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GIGSEA #720

Closed zhushijia closed 6 years ago

zhushijia commented 6 years ago

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bioc-issue-bot commented 6 years ago

Hi @zhushijia

Thanks for submitting your package. We are taking a quick look at it and you will hear back from us soon.

The DESCRIPTION file for this package is:

Package: GIGSEA
Type: Package
Title: Genotype Imputed Gene Set Enrichment Analysis
Version: 0.99.0
Author: Shijia Zhu
Maintainer: Shijia Zhu <shijia.zhu@mssm.edu>
Description: We presented the Genotype-imputed Gene Set Enrichment Analysis (GIGSEA), a novel method 
    that uses GWAS-and-eQTL-imputed trait-associated differential gene expression to interrogate gene set 
    enrichment for the trait-associated SNPs. By incorporating eQTL from large gene expression studies, 
    e.g. GTEx, GIGSEA appropriately addresses such challenges for SNP enrichment as gene size, gene boundary, 
    SNP distal regulation, and multiple-marker regulation. The weighted linear regression model, taking as 
    weights both imputation accuracy and model completeness, was used to perform the enrichment test, 
    properly adjusting the bias due to redundancy in different gene sets. The permutation test, furthermore, 
    is used to evaluate the significance of enrichment, whose efficiency can be largely elevated by expressing 
    the computational intensive part in terms of large matrix operation. We have shown the appropriate type I 
    error rates for GIGSEA (<5%), and the preliminary results also demonstrate its good performance to uncover 
    the real signal. 
License: LGPL-3
Encoding: UTF-8
LazyData: true
Depends: Matrix, MASS, locfdr, stats, utils
Suggests: knitr
VignetteBuilder: knitr
RoxygenNote: 6.0.1
NeedsCompilation: no
biocViews: GeneSetEnrichment,SNP,VariantAnnotation,GeneExpression,GeneRegulation,Regression,DifferentialExpression
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LiNk-NY commented 6 years ago

Hi Shijia, @zhushijia Thank you for your submission. I will be reviewing your package later today. Best regards, Marcel

zhushijia commented 6 years ago

Hi Marcel,

Sounds great! Thank you very much for your help!

Best Shijia

lgeistlinger commented 6 years ago

Hi @zhushijia

I guess @LiNk-NY will give you some more formal feedback on code and implementation practice, I rather took a look into your DESCRIPTION file and your vignette.

It seems as if you have implemented useful functionality for gene set analysis of GWAS data, but from your documentation / vignette it's currently hard to understand what you did exactly.

** Description

Resembles an Abstract of a scientific article. For a software package, you typically want that to be more compact and generally comprehensible. Good practice is a sentence on background, 1-2 sentences on what you have implemented, and a sentence how this integrates with existing functionality. A good example is the Description field here: http://bioconductor.org/packages/MultiAssayExperiment

** vignette building instructions are needed in yaml header of Rmd file

** Abstract: *** Many specific undefined terms, e.g.

*** Your grammar also indicates that you are having a manuscript somewhere but a reference is missing:

*** Appropriately addresses such challenges for SNP enrichment as gene size, gene boundary, and multiple-marker regulation? (Why is this challenging and how does it address that?)

** Quick start:

*** Linking

https://cloud.hakyimlab.org/static/img/PrediXcan-GWAS-Summary-PrediXcan.png

here would give some context and help users to understand what you are talking about.

*** It's not a good idea to comment the command in your quick start. That's basically an eval=FALSE chunk and undermines the reproducibility of your vignette (see http://bioconductor.org/developers/package-guidelines/#vignettes). In your case, I would also clearly separate functionality based on MetaXcan (thus relying on external software) from your subsequent enrichment analysis, and not combine this into one step.

*** I like the distinction between discrete and continuous gene sets and their representation in sparse matrices

*** User self-defined gene sets --> user-defined gene sets

*** Section 5.1: it's basically unclear what you do here. Again, do you have any manuscript here that you can refer to or can you refer to the literature for similar approaches? If not, explain in more detail what you do.

** link or include cited references in vignette

zhushijia commented 6 years ago

Hi @lgeistlinger

Thank you very much for your comments. All make sense. I will try to address. :-)

Best wishes Shijia

LiNk-NY commented 6 years ago

Hi Shijia Zhu, @zhushijia Thank you for your submission. Please see the review for GIGSEA below.

If you have any questions please post them here. Thanks! -Marcel


GIGSEA #720

README.md

DESCRIPTION

NAMESPACE

R

Minor:

vignettes

vignette: >
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteIndexEntry{GIGSEA: Genotype Imputed Gene Set Enrichment Analysis}
  %\VignetteEncoding{UTF-8}

inst/NEWS


LiNk-NY commented 6 years ago

Thanks Ludwig @lgeistlinger for the scientific content review! :+1:

zhushijia commented 6 years ago

Hi LiNk-NY @LiNk-NY

Thank you very much for the detailed comments. I will try my best to address them.

Best wishes Shijia

LiNk-NY commented 6 years ago

Please bump your package's version for another build in the BBS/SPB. Thanks, Marcel

LiNk-NY commented 6 years ago

Hi Shijia,

Please respond to the review and push your changes. Otherwise I will have to close the issue within 2 weeks.

Thank you for your attention.

Regards, Marcel

zhushijia commented 6 years ago

Hi Marcel,

I apologize for the late response. I was wrapping up the corresponding paper recently, and eventually submit it. I will address the comments and respond quickly.

Thank you so much for your patient help.

Best Wishes Shijia

On Fri, May 18, 2018 at 11:15 AM, Marcel Ramos notifications@github.com wrote:

Hi Shijia,

Please respond to the review and push your changes. Otherwise I will have to close the issue within 2 weeks.

Thank you for your attention.

Regards, Marcel

— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub https://github.com/Bioconductor/Contributions/issues/720#issuecomment-390239596, or mute the thread https://github.com/notifications/unsubscribe-auth/AFKtsZPEqbQRxEGQSn78j3kh7ceOSyH7ks5tzuWCgaJpZM4TPAoV .

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bioc-issue-bot commented 6 years ago

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