? icon here on your dataset then adjust the Database/Build field to be mm9 and save.
Please let us know if you can get this to work!
Thank you Jennaj, It worked! After I changed the database key to be mm9, I can visualize the track in UCSC gennome browser now.
Sherry
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Hi Jennaj,
I have another question to ask you, hope you don’t mind. I need open multiple chip-seq bigwig files from different transcription factors and align them like lining up DNA sequencing results to find out their binding similarities inside mouse genome. Is there any way I can do that in UCSC genome browser?
Tnx again!
Sherry
Hi @Sherry
I’m glad you have the UCSC visualizations working now!
Then, for this part:
UCSC isn’t used to generate new data tracks this way.
Instead, you can do the data comparison in Galaxy! Since you already have the bigwig files, I would suggest looking at the deepTools group to start with. Go to the tool panel and scroll down to find the section. Or, better, click into Discover Tools at the top, then type in the keyword “deeptools” since that will also bring up some related tools.
You can also explore more by tool groups (example “chip-seq”), datatypes (example “bigwig”) and categories (EDAM ontologies are still being curated by the wider bioinformatics communities but you can try!).
Most tools link out to the documentation from the authors down in the Help second on the tool forms. This is the direct link for the tools I’m suggesting to make it faster. These will work in Galaxy the same as described here since all is based on the same original tool. If you find a command line flag you want to apply, it should be on the form, and you may need to expand some of the nested sections before using your browser find function for the search.
Then, once you have results from this next layer, you can also visualize any new coordinate-based data at UCSC. Be sure to review at UCSC the concept of a Session. This allow you to group together data tracks, save genomic positions, add in notes, generate share links and more.
Your Galaxy history share link, along with the UCSC session share link, can make collaborating on projects, and later publishing the project, much faster since everyone is reviewing the exact same data all with the same context.
Hope this helps!
Thank you Jennaj for all the information you provided. I will try it and let you know how it turns out. Really appreciate it!
Sherry
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