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netDx #1149

Closed shraddhapai closed 4 years ago

shraddhapai commented 5 years ago

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bioc-issue-bot commented 5 years ago

Hi @shraddhapai

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: netDx.examples
Title: Companion data package to netDx
Version: 0.99.0
Author: c(person("Shraddha", "Pai", email = "shraddha.pai@utoronto.ca", role = c("aut", "cre")),
    person("Philipp","Weber",role="aut"),
    person("Ahmad","Shah", role="aut"),
    person("Shirley","Hui",role="aut"),
    person("Ruth","Isserlin",role="aut"),
    person("Hussam","Kaka", role="aut"),
    person("Gary D","Bader",role="aut"))
Authors@R: c(person("Shraddha", "Pai", email = "shraddha.pai@utoronto.ca", role = c("aut", "cre")),
    person("Philipp","Weber",role="aut"),
    person("Ahmad","Shah", role="aut"),
    person("Shirley","Hui",role="aut"),
    person("Ruth","Isserlin",role="aut"),
    person("Hussam","Kaka", role="aut"),
    person("Gary D","Bader",role="aut"))
Maintainer: Shraddha Pai <shraddha.pai@utoronto.ca>
Description: Companion data package to run vignettes for netDx.
Depends:
    R (>= 3.6)
Suggests: netDx
License: MIT
LazyData: false
RoxygenNote: 6.1.1

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bioc-issue-bot commented 5 years ago

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IMPORTANT: Please read the instructions for setting up a push hook on your repository, or further changes to your repository will NOT trigger a new build.

bioc-issue-bot commented 5 years ago

Dear Package contributor,

This is the automated single package builder at bioconductor.org.

Your package has been built on Linux, Mac, and Windows.

On one or more platforms, the build results were: "ERROR". This may mean there is a problem with the package that you need to fix. Or it may mean that there is a problem with the build system itself.

Please see the build report for more details.

shraddhapai commented 5 years ago

AdditionalPackage: https://github.com/BaderLab/netDx

bioc-issue-bot commented 5 years ago

Hi @shraddhapai,

Starting build on additional package https://github.com/BaderLab/netDx.

IMPORTANT: Please read the instructions for setting up a push hook on your repository, or further changes to your additional package repository will NOT trigger a new build.

The DESCRIPTION file of this additional package is:

Package: netDx
Title: Network-based patient classifier
Version: 0.99.0
Author: c(person("Shraddha", "Pai", email = "shraddha.pai@utoronto.ca", role = c("aut", "cre")),
    person("Philipp","Weber",role="aut"),
    person("Ahmad","Shah", role="aut"),
    person("Shirley","Hui",role="aut"),
    person("Ruth","Isserlin",role="aut"),
    person("Hussam","Kaka", role="aut"),
    person("Gary D","Bader",role="aut"))
Authors@R: c(person("Shraddha", "Pai", email = "shraddha.pai@utoronto.ca", role = c("aut", "cre")),
    person("Philipp","Weber",role="aut"),
    person("Ahmad","Shah", role="aut"),
    person("Shirley","Hui",role="aut"),
    person("Ruth","Isserlin",role="aut"),
    person("Hussam","Kaka", role="aut"),
    person("Gary D","Bader",role="aut"))
Maintainer: Shraddha Pai <shraddha.pai@utoronto.ca>
Description: General-purpose algorithm to build a patient classifier from heterogenous patient data.
The method converts data into patient similarity networks at the level of features. Feature selection identifies
features of predictive value to each class. Methods are provided for versatile predictor design and performance
evaluation using standard measures. netDx natively groups molecular data into pathway-level features and connects
with Cytoscape for network visualization of pathway themes.
For method details see: Pai et al. (2019). netDx: interpretable patient classification using integrated patient
similarity networks. Molecular Systems Biology. 15, e8497
Depends:
R (>= 3.6),bigmemory,foreach,doParallel,combinat,BiocManager,GenomicRanges,knitr,htmltools,netDx.examples
Imports: ROCR,pracma,RColorBrewer,ggplot2,RCy3,caroline,glmnet,httr,igraph,reshape2
VignetteBuilder: knitr 
Encoding: UTF-8
License: MIT
LazyData: false
URL: http://netdx.org
RoxygenNote: 6.1.1
bioc-issue-bot commented 5 years ago

Dear Package contributor,

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bioc-issue-bot commented 5 years ago

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Your package has been built on Linux, Mac, and Windows.

