iPathwayGuide Frequently-Asked Questions

1. Prepare a list of genes with a header “Symbol”, in one single column. Please use HGNC/MGI symbols only.
2. You can use in-built reference background gene set, or a custom background gene set for enrichment analysis
3. If you opt for enrichment with custom background gene set, prepare of list of background genes, with a header “Symbol”, in one single column. Please use HGNC/MGI symbols only.
4. In user dashboard, click on “Analyze a new experiment”
5. Intake form loads and in intake form, select “Only my genes of interest/DE genes” under “What data would you like to analyze” drop down menu
6. Select appropriate organism and Data type
7. Upload the input file by clicking on “Choose file” and select file prepared in step 1
8. Uploaded data is displayed in file content preview.
9. Under “Gene symbol” column, select the column with genes (gene symbols) with header “Symbol”
10. Click on “select the reference type” drop down menu
11. If you want to use custom background, follow steps 13 to 16. If you want to use an in-built reference gene set, follow step 12.
12. To use the in-built reference gene set, click on “all genes/proteins in the transcriptome/proteome” available under “select the reference type” drop down menu and skip steps 13-16.
13. To use custom background, click on “a custom set of genes” available under “select the reference type” drop down menu.
14. Click on “Choose file” available under “Upload reference file (Mandatory)” to upload custom background gene set. Upload file prepared in step 3.
15. Uploaded data is displayed in file content preview.
16. Under “Gene symbol” column, select the column with genes with header “Symbol”
17. Click on upload and proceed with analysis.

The report is deprecated” message is there to inform you that the report is not based on the latest knowledge available. If you choose to update the report, the analysis is done again, from scratch, with the latest version of all annotations. If you do that, your new, re-analyzed results will reflect the most up-to-date knowledge. We recommend that you update your analysis results for all the data sets that you care about or work on. If you choose not to update, you can have access to the deprecated report by clicking on the little “i” symbol (for information) on the very right of the report. That will open a window showing you all previous versions of your analysis results. You can access any of them by clicking on the date.

You can find a more detailed explanation with screen captures in our FAQ: https://advaitabio.com/product-support/ under “How do I find a deprecated analysis?”

Of course, you are allowed to publish any and all figures from our software. That’s the whole point. The software is meant to create figures and give you results that can be directly published so you can save time and be more productive.

We would kindly ask that you either maintain the “(c) Advaita Corporation 2022” in the figure, or mention in the caption something like “Figure obtained with iPathwayGuide (AdvaitaBio)”. Just mentioning the software in the Methods would not be sufficient since it would not be clear what figures where produced with it.

I would like to take this opportunity to remind you a couple of things:

1. we are here to help if you need any help with the Methods section or even if you have any questions from the reviewers about anything to do with our analysis.
2. many figures can be customized in terms of content, order, etc. Some figures can be customized for colors, as well. Please let us know if you want us to show you how to do this.
3. once the paper is published, if you let us know, we may be able to highlight your research in a short piece that we can send to our mailing list. That will greatly increase the visibility of your research.

Regarding the figures, you need to download them in .SVG format from iPathwayGuide. Any downloadable figure in our software can be downloaded as SVG. The SVG is a scalable vector format that can scale to any size and offers perfect resolution. Since we are talking about images, please keep in mind that you can customize most figures. In some, you can even select the colors. In many, you can select which genes to include and in which order. Please contact us if you have any questions about these capabilities or if you want to have a short meeting to show you how to do any such customization.

