Is it possible to visualize overlaps using co-ordinate datas ?
I’ve tried many ways to do it using venn diagram,bar graph etc
I did use the venn diagram using lists tool but i cannot get the Id’s for my co-ordinates
ive tried the intersect tools to create the dataset but can’t seem to reach an output
Are there any tools which will allow me to do so , and it’d be helpful if there are any tutorials present on it .
my files are in bed format
Hi Monish,
If you have a paper with a figure you like, can you use the same approach.
It is unclear what kind of visualization do you want and what data do you have. Do you want positions on chromosomes or summary? If summary, what do you want to see? Proportion of overlapped and non-overlapped intervals in two bed files in nucleotides or something else, for example, proportion of intervals in set A overlapping with intervals in set B? Do you have overlapped intervals in a single set? If intervals do not overlap within a dataset, maybe try any intersect tools, get length of overlap, calculate total length of intervals in set A and B, calculate length of non-overlapping regions, e.g., length A minus length of overlap, and plot two non-overlapping values and overlap in-between.
IMHO, description of data and desired output is not sufficient for better recommendation, bun once you produce a better description of desired output, you’ll figure out steps required for it.
Kind regards,
Igor
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Hi @Monish_V , as @igor stated we would like to help you, but it isn’t quite clear what this data represents and what your final goal is (what story you want to tell with the final graphics).
Then, it seems you are running into tool errors of some sort. Maybe troubleshooting these is where to start, to get you past the technical problems? Getting a peek at your data will also help us to help you! This guide explains how to share you work for feedback → How to get faster help with your question
Finally, to build on what @igor already suggested, for this part:
What do you mean by “IDs for coordinates”? If these are genomic coordinates, and you want to label them, it is pretty common to simply use the name of the genomic strand and the coordinates as the label plus maybe the strand – all of these put together can create a descriptive naming label you can use for the “ID”. It is also common to compare one set of coordinates to other types of coordinate-based information to label by inheritance.
Example of the latter: Given a specific genomic assembly (string of nucleotides), a sequencing read aligns to coordinates A and a gene’s footprint has coordinates B. When coordinates A and B are compared, and found to have sufficient “overlap”, it can be stated that the sequencing read was likely derived from a transcript associated with that gene. The transcript label, gene label, and higher order annotation like ontology can then be associated that read. Later on, these associations can be “counted up” and scientific conclusions made.
Most genomic analysis involves some version of that example. We can help to troubleshoot but the subject is very broad! We’ll need to know a bit more about what you are doing to make suggestions about how this is usually done for the kind of data you have. Real data helps for this, which is why we suggest sharing – all the details are included with just one link and you can unshare after.
Then, for this result
Was this a tool error? Or maybe an inconclusive or unexpected result? We can help with troubleshooting both, or at least enough for you to (probably) be able to eliminate technical issues.
We have some short help here if you are not sure where to review the your job logs, full error messages, and related details.
Resources
You can also explore on your own! Hopefully you have found the GTN Tutorials already but if you haven’t, the resources are located here. This is the same place the 
icon at a public Galaxy server will open to.
Then, when you are new to Galaxy, or just would like an introduction to some common manipulations for a new analysis domain, go into the Learning Pathways area here.
Learning Pathways- The first pathway will likely be of interest to you: Learning Pathway: Introduction to Galaxy and Sequence analysis
- Why? Because the second tutorial is comparing genomic coordinates between different annotation features followed by some summaries, plus visualization in a genomic browser. This seems close to what you are doing now.
The only other item I would suggest is to explore the Visualization tab in the side Activity Bar. You’ll find many more visualization tools and most have sample data you can load up to see how each works. So, maybe start up a new history to load the examples into, and explore if you are looking for novel ways to graph the data you already have.
Hope this helps! 