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Data supplement to Manuscript "A 5-Gene Signature (PROGRESS-STYCK) predicts ICU Admission and Death in Community Acquired Pneumonia"

<p>Supplementary RNAseq data for correlation analysis with HT12v4 Chip data</p> <p>This refers to the publication</p> <p><strong>A 5-Gene&nbsp;</strong><strong>Signature (PROGRESS-STYCK) predicts ICU Admission and Death in Community Acquired Pneumonia</strong></p> <p>Holger Kirsten<sup>1</sup>*, Sebastian Weis<sup>2,3,4</sup>*, Peter Ahnert<sup>1</sup>, Martin Witzenrath<sup>5,6</sup>, Brendon P. Scicluna<sup> 7,8</sup>, Knut Krohn<sup>9</sup>, Friedmann Horn<sup>10</sup>Michael Rade<sup> 10</sup>, Catharina Bertram<sup>10</sup>, Kristin Reiche<sup>10</sup>, Dennis L&ouml;ffler<sup>10</sup>, Conny Blumert<sup>10</sup>, Kai Sohn<sup>11</sup>, Stefan Jenner<sup>11</sup>,, Kai Sohn<sup>11</sup>, Geraldine Nouailles<sup>5</sup>, Michael Kiehntopf<sup>12,13</sup>, Petra Creutz<sup>5</sup>, Markus Loeffler<sup>1</sup>, Norbert Suttorp<sup>5,6</sup>,PROGRESS Study Group, Markus Scholz<sup>1+</sup>, Michael Bauer<sup>2+</sup></p> <p>&nbsp;</p> <p><sup>1</sup> Institute for Medical Informatics, Statistics and Epidemiology (IMISE), Leipzig University, Leipzig, Germany,</p> <p><sup>2</sup> Department of Anesthesiology and Intensive Care Medicine, Jena University Hospital,</p> <p>Friedrich-Schiller-University Jena, Germany</p> <p><sup>3 </sup>Institute for Infectious Disease and Infection Control, Jena University Hospital, Friedrich-Schiller-University Jena, Jena, Germany</p> <p><sup>4 </sup>Leibniz Institute for Leibniz Institute for Natural Product Research and Infection Biology</p> <p>Hans Kn&ouml;ll Institute, Jena</p> <p><sup>5 </sup>Charit&eacute; - Universit&auml;tsmedizin Berlin, corporate member of Freie Universit&auml;t Berlin and Humboldt-Universit&auml;t zu Berlin, Department of Infectious Diseases and Respiratory Medicine, Berlin, Germany.</p> <p><sup>6</sup> German Center for Lung Research (DZL), Partner Site Charit&eacute;, Berlin, Germany.</p> <p><sup>7</sup> Centre for Molecular Medicine and Biobanking, University of Malta, Malta</p> <p><sup>8</sup> Department of Applied Biomedical Science, Faculty of Health Sciences, Mater Dei hospital, University of Malta, Malta</p> <p><sup>9</sup> Core Unit DNA Technologies, Medical Faculty, Leipzig University, Leipzig, Germany.</p> <p><sup>10</sup> Department of Diagnostics, Institute for Cell Therapy and Immunology, Leipzig, Germany</p> <p><sup>11</sup> Fraunhofer Institute for Interfacial Engineering and Biotechnology, Stuttgart, Germany</p> <p><sup>12 </sup>Department of Clinical Chemistry and Laboratory Medicine, Jena University Hospital, Friedrich-Schiller-University Jena, Jena, Germany.</p> <p><sup>13 </sup>Integrated Biobank Jena (IBBJ), Jena University Hospital, Friedrich-Schiller-University Jena, Jena, Germany.</p> <p>*+ these authors contributed equally to the work.</p> <p>&nbsp;</p> <p>For sequencing-based expression quantification, libraries were prepared using globin-mRNA depleted RNA and sequencing was performed with HiSeq2500 sequencing (Illumina, San Diego, CA, USA), with an average sequencing depth of 100 million clusters per sample and 2x100b paired-end reads. Data analysis included demultiplexing, trimming, filtering, removal of low-quality bases, quantification at gene-level, and quality-assessment. Data of measured genes and individuals can be found in file&nbsp;<strong>s816_1_expression_levels_ngs.txt</strong>.&nbsp;&nbsp;</p> <p>For array-based expression quantification, purified RNA was hybridized to Illumina HT-12v4 Expression-BeadChips (Illumina, San Diego, CA, USA). Low-quality samples were removed, and data was log2-transformed, quantile-normalized, batch-corrected and filtered for minimum expression levels, resulting in 26,601 transcripts representing 16,329 unique genes.Data of measured genes and individuals can be found in&nbsp; <strong>s816_1_expression_levels_array.txt</strong></p> <p>Data showing corresponding genes between NGS gene IDs and Array probe IDs can be found in <strong>s816_1_assignment_genes_ngs_array.txt</strong><br> &nbsp;</p>

ShareScore

16/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
8
Harmonization
4
Access
0
Reuse readiness
0
Engagement
4

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