The basics are always the same regarding of the assay. The first step is to map the results of your assays onto genes. The assay can be very different but in most cases you can map the results on genes. For instance, for a methylation assay, you could associate each differentially methylated region to the gene immediately downstream of it. There will be some that won’t be mapped, but most areas that have an effect on transcriptional control are expected to be mapped correctly. Then you calculate an effect size. that can be a log fold change of differential expression or differential protein abundance or methylation, etc. It is often possible to calculate a p-value, as well. Once you have genes, effect sizes, and p-values, you can upload this in iPathwayGuide. You should specify the type of assay the data came from so you can do a meta-analysis later integrating multiple types of data, if those additional data become available.

iPathwayGuide supports directly human, mouse and rat. For other organisms, you need to first map your genes to orthologs. Many of our users have done this very successfully.
Here is an example in which iPathwayGuide was used to make important discoveries involving mackerel and sardines:

Transcriptomic analysis of short-term 17α-ethynylestradiol exposure in two Californian sentinel fish species sardine (Sardinops sagax) and mackerel (Scomber japonicus).

When you complete and publish your research, please share it with us. We will be happy to make your research more visible by sharing it with our users.

The answer here is very similar to the one above. When you change the organism, the annotations will be different. This would be a totally different experiment basically. This is an additional reason for which this has to be a different analysis.

When you change the p-value, the number of differentially expressed genes will change. That in turn, will change every single results in every single type of analysis performed: GO terms, pathway, upstream regulator, drugs, mechanisms, etc. The results will be an entirely different from the results before. Hence, this will be a new analysis. A good thing to do is to analyze your data with a couple of different thresholds and then do a meta-analysis of the results. this way, you will be able to tell whether your conclusions change depending on the threshold used. Obviously, you would place more trust in findings that remain the same regarding of the threshold used.

On the Pathways tab, on the right hand side, “pathway details” then “Gene table” then the “+” sign. When you click on that, you will see a table with the genes on the pathway. there you can sort, search for specific genes, etc. You can also download the entire table with the usual download icon.

On your dashboard, you can click on the little shopping cart and then click on “purchase with balance.” The report will become available right away.

When one shares a report with somebody else, the recipient gets a link and they will be able to access the report and do everything that the owner can do. The owner has the opportunity to decide whether the recipient is allowed to share the report further. Once the recipient clicks on the link they will be sent to the application to accept the share; they will then go into their account and click the accept share button. Once the link has been used it cannot be reused. So if a recipient of a share forwards the email to somebody else, the second person will not be able to see the report. This is by design so data cannot be shared without the permission of the owner. Also, if one clicks on the same link more than once, the second time, the link will not work.

Please make sure your are using the “…gene_exp.diff” file that comes from CuffLinks. There are some applications that claim to emulate CuffDiff output (e.g. Galaxy). If you are using one of these applications, please make sure the output file has all columns populated. See below for specific columns that must be present. Also, use this link to view the Cuffdiff manual.

It is a great idea to use the software and explore the capabilities before making a purchase. The way to do this is to create a free account on our web site www.advaitabio.com. Once you create an account, you will have full access to several analysis results. These datasets cover a range of experiment types, conditions, and analysis outcomes. You will be able to fully use the software to explore these data sets in whichever way you choose. You will have full access to interact with all of the demo analyses and experience all of the features of iPathwayGuide. We also provide sample data files, which will show you some of the formats that can be used to upload data for analysis.  An alternative would be to setup a time and let one of us to show you around the software. You will learn more in a much shorter time, and you will also be able to get immediate answers to any questions you may have.

We report the ‘Creation Time’ based on Coordinated Universal Time (UTC).

iPathwayGuide is designed to work with all the latest major browser platforms:

• Google Chrome
• Mozilla Firefox
• Apple Safari (Mac only, iOS not supported yet)
• Microsoft Internet Explorer 11 – Some image download capabilities may not function​​

Yes. From the login menu, click reset password. You will receive an email with the new password.

A list of databases and versions is available from within each report. See our Release Notes to see the latest data.

Citing iPathwayGuide

Using Advaita Bio’s products or content for any form of publication (e.g. print, electronically) requires researchers to cite them. Please use one of the options below for citations:

GEO2R does not perform normalization for Affymetrix CEL files. The Advaita iPathwayGuide CEL file uploader currently utilizes the Gene-chip Robust Multi-array Average (GCRMA) normalization method. As such, there can be discrepancies between CEL files processed with GEO2R vs. iPathwayGuide.