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LiNk-NY commented 5 years ago

Hi Shradda, @shraddhapai

Can you say where the data are coming from for the "netDx.examples" data package? This could be TCGA data that is already available from other Bioconductor packages such as TCGAbiolinks, RTCGAToolbox, GenomicDataCommons, curatedTCGAData, etc.

Best, Marcel

bioc-issue-bot commented 5 years ago

Received a valid push; starting a build. Commits are:

2f7c512 moved to data 809b450 passes bioc checks

bioc-issue-bot commented 5 years ago

Dear Package contributor,

This is the automated single package builder at bioconductor.org.

Your package has been built on Linux, Mac, and Windows.

On one or more platforms, the build results were: "ERROR". This may mean there is a problem with the package that you need to fix. Or it may mean that there is a problem with the build system itself.

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bioc-issue-bot commented 5 years ago

Received a valid push; starting a build. Commits are:

4edf1bd removed suggested netDx package till accepted into...

bioc-issue-bot commented 5 years ago

Dear Package contributor,

This is the automated single package builder at bioconductor.org.

Your package has been built on Linux, Mac, and Windows.

On one or more platforms, the build results were: "ERROR". This may mean there is a problem with the package that you need to fix. Or it may mean that there is a problem with the build system itself.

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bioc-issue-bot commented 5 years ago

Received a valid push; starting a build. Commits are:

c5786a4 check related doc fix

bioc-issue-bot commented 5 years ago

Dear Package contributor,

This is the automated single package builder at bioconductor.org.

Your package has been built on Linux, Mac, and Windows.

On one or more platforms, the build results were: "ERROR". This may mean there is a problem with the package that you need to fix. Or it may mean that there is a problem with the build system itself.

Please see the build report for more details.

bioc-issue-bot commented 5 years ago

Received a valid push; starting a build. Commits are:

1aabffb errors related to stats/utils import cleared fa670a0 updated import 9c09d34 includes stats utils

bioc-issue-bot commented 5 years ago

Dear Package contributor,

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bioc-issue-bot commented 5 years ago

Received a valid push; starting a build. Commits are:

236622d updated author field

bioc-issue-bot commented 5 years ago

Dear Package contributor,

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Your package has been built on Linux, Mac, and Windows.

On one or more platforms, the build results were: "skipped, ERROR, WARNINGS". This may mean there is a problem with the package that you need to fix. Or it may mean that there is a problem with the build system itself.

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shraddhapai commented 5 years ago

@LiNk-NY Hi Marcel, some of the data in netDx.examples come from TCGA and some via other sources. None of these has been obtained from BioConductor. 1) There is a breast cancer example for which I have cited the paper in the corresponding man page (man/TCGABRCA.rd). 2) All data prefixed with KIRC come from the renal clear cell carcinoma data, but we obtained these from the PanCancer survival project. The paper for those data is referenced in the man page (e.g. man/KIRC_dat.Rd). 3) The medulloblastoma data comes from an individual study which also has been cited in the man page. Is this sufficient or should more information be added?

I have just committed major changes to netDx and netDx.examples. 1) I see that netDx fails a check on Windows. We are currently supporting only OS X and Linux systems. Will this be a problem? 2) netDx has WARNINGs regarding the use of set.seed. In all instances we have a user-settable parameter to ensure reproducibility of results, so I feel justified in using the set.seed() calls.

Thanks!

LiNk-NY commented 5 years ago

Hi Shraddha, @shraddhapai

It's great that you provide the source of the data but I still have a few questions with your submission:

  1. Why provide example data that is already available through Bioconductor resources? (see comment above) Why not re-use existing data resources as data examples?
  2. Being that you want to provide 'novel' example data, why not use an established Bioconductor class such as SummarizedExperiment to harmonize the representation?
  3. Your software infrastructure does not provide compatibility with SummarizedExperiment. Why is this the case?

