Dataset Information

FMRIflows: A Consortium of Fully Automatic Univariate and Multivariate fMRI Processing Pipelines.

ABSTRACT: How functional magnetic resonance imaging (fMRI) data are analyzed depends on the researcher and the toolbox used. It is not uncommon that the processing pipeline is rewritten for each new dataset. Consequently, code transparency, quality control and objective analysis pipelines are important for improving reproducibility in neuroimaging studies. Toolboxes, such as Nipype and fMRIPrep, have documented the need for and interest in automated pre-processing analysis pipelines. Recent developments in data-driven models combined with high resolution neuroimaging dataset have strengthened the need not only for a standardized preprocessing workflow, but also for a reliable and comparable statistical pipeline. Here, we introduce fMRIflows: a consortium of fully automatic neuroimaging pipelines for fMRI analysis, which performs standard preprocessing, as well as 1st- and 2nd-level univariate and multivariate analyses. In addition to the standardized pre-processing pipelines, fMRIflows provides flexible temporal and spatial filtering to account for datasets with increasingly high temporal resolution and to help appropriately prepare data for advanced machine learning analyses, improving signal decoding accuracy and reliability. This paper first describes fMRIflows' structure and functionality, then explains its infrastructure and access, and lastly validates the toolbox by comparing it to other neuroimaging processing pipelines such as fMRIPrep, FSL and SPM. This validation was performed on three datasets with varying temporal sampling and acquisition parameters to prove its flexibility and robustness. fMRIflows is a fully automatic fMRI processing pipeline which uniquely offers univariate and multivariate single-subject and group analyses as well as pre-processing.

SUBMITTER: Notter MP

PROVIDER: S-EPMC10014671 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

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fMRIflows: A Consortium of Fully Automatic Univariate and Multivariate fMRI Processing Pipelines.

Notter Michael P MP Herholz Peer P Da Costa Sandra S Gulban Omer F OF Isik Ayse Ilkay AI Gaglianese Anna A Murray Micah M MM

Brain topography 20221227 2

How functional magnetic resonance imaging (fMRI) data are analyzed depends on the researcher and the toolbox used. It is not uncommon that the processing pipeline is rewritten for each new dataset. Consequently, code transparency, quality control and objective analysis pipelines are important for improving reproducibility in neuroimaging studies. Toolboxes, such as Nipype and fMRIPrep, have documented the need for and interest in automated pre-processing analysis pipelines. Recent developments i ...[more]

PMID: 36575327

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Project description:BackgroundRNA-Seq is an increasing used methodology to study either coding and non-coding RNA expression. There are many software tools available for each phase of the RNA-Seq analysis and each of them uses different algorithms. Furthermore, the analysis consists of several steps regarding alignment (primary-analysis), quantification, differential analysis (secondary-analysis) and any tertiary-analysis and can therefore be time-consuming to deal with each step separately, in addition to requiring a computer knowledge. For this reason, the development of an automated pipeline that allows the entire analysis to be managed through a single initial command and that is easy to use even for those without computer skills can be useful. Faced with the vast availability of RNA-Seq analysis tools, it is first of all necessary to select a limited number of pipelines to include. For this purpose, we compared eight pipelines obtained by combining the most used tools and for each one we evaluated peak of RAM, time, sensitivity and specificity.ResultsThe pipeline with shorter times, lower consumption of RAM and higher sensitivity is the one consisting in HISAT2 for alignment, featureCounts for quantification and edgeR for differential analysis. Here, we developed ARPIR, an automated pipeline that recurs by default to the cited pipeline, but it also allows to choose, between different tools, those of the pipelines having the best performances.ConclusionsARPIR allows the analysis of RNA-Seq data from groups undergoing different treatment allowing multiple comparisons in a single launch and can be used either for paired-end or single-end analysis. All the required prerequisites can be installed via a configuration script and the analysis can be launched via a graphical interface or by a template script. In addition, ARPIR makes a final tertiary-analysis that includes a Gene Ontology and Pathway analysis. The results can be viewed in an interactive Shiny App and exported in a report (pdf, word or html formats). ARPIR is an efficient and easy-to-use tool for RNA-Seq analysis from quality control to Pathway analysis that allows you to choose between different pipelines.

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Dataset Information

FMRIflows: A Consortium of Fully Automatic Univariate and Multivariate fMRI Processing Pipelines.

Publications

fMRIflows: A Consortium of Fully Automatic Univariate and Multivariate fMRI Processing Pipelines.

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