Spatial transcriptomic characterization of COVID-19 pneumonitis identifies immune circuits related to tissue injury
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SciScore for 10.1101/2021.06.21.449178: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics IRB: Ethics statement: This study was approved by the ethics committee of the University of Navarra, Spain (15/05/2020) and the Medical Sciences Interdivisional Research Ethics Committee of the University of Oxford (Approval R76045/RE001). Sex as a biological variable not detected. Randomization Differential gene expression and over-representation analysis: Differential gene expression was calculated for each gene between areas of mild/moderate and severe alveolar damage using linear mixed