Please read and follow the package guidelines as outlined here: https://www.bioconductor.org/developers/package-guidelines/

As it stands now, the package would require considerable work to get it into acceptable form. The package guidelines will give you an idea.

Best regards, Marcel

shraddhapai commented 5 years ago

Hi Marcel, Thanks for the feedback.

  1. The chief answer to your questions below is that this package was developed in the course of method development for a research article, and not from scratch for submission to BioConductor. The data we use for examples flow naturally from the work done in that paper. By mandating an update to the examples by spending time to familiarize ourselves with existing data packages, BioConductor is putting a high bar on research scientists attempting to make near-ready work available to the community at large. I have already spent considerable time conforming to BioC requirements via the check, build and BiocCheck utilities, and including examples with data that work. How necessary is the use of these pre-packaged data for BioC acceptance?

  2. Using a SummarizedExperiment sounds straightforward, if it is highly similar to the old ExpressionSet. From what I can see, only a few high-level methods need to change their input from using data.frames and matrices and putting them into lists, to using the SummarizedExperiment setup. This should be easy to do. Most internal methods don't operate on the entire dataset, only on pieces and subsets of it. Am I missing anything?

  3. In my daily dev work I don't use SummarizedExperiment. This classifier integrates data from multiple assays. I have used ExpressionSet in the past but not SummarizedExperiment because I wasn't aware of it and ExpressionSet only had a slot for one assay. I do routinely use GenomicRanges, because of the useful ability to perform operations on genomic ranges. This is why that data structure is used in the package. If I were to update the methods to use SummarizedExperiments, the doc would be accordingly updated too.

You mention at the end of your message that "considerable" work is required. What in particular were you thinking of?

Best,Shraddha

On Thu, Aug 1, 2019 at 5:08 PM Marcel Ramos notifications@github.com wrote:

Hi Shraddha, @shraddhapai https://github.com/shraddhapai

It's great that you provide the source of the data but I still have a few questions with your submission:

  1. Why provide example data that is already available through Bioconductor resources? (see comment above) Why not re-use existing data resources as data examples?
  2. Being that you want to provide 'novel' example data, why not use an established Bioconductor class such as SummarizedExperiment to harmonize the representation?
  3. Your software infrastructure does not provide compatibility with SummarizedExperiment. Why is this the case?

Please read and follow the package guidelines as outlined here: https://www.bioconductor.org/developers/package-guidelines/

As it stands now, the package would require considerable work to get it into acceptable form. The package guidelines will give you an idea.

Best 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/1149?email_source=notifications&email_token=ABZHUARFLWS4HS2OBEYEQVLQCNGFTA5CNFSM4HYMJN42YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOD3L4YEY#issuecomment-517458963, or mute the thread https://github.com/notifications/unsubscribe-auth/ABZHUAW5Z5LKMYHZJ6L3GA3QCNGFTANCNFSM4HYMJN4Q .

-- Shraddha Pai Post-doctoral Fellow, http://baderlab.org The Donnelly Center, University of Toronto @spaiglass on Twitter

shraddhapai commented 5 years ago

Hi, I should also add for #1 that the data all require patient labels.

The kidney data (which was originally generated from TCGA but which we obtained in processed form from the PanCancer survival project), there are binary patient labels (poor/good survivor) which we obtained from this project. To pull these from TCGA we would need to fetch the data separately, subset for the patients used by the PanCancer survival project, and then assign binary labels.

The medulloblastoma example also has subtypes which were identified in the paper which generated these data. The classifier example runs 4-way classification based on these labels.

Finally the breast cancer data (which we did obtain from TCGA's portal page for that dataset) has PAM50 subtypes, but these data likely already exist in BioC.

LiNk-NY commented 5 years ago

Hi Shraddha, @shraddhapai Thank you for your prompt response.

  1. The chief answer to your questions below is that this package was developed in the course of method development for a research article, and not from scratch for submission to BioConductor. The data we use for examples flow naturally from the work done in that paper. By mandating an update to the examples by spending time to familiarize ourselves with existing data packages, BioConductor is putting a high bar on research scientists attempting to make near-ready work available to the community at large. I have already spent considerable time conforming to BioC requirements via the check, build and BiocCheck utilities, and including examples with data that work. How necessary is the use of these pre-packaged data for BioC acceptance?

