TFNetPropX: A Web-Based Comprehensive Analysis Tool for Exploring Condition-Specific RNA-Seq Data Using Transcription Factor Network Propagation
Round 1
Reviewer 1 Report
In this study, Moon et al, present TFNetPropX, a user-friendly web-based platform to perform gene-level, gene-set-level and network-level analysis of RNA-seq data under two different conditions. It is very interesting study and represent important platform for network-level analysis of RNA-seq data. But few studies need to be addressed
1. In step 1 I think some parameters are missing and may come with false positive results. More parameters are needed to be added
2. Why user specifies th p-value, what is the logic behind that. This value is important to show significant expression changes
3. If the user is not familiar with the threshold of the parameters, what will happened then.The author should define the threshold to the user and its effect on overall results
4. RNA sequence data is different in different diseases. How can we use this tool to find out RNA sequence data for a specific disease. How it is user friendly in this case.
5. Why p value 0.15 is selected as mentioned in case 1 results
6. The author has given only one reference to support their predicted analysis with previous studies. Add more references to support your studies.
7. In case study 2 the author has taken p value 0.005. Will this value affect the overall results of the selected genes
Comments for author File: 
Comments.pdf
Author Response
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Author Response File: Author Response.pdf
Reviewer 2 Report
The article entitled “TFNetPropX: A Web-Based Comprehensive Analysis Tool for Exploring Condition-Specific RNA-Seq Data using TF Network Propagation” is very well written. The tool surely help the researchers working in the field of transcriptomics and Network biology. Some suggestions/comments are given below for authors:
If possible, authors should avoid using abbreviations in the title (e.g., TF).
Abbreviations should be explained when appear first time.
It would be better if authors clearly mention (e.g., in abstract) that the current version of TFNetPropX dealing in human or mouse only. Have the authors planned to add more species in the database in future? If yes, it could also be mentioned with an approximate time.
I couldn’t find any manual on the homepage of TFNetPropX describing all the terms used in the manuscript. For example, how the users will get to know what thresholds values are need to be selected? What are log2FC p-values and how and on what basis users should select these values?
If possible, the authors can add/give an example on the TFNetPropX homepage which can help users how to use the tool and what type of results they will get (along with some interpretation of example results).
Author Response
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Author Response File: Author Response.pdf
Reviewer 3 Report
This manuscript introduces a novel online tool designed to streamline the intricacies of RNA-seq data processing, substantially cutting down the time required for analysis. In essence, this website holds promise for researchers seeking efficient RNA-seq data analysis solutions. However, it is important to note that there remain certain queries and concerns that warrant the authors' attention and resolution before publication.
1. In this manuscript, the authors assert that the website is designed to facilitate the analysis of RNA-seq data, with a specific focus on raw count matrices as the input, rather than raw sequencing data. In such a scenario, users are responsible for conducting quality control, trimming, mapping to reference genomes, and read counting independently. It may be more accurate to characterize this website as a tool for analyzing and visualizing count matrix data, rather than categorizing it as a tool for RNA-seq data analysis.
2. While it is encouraged to archive sequencing data in public repositories for the benefit of the research community, ensuring the privacy of data before publication is a significant concern for scientists. Therefore, it would be advantageous if the website could offer a "Terms of Service and Privacy Policy" to address this aspect and provide clarity on data privacy and usage.
3. In Line 157-158, there should be 20 top genes labelled while in Figure 2 and Figure 5, only 10 and 13 genes are labeled with gene names, respectively.
Author Response
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Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
The authors have sufficiently improved the manuscript and answered all questions.
Reviewer 2 Report
The authors have significantly improved their article as per reviewers' suggestions and recommendations.
