Community members: your publication on arXiv.org!

Community experts, we’re pleased to inform you that you’re co-authors of the article titled OMICtools: a community-driven search engine for biological data analysis. The preprint version of this article has been assigned the permanent arXiv identifier 1707.03659 and is available on arXiv.org.

This publication gives us the opportunity to thank all the OMICtools biocurators and users for their helpful collaboration in providing high-quality and updated information on bioinformatics tools.

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Overview of the collaborative functionality offers on the OMICtools platform

Here’s the abstract: with high-throughput biotechnologies generating unprecedented quantities of data, researchers are faced with the challenge of locating and comparing an exponentially growing number of programs and websites dedicated to computational biology, in order to maximize the potential of their data.

OMICtools is designed to meet this need with its open-access search engine offering an easy means of locating the right tools corresponding to each researcher and their specific biological data analyses. The OMICtools website centralizes more than 18,500 software tools and databases, manually classified, by a team of biocurators including many scientific experts. Key information, a direct link, and access to discussions and evaluations by the biomedical community are provided for each tool. Anyone can join the OMICtools community and create a profile page, to share their expertise and comment on tools. In addition, developers can directly upload their code versions which are registered for identification and citation in scientific publications, improving research traceability.

The OMICtools community links thousands of life scientists and developers worldwide, who use this bioinformatics platform to accelerate their projects and biological data analyses.

Community opinion: optimize your search experience

Firstly, a big thanks to all of you who participated in our survey!

A few weeks ago, we sent out a survey so we can better meet your needs and improve your search experience on OMICtools. Thanks to all of the 78 participants who took part in this survey, your feedback is really important to us.

We are happy to report here the positive results of this survey. All of you were satisfied regarding the relevance of the results you get with the OMICtools search engine, with 59% judging the results as good and 31% as great.

Participants also reported that for 55% of you find the OMICtools search engine and website easy to use and innovative, and 43% consider it satisfactory. Only 2% (1 person) encountered difficulties using it (we are always happy to answer any questions right away about any difficulties you encounter).

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We listed six criteria used in our ranking algorithm (see the previous post OMICtools: upgrading your search experience for more details) which we use to define the order the tools appear in your search results, and we asked you to order them by importance. Your ranking from most important to least important (left to right) is:

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With tool quality rating being of primary importance for users – make sure you rate any tools you yourself use, so others can benefit from the community’s experience. We also asked you to give your opinion on the choice of our new additional filters:

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Your answers have helped us a lot. The new filters are now available!

You can now use them to specify your needs on the category pages and to sort the search engine results by computer skills, operating system (os), programming language, technology and/or software type.

Once again, thanks for completing this survey! Your feedback on filters is always welcome.

How to make software more robust?

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Scientific quality and reproducibility rely on the traceability of the experimental data, statistical methods and bioinformatics tools used to generate results. Being unable to replicate and validate scientific results is unfortunately very common. This reproducibility crisis as named by Monya Baker considerably slows down the research progress and affects all of the fields including chemistry, biology and medicine.

Best practices are crucially needed today to improve reproducibility of data analysis and hence to make software robust enough to be run by any user.

Indeed, most of the software tools used to produce scientific results and publications are prototypes and lack robustness. Usually designed and run by a single person in a specific computing environment, codes may be very difficult to be used by other persons to analyze their data and are too often abandoned after publication. Last month, Morgan Taschuk and Greg Wilson published Ten simples rules for making research software more robust providing a quick guide for mastering the key challenge of robustness in software engineering.

What is a “robust” software?

The authors define robust software as a “software that works for people other than the original author and on machines other than its creator’s.” And this mean that “it can be installed on more than one computer with relative ease, it works consistently as advertised, and it can be integrated with other tools.”

Increasing software robustness is a key question for software developers and all users who want to produce replicable and reproducible results and publish their work.Improving software robustness would only take the effort to follow these ten simple rules summarized in the list below:

1. Use version control

2. Document your code and usage

3. Make common operations easy to control

4. Version your releases

5. Reuse software (within reason)

6. Rely on build tools and package managers for installation

7. Do not require root or other special privileges to install or run

8. Eliminate hard-coded paths

9. Include a small test set that can be run to ensure the software is actually working

10. Produce identical results when given identical inputs

How OMICtools promotes software quality and traceability

OMICtools has developed several strategies to promote better quality of bioinformatics resources and reproducibility of computational analysis.

First, OMICtools promotes the citation of bioinformatics resources and exact code version identification for reproducibility and traceability of biological data analysis.

OMICtools brings together thousands of software in a single place where any user can find all the relevant information to choose and use the program he needs. Our search engine offer an easy way to get the list of tools dedicated to a specific question and analysis function. Moreover, citations and references are specified for each tool as well as the successive program versions and obsolete links to facilitate the survey of bioinformatics tools

Secondly, OMICtools is a collaborative repository platform that facilitates the development, maintenance and follow-up of bioinformatic tools by programmers themselves.

Software developers can directly upload their source codes into the OMICtools server so the community can easily locate them. In addition to the research resource identifier (RRID) which is attributed for each of OMICtools resource, each published source code version get a unique digital object identifier (DOI). Attributing DOI provides an interoperable exchange with other digital resources and a persistent identification, even if material is moved or rearranged. Software developers indicate the version of the source code, the operating system and architecture, as well as the publication, to link the code and program access to DataCite’s API which automatically generates the corresponding DOI.  They can modify and update their own project by providing their new code versions. Moreover, OMICtools is implementing a dedicated GitLab service. On their GitLab page, programmers will be able to modify and update their own projects and work together to test, build, consolidate and deploy their codes.

App developers, here’re three good reasons to upload your code versions on OMICtools repository platform:

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Based on the recent papers:

(Taschuk and Wilson, 2017) Ten simple rules for making research software more robust. PLoS Computational Biology.

(Baker, 2016) 1,500 scientists lift the lid on reproducibility. Nature.