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Although Reviewer 3 still has a comment on your system, I think it can be published in PeerJ Computer Science now.
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The author only add the download page. The author do not provide any further customized or analysis functions.
I still think IncOnco is a bit too rough.
Please find attached the re-reviews from all 3 reviewers.
Please revise your manuscript according to the comment 2 from reviewer 1: Synonymous gene name search is a basic function for bioinformatics web tools and so should be added to OncoLnc. I note that your rebuttal stated that you will work on this, but it should be added before this paper is published.
Based on Review 2's comments, please revise your manuscript to include some of the examples you provided in the rebuttal letter
According to Reviewer 3 comments, please improve and add more functions to explore the survival correlation data of interest.
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1. In the response letter, author mentioned they will provide links for downloading Table S1-S3 in OncoLnc website. However, I can’t find it in OncoLnc.
2. Synonymous gene name search is the basic function for bioinformatics web tools. Please add this feature in OncoLnc.
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Minor Comment:
The author has given some examples in his rebuttal letter. I suggested the author to add these examples in the main text to support OncoLnc.
Yes, the users should know what they would like to query. However, in biology research field, there are lots of alias for genes and other biomolecules. A function to list the possible alias for the queried item is definitely not useless. The author has reminded the users what kind of ID they should use. This function would be helpful. However, the author made this information as superscript. If the author could put this information in the query box, it will be easier to be noticed by the users.
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lncOnco provides the results of precomputed survival analyses. The author also curated the ID and gene symbol of mRNA which is a great and hard work. Researchers can use IncOnco to explore the gene of interest. However, I think IncOnco is a bit too rough.
The author claims OncoLnc is the only data portal that allows for simple download of the clinical data and expression data. I assume that the target users of IncOnco are the researchers who are lacking the programming skill. Therefore, the website should add more functions for them to explore the survival correlation data of interest. For example, the information of all supplementary tables can be searched and downloaded from website. Providing the customized download, such as the specific cancer of interest, also would be useful for those researchers to perform other analyses further, especially for lncRNA.
This web tool is useful, but the manuscript needs to be improved. Please revise your manuscript according to the reviewers' comments.
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This work developed a web tool, named lncOnco, which systematically and comprehensively calculate the correlation between mRNA, lncRNA, and miRNA expression and survival rate in cancers from TCGA. This is a valuable tool for researchers lacking programming knowledge to access the TCGA data and look for the genes associated with prognosis cross all cancer types. The manuscript is generally well written and clearly presented. I have just a few suggestions on this work:
1. Table S1-S3 should be a part of this tool. Please add these information into system and design an interface for users to view, access, and query.
2. I can’t find any link or button back to main page or search page. It is not convenient if I would like to start a new search.
3. It is unable to search using synonymous gene names (e.g. TP53 and P53). I think this function is required because some synonyms are more familiar to biologists.
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There is no evaluation of the survival-associated biomolecules the OncoLnc identified. The author should at least enumerate several examples to discuss the importance of the identified survival-associated biomolecules in cancer(s). This is useful to convince the users that the biomolecules identified by OncoLnc are reliable.
1. So far, OncoLnc only provided continuous data for cox model. However, some biomolecules affected cancer(s) only when their expression level exceeded a certain cut-off. The author may consider to add one function which allows the user to use the categorical input for cox model. For example, users could choose the median (50%) of the expression profile of the studied biomolecule to run the cox-model.
2. The author must add more information to describe the method applied to OncoLnc. For example, the concept of cox model. In other words, a well-described manual is required.
3. The author should add a return bottom in the result page. Or, they should put the query function in the result page.
4. In the result page, the sorting function for each column.
5. When a user input an item which doesn’t perfectly matched any item in OncoLnc, the OncoLuc should list some similar items to the user.
The background and introduction of this article are not sufficient to clarify the motivation for OncoLnc development. The author hopes OncoLnc can facilitate users to survey the survival correlation with mRNA, miRNA and LncRNA by using TCGA clinical data. However the importance, relevance and previous studies of three kinds of data in survival study were not mentioned and compared.
Many details were not described or unclear in method, especially for statistical analysis. First, the survival analysis is the most important part in this study. The author did not mention how to select the variables used in each data type. Second, in survival analysis, not all patients have the clinical parameters which used in cox regression model. The way of dealing with this kind of data should be detailed. Thrid, the datasets used in this study need more details, including original sources and appropriate citations.
Three kinds of datasets, mRNA, miRNA and LncRNA, were used in this study. However, their importances were not addressed, as well as the motivation for using these datasets. In addition, the author performed survival analysis for each tumor type and each data type. Different kinds of data were pieced together into OncLnc. It would be better if OncLnc can provide the analysis or pre-calculated results to integrate the different data types and tumor types. It can give the researchers an insight into biomark selection survival analysis.
I suggest that the motivation and background should be improved. The website can value-added more functions, such as custmized analysis, instead of pre-computed resluts.
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