Please note that a Bioconductor package submission is a considerably different exercise than work done for a paper. Bioconductor maintains a minimum standard for all software packages. The purpose of the review is to ensure that software works easily within the Bioconductor ecosystem by providing inter-operable packages that use familiar and existing Bioconductor classes.

Your method does not necessarily have to include the example data that you used to develop it. It can make use of available Bioconductor data resources for demonstration. To answer your question, it is not necessary to use the pre-packaged data for acceptance but I would recommend it since some of the data is already available in Bioconductor. An alternative would be to include a reduced example data set within the method package itself.

In my opinion, it would be preferable for both parties to not maintain a data package that is solely used for examples. Simply including the data that you used to develop your method comes short of guidelines for the above reasons.

Keep in mind that there are other avenues for making your vignette / workflow and data available to the community such as within a GitHub repository. It would be a good idea to separate the method software from the paper workflow / analysis.

  1. Using a SummarizedExperiment sounds straightforward, if it is highly similar to the old ExpressionSet. From what I can see, only a few high-level methods need to change their input from using data.frames and matrices and putting them into lists, to using the SummarizedExperiment setup. This should be easy to do. Most internal methods don't operate on the entire dataset, only on pieces and subsets of it. Am I missing anything?

Yes, SummarizedExperiment is the preferred way of working with expression data and thus providing a core data structure for Bioconductor packages. It provides an integrative representation of the clinical data, expression data and even ranged data with RangedSummarizedExperiment. I am not sure what internal methods you are referring to but your inputs can be either matrix or SummarizedExperiment as we only require support for core data classes.

  1. In my daily dev work I don't use SummarizedExperiment. This classifier integrates data from multiple assays. I have used ExpressionSet in the past but not SummarizedExperiment because I wasn't aware of it and ExpressionSet only had a slot for one assay. I do routinely use GenomicRanges, because of the useful ability to perform operations on genomic ranges. This is why that data structure is used in the package. If I were to update the methods to use SummarizedExperiments, the doc would be accordingly updated too. You mention at the end of your message that "considerable" work is required. What in particular were you thinking of?

RangedSummarizedExperiment would be the ideal data structure for the above use case. I would refer you to the package guidelines to get an idea of what work would be required. To start, we would recommend against using cat, sink, set.seed, saving files for the user, deleting files for the user via system calls, etc.

Best regards, Marcel

shraddhapai commented 5 years ago

Hi Marcel, Thank you for taking the time to explain the perspective that the BioC development proceeds with. This was very useful in helping me understand how our package needs to be restructured for submission to BioC. In particular, your comment about separating the workflow from methods was helpful. But the update will definitely require major design changes on our end.

Wondering if you can guide us with the following: We want to make the classifier to be as turn-key as possible. For example, the buildPredictor() function: it takes all the input data from the user and runs a standard cross-validation design over multiple train-test splits, computes feature scores and model performance over these splits. This is the function by which we expect most beginners to interact with the classifier. All the lower-level functions are hidden from the user, similar to the caret machine-learning package.

The biggest violation of this function, based on your comments below, is probably that it creates the output directory with all the predictor results organized. It writes all the output files, including feature-scores and performance results for each train/test split.

<outDir>
   -- predictionResults.txt
   <rng1>
       - <label1>
           - <featureScores>
                - <feature-level scores>
      - <label2>
           - <featureScores>
                - <feature-level scores>
  predictionResults.txt
  <rng2>
     ...
     ...
  <rngX>

Thanks,Shraddha

LiNk-NY commented 5 years ago

Hi Shraddha, @shraddhapai

From our discussion, it sounds like this function would turn into a workflow/vignette rather than be a method in the package. Does this sound right? But then to use it, wouldn't a user have to copy-paste all this code into their own R function? Our goal is to have the user only specify the conceptual aspect of the predictor design and not be exposed to all the intermediate or low-level function-calls ; netDx should just handle this.

I'd suggest that you either use tempfile() or hold all the results in memory without having to save any files. If the files are important, then you'd have to use the tempfile solution and allow users to change the directory if they wish via the function argument (e.g., directory). I don't think it would be a workflow as it is only a single function and you'd like users to interact with it at the top level (specifying the arguments).

