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  • Neurodesk: an accessible, flexible and portable data analysis environment for reproducible neuroimaging

    Authors: Angela I. Renton, Thuy T. Dao, Tom Johnstone, Oren Civier, Ryan P. Sullivan, David J. White, Paris Lyons, Benjamin M. Slade, David F. Abbott, Toluwani J. Amos, Saskia Bollmann, Andy Botting, Megan E. J. Campbell, Jeryn Chang, Thomas G. Close, Monika Dörig, Korbinian Eckstein, Gary F. Egan, Stefanie Evas, Guillaume Flandin, Kelly G. Garner, Marta I. Garrido, Satrajit S. Ghosh, Martin Grignard, Yaroslav O. Halchenko, Anthony J. Hannan, Anibal S. Heinsfeld, Laurentius Huber, Matthew E. Hughes, Jakub R. Kaczmarzyk, Lars Kasper, Levin Kuhlmann, Kexin Lou, Yorguin-Jose Mantilla-Ramos, Jason B. Mattingley, Michael L. Meier, Jo Morris, Akshaiy Narayanan, Franco Pestilli, Aina Puce, Fernanda L. Ribeiro, Nigel C. Rogasch, Chris Rorden, Mark M. Schira, Thomas B. Shaw, Paul F. Sowman, Gershon Spitz, Ashley W. Stewart, Xincheng Ye, Judy D. Zhu, Aswin Narayanan & Steffen Bollmann
    DOI: https://doi.org/10.1038/s41592-023-02145-x
    Submitted by sbollmann    

    Why should we attempt to reproduce this paper?

    We invested a lot of work to make the analyses from the paper reproducible and we are very curious how the documentation could be improved and if people run into any problems.

  • The Interplay of Time-of-day and Chronotype Results in No General and Robust Cognitive Boost

    Authors: Alodie Rey-Mermet, Nicolas Rothen
    DOI: https://doi.org/10.1525/collabra.88337
    Submitted by areyme      

    Why should we attempt to reproduce this paper?

    In this paper, an R package was used to improve the reproducibility of the analyses. Therefore, it would be good to know to what extent this works. The R package includes the following analyses: (1) data trimming and preparation, (2) descriptive statistics, (3) reliability and correlations, (4) t-tests and Bayesian t-tests, (5) latent-change models (structural equation modeling approach), and (6) multiverse analyses. Furthermore, all deidentified data, experiment codes, research materials, and results are publicly accessible on the Open Science Framework (OSF) at https://osf.io/ngfxv. The study’s design and the analyses were pre-registered on OSF. The preregistration can be accessed at https://osf.io/ tywu7.

  • Revisiting the zonally asymmetric extratropical circulation of the Southern Hemisphere spring using complex empirical orthogonal functions

    Authors: Elio Campitelli, Leandro Díaz, Carolina Vera
    DOI: 10.1007/s00382-023-06780-0
    Submitted by eliocamp      
      Mean reproducibility score:   1.0/10   |   Number of reviews:   1
    Why should we attempt to reproduce this paper?

    I used a lot of different tools and strategies to make this paper easily reproducible at different levels. There's Docker container for the highest level of reproducibility, and package versions are managed with renv. The data used in the paper is hosted on Zenodo to avoid long queue times when downloading from the Climate Data Store and future-proof for when it goes away and checksumed before using it.

    Tags: R Docker climate
  • Machine learning a model for RNA structure prediction

    Authors: Nicola Calonaci, Alisha Jones, Francesca Cuturello, Michael Sattler, Giovanni Bussi
    DOI: 10.1093/nargab/lqaa090
    Submitted by giovannibussi      

    Why should we attempt to reproduce this paper?

    The method is trained on the data that were available, but it is meant to be re-trainable as soon as new data are published. It would be great to be really sure that even someone else will be able to do it. In case we receive any feedback, we would be really happy to improve our Github repository so as to make the reproduction easier!

  • The role of conidia in the dispersal of Ascochyta rabiei

    Authors: Khaliq, I., Fanning, J., Melloy, P. et al.
    DOI: 10.1007/s10658-020-02126-2
    Submitted by hub-admin    

    Why should we attempt to reproduce this paper?

    I suggested a few papers last year. I’m hoping that we’ve improved our reproducibility with this one, this year. We’ve done our best to package it up both in Docker and as an R package. I’d be curious to know what the best way to reproduce it is found to be. Working through vignettes or spinning up a Docker instance. Which is the preferred method?

    Tags: R Docker
  • Growth Dynamics of Independent Gametophytes of Pleurosoriopsis makinoi ( Polypodiaceae)

    Authors: Atsushi Ebihara, Joel H. Nitta, Yurika Matsumoto, Yuri Fukazawa, Marie Kurihara, Hitomi Yokote, Kaoru Sakuma, Otowa Azakami, Yumiko Hirayama, Ryoko Imaichi
    Submitted by joelnitta    
      Mean reproducibility score:   10.0/10   |   Number of reviews:   1
    Why should we attempt to reproduce this paper?

    It uses the drake R package that should make reproducibility of R projects much easier (just run make.R and you're done). However, it does depend on very specific package versions, which are provided by the accompanying docker image.

    Tags: R Docker Drake
  • Population structure and phenotypic variation of Sclerotinia sclerotiorum from dry bean (Phaseolus vulgaris) in the United States

    Authors: Kamvar ZN, Amaradasa BS, Jhala R, McCoy S, Steadman JR, Everhart SE
    DOI: 10.7717/peerj.4152
    Submitted by hub-admin    
      Mean reproducibility score:   6.0/10   |   Number of reviews:   1
    Why should we attempt to reproduce this paper?

    This paper is reproduced weekly in a docker container on continuous integration, but it is also set up to work via local installs as well. It would be interesting to see if it's reproducible with a human operator who knows nothing of the project or toolchain.

    Tags: R make Docker

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