@article{9e6cfdaa7e2843a6a2f9e3d1366ec867,
title = "Integrating neuroimaging and gene expression data using the imaging transcriptomics toolbox",
abstract = "The integration of neuroimaging and transcriptomics data, Imaging Transcriptomics, is becoming increasingly popular but standardized workflows for its implementation are still lacking. We describe the Imaging Transcriptomics toolbox, a new package that implements a full imaging transcriptomics pipeline using a user-friendly, command line interface. This toolbox allows the user to identify patterns of gene expression which correlates with a specific neuroimaging phenotype and perform gene set enrichment analyses to inform the biological interpretation of the findings using up-to-date methods. For complete details on the use and execution of this protocol, please refer to Martins et al. (2021).",
keywords = "Bioinformatics, Computer sciences, Health Sciences, Neuroscience, Sequence analysis",
author = "Alessio Giacomel and Daniel Martins and Matteo Frigo and Federico Turkheimer and Williams, {Steven C.R.} and Ottavia Dipasquale and Mattia Veronese",
note = "Funding Information: D.M., O.D., F.T., and S.C.R.M. are supported by the NIHR Maudsley{\textquoteright}s Biomedical Research Centre at the South London and Maudsley NHS Trust . MV is supported by MIUR , Italian Ministry for Education , under the initiatives “Departments of Excellence” (Law 232/2016 ) and by the National Institute for Health Research Biomedical Research Centre at South London and Maudsley National Health Service Foundation Trust and King{\textquoteright}s College London . A.G. is supported by the KCL-funded CDT in Data-Driven Health; this represents independent research partly funded by the NIHR Maudsley{\textquoteright}s Biomedical Research Center at the South London and Maudsley NHS Trust and partly funded by GlaxoSmithKline (GSK). Funding Information: D.M. O.D. F.T. and S.C.R.M. are supported by the NIHR Maudsley's Biomedical Research Centre at the South London and Maudsley NHS Trust. MV is supported by MIUR, Italian Ministry for Education, under the initiatives ?Departments of Excellence? (Law 232/2016) and by the National Institute for Health Research Biomedical Research Centre at South London and Maudsley National Health Service Foundation Trust and King's College London. A.G. is supported by the KCL-funded CDT in Data-Driven Health; this represents independent research partly funded by the NIHR Maudsley's Biomedical Research Center at the South London and Maudsley NHS Trust and partly funded by GlaxoSmithKline (GSK). A.G. wrote the python script and drafted the protocol; D.M. led the conceptual design of the toolbox and drafted the protocol; O.D. M.V. M.F. F.T. and S.C.R.W. revised the protocol for intellectual content. All authors approved the final version of the manuscript. The authors declare no competing interests. This manuscript represents independent research. Publisher Copyright: {\textcopyright} 2022 The Author(s)",
year = "2022",
month = jun,
day = "17",
doi = "10.1016/j.xpro.2022.101315",
language = "English",
volume = "3",
journal = "STAR Protocols",
issn = "2666-1667",
publisher = "Cell Press",
number = "2",
}