If I were to remove all the "set.seed" calls from all the functions (e.g. splitting train/test samples in splitTrainTest_resampling() and in makeQueries()), how would I control the setting of the RNG seed for multiple operations? Or is the tradeoff that the user calls "set.seed()" once at the outset and that is it?

set.seed has no place inside functions. Please keep your functions modular and allow users to set their own seeds. http://bioconductor.org/developers/package-guidelines/#rcode

How do you print messages if "cat()" is not allowed?

Please use message

Finally, I will likely have more questions as I work through the redesign. Is this comment thread the appropriate venue to ask? I will ask smaller questions via the bioc-devel mailing list or community-bioc slack channel.

If it were me, my first resources would be:

For more advanced topics such as deciding on appropriate S4 data structures, I would ask on the bioc-devel mailing list. See here: http://bioconductor.org/developers/package-submission/#support

Best, Marcel

shraddhapai commented 5 years ago

Great, thanks for the recommendations Marcel. I will work on those changes. Best,Shraddha

On Mon, Aug 5, 2019 at 12:09 PM Marcel Ramos notifications@github.com wrote:

Hi Shraddha, @shraddhapai https://github.com/shraddhapai

From our discussion, it sounds like this function would turn into a workflow/vignette rather than be a method in the package. Does this sound right? But then to use it, wouldn't a user have to copy-paste all this code into their own R function? Our goal is to have the user only specify the conceptual aspect of the predictor design and not be exposed to all the intermediate or low-level function-calls ; netDx should just handle this.

I'd suggest that you either use tempfile() or hold all the results in memory without having to save any files. If the files are important, then you'd have to use the tempfile solution and allow users to change the directory if they wish via the function argument (e.g., directory). I don't think it would be a workflow as it is only a single function and you'd like users to interact with it at the top level (specifying the arguments).

If I were to remove all the "set.seed" calls from all the functions (e.g. splitting train/test samples in splitTrainTest_resampling() and in makeQueries()), how would I control the setting of the RNG seed for multiple operations? Or is the tradeoff that the user calls "set.seed()" once at the outset and that is it?

set.seed has no place inside functions. Please keep your functions modular and allow users to set their own seeds. http://bioconductor.org/developers/package-guidelines/#rcode

How do you print messages if "cat()" is not allowed?

Please use message

Finally, I will likely have more questions as I work through the redesign. Is this comment thread the appropriate venue to ask? I will ask smaller questions via the bioc-devel mailing list or community-bioc slack channel.

If it were me, my first resources would be:

For more advanced topics such as deciding on appropriate S4 data structures, I would ask on the bioc-devel mailing list. See here: http://bioconductor.org/developers/package-submission/#support

Best, Marcel

— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub https://github.com/Bioconductor/Contributions/issues/1149?email_source=notifications&email_token=ABZHUAVTX3OU3QRAS4YAMLTQDBGBZA5CNFSM4HYMJN42YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOD3SJP3Y#issuecomment-518297583, or mute the thread https://github.com/notifications/unsubscribe-auth/ABZHUAW6HUXRHXEUM7E6MZTQDBGBZANCNFSM4HYMJN4Q .

-- Shraddha Pai Post-doctoral Fellow, http://baderlab.org The Donnelly Center, University of Toronto @spaiglass on Twitter

lshep commented 4 years ago

Are there any updates on this package? We generally like to see package improvements within 2-3 weeks to move packages through the review process. If you need more time we can temporarily close the issue and you can reopen it when you are ready to commit changes.

shraddhapai commented 4 years ago

Hi, I am slowly working through the changes required (there are quite a few) but it may be a few weeks yet. It may be best to temporarily close the issue. How do I reopen the issue when the time comes? Thanks,Shraddha

On Thu, Sep 19, 2019 at 8:01 AM lshep notifications@github.com wrote:

Are there any updates on this package? We generally like to see package improvements within 2-3 weeks to move packages through the review process. If you need more time we can temporarily close the issue and you can reopen it when you are ready to commit changes.

— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub https://github.com/Bioconductor/Contributions/issues/1149?email_source=notifications&email_token=ABZHUAXSAWSJ4YWWK3ZW4FDQKNS2XA5CNFSM4HYMJN42YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOD7DG6TI#issuecomment-533098317, or mute the thread https://github.com/notifications/unsubscribe-auth/ABZHUAQ24H2BXFC3AIDZ4BLQKNS2XANCNFSM4HYMJN4Q .

--

Shraddha Pai, PhD http://shraddhapai.com ; @spaiglass on Twitter Post-doctoral Fellow, http://baderlab.org The Donnelly Centre for Cellular and Biomolecular Research University of Toronto

lshep commented 4 years ago

Please comment back here tagging @lshep and @LiNk-NY that you are ready to pick the review process back up and we will open it back up for you. Cheers!

bioc-issue-bot commented 4 years ago

This issue is being closed because there has been no progress for an extended period of time. You may reopen the issue when you have the time to actively participate in the review / submission process. Please also keep in mind that a package accepted to Bioconductor requires a commitment on your part to ongoing maintenance.

Thank you for interest in Bioconductor.

shraddhapai commented 4 years ago

Hi @lshep and @LiNk-NY, this package has been modified as per BioC package guidelines, passes check and BiocCheck and is ready for review. Could you please re-open the issue? Thanks!

LiNk-NY commented 4 years ago

Hi Shraddha @shraddhapai Can you bump the package y version? Hopefully the webhook is still active and the SBP will build your package. Thanks. cc: @lshep

shraddhapai commented 4 years ago

Hi Marcel, the y? It was previously 0.99.2 and I just bumped the z to 0.99.3 and committed (~20 min ago). What do I bump the y to? Thanks,S

On Mon, Nov 18, 2019 at 1:26 PM Marcel Ramos notifications@github.com wrote:

Hi Shraddha @shraddhapai https://github.com/shraddhapai Can you bump the package y version? Hopefully the webhook is still active and will build your package. Thanks. cc: @lshep https://github.com/lshep

— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub https://github.com/Bioconductor/Contributions/issues/1149?email_source=notifications&email_token=ABZHUAWSMTXAAXWBTEGA4NLQULM3RA5CNFSM4HYMJN42YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOEELNS5Y#issuecomment-555145591, or unsubscribe https://github.com/notifications/unsubscribe-auth/ABZHUAVMDHTFOCPMENNL5S3QULM3RANCNFSM4HYMJN4Q .

--

Shraddha Pai, PhD http://shraddhapai.com ; @spaiglass on Twitter Post-doctoral Fellow, http://baderlab.org The Donnelly Centre for Cellular and Biomolecular Research University of Toronto

LiNk-NY commented 4 years ago

Yes, sorry the z version.

bioc-issue-bot commented 4 years ago

Received a valid push; starting a build. Commits are:

f033bca trigger build again

shraddhapai commented 4 years ago

Hi, ok - just bumped from 0.99.3 to 0.99.4. Webhook has a green checkmark next to it so hopefully it's ok. -S

On Mon, Nov 18, 2019 at 1:37 PM Marcel Ramos notifications@github.com wrote:

Yes, sorry the z version.

— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub https://github.com/Bioconductor/Contributions/issues/1149?email_source=notifications&email_token=ABZHUASI4PMVSETD5KDBHC3QULOHRA5CNFSM4HYMJN42YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOEELOZWA#issuecomment-555150552, or unsubscribe https://github.com/notifications/unsubscribe-auth/ABZHUAUNGZBKOSHTAF4UKLTQULOHRANCNFSM4HYMJN4Q .

--

Shraddha Pai, PhD http://shraddhapai.com ; @spaiglass on Twitter Post-doctoral Fellow, http://baderlab.org The Donnelly Centre for Cellular and Biomolecular Research University of Toronto

bioc-issue-bot commented 4 years ago

Dear Package contributor,

This is the automated single package builder at bioconductor.org.

Your package has been built on Linux, Mac, and Windows.

On one or more platforms, the build results were: "WARNINGS, skipped, ERROR". This may mean there is a problem with the package that you need to fix. Or it may mean that there is a problem with the build system itself.

Please see the build report for more details.

bioc-issue-bot commented 4 years ago

Received a valid push; starting a build. Commits are:

986ad33 trigger build

bioc-issue-bot commented 4 years ago

Received a valid push; starting a build. Commits are:

a188500 trigger build

bioc-issue-bot commented 4 years ago

Dear Package contributor,

This is the automated single package builder at bioconductor.org.

Your package has been built on Linux, Mac, and Windows.

On one or more platforms, the build results were: "WARNINGS, skipped, ERROR". This may mean there is a problem with the package that you need to fix. Or it may mean that there is a problem with the build system itself.

Please see the build report for more details.

bioc-issue-bot commented 4 years ago

Dear Package contributor,

This is the automated single package builder at bioconductor.org.

Your package has been built on Linux, Mac, and Windows.

On one or more platforms, the build results were: "WARNINGS". This may mean there is a problem with the package that you need to fix. Or it may mean that there is a problem with the build system itself.

Please see the build report for more details.

bioc-issue-bot commented 4 years ago

Dear Package contributor,

This is the automated single package builder at bioconductor.org.

Your package has been built on Linux, Mac, and Windows.

On one or more platforms, the build results were: "WARNINGS, skipped, ERROR". This may mean there is a problem with the package that you need to fix. Or it may mean that there is a problem with the build system itself.

Please see the build report for more details.

bioc-issue-bot commented 4 years ago

Received a valid push; starting a build. Commits are:

557dcae bypass python, remove dup network writing 0716328 written in r 4e3ae81 for testing 3ac1808 vignette runs from end to end b26339d parallelize a635092 Trigger build 975ba75 removed append comment 59e10bb removed append flag in makePSN 4bfebc7 Merge branch 'master' into nopython 50c9819 Merge pull request #68 from BaderLab/nopython Rem...

bioc-issue-bot commented 4 years ago

Dear Package contributor,

This is the automated single package builder at bioconductor.org.

Your package has been built on Linux, Mac, and Windows.

On one or more platforms, the build results were: "TIMEOUT". This may mean there is a problem with the package that you need to fix. Or it may mean that there is a problem with the build system itself.

Please see the build report for more details.

bioc-issue-bot commented 4 years ago

Received a valid push; starting a build. Commits are:

7ab10cd fixed examples 5d40731 Merge pull request #69 from BaderLab/nopython fix...

bioc-issue-bot commented 4 years ago

Dear Package contributor,

This is the automated single package builder at bioconductor.org.

Your package has been built on Linux, Mac, and Windows.

On one or more platforms, the build results were: "WARNINGS". This may mean there is a problem with the package that you need to fix. Or it may mean that there is a problem with the build system itself.

Please see the build report for more details.

LiNk-NY commented 4 years ago

Hi Shraddha, @shraddhapai

Please follow up on the warnings / notes from the build results.

For example: 

* checking package dependencies ... NOTE
Depends: includes the non-default packages:
  'bigmemory', 'foreach', 'doParallel', 'combinat', 'BiocManager',
  'GenomicRanges', 'knitr', 'htmltools', 'BiocFileCache', 'rappdirs'

Best, Marcel

shraddhapai commented 4 years ago

Hi Marcel @LiNk-NY , I tried removing the dependency names in DEPENDS but then BiocCheck just gives me a warning saying "Import BiocFileCache, GenomicRanges, bigmemory, doParallel, foreach, combinat, rappdirs in DESCRIPTION as well as NAMESPACE."

How do I resolve this problem? Thanks,Shraddha

LiNk-NY commented 4 years ago

Hi Shraddha, @shraddhapai

It means that you should include @importFrom or @import directives in your code for selective importing or package namespace importing, respectively.

Best, Marcel

bioc-issue-bot commented 4 years ago

Received a valid push; starting a build. Commits are:

5a69933 bioc fixes 228f910 just before tidy_source 33b459e just before tidysource 4fda014 Merge branch 'bioc_fixes' of https://github.com/Ba... 637fd7a cleaning formatting - in progress 43f286f fixed long lines abb404f resolved errors and warnings, fixed formatting 391ba26 passes check/bioccheck without errors/warnings 84498e1 Merge pull request #70 from BaderLab/bioc_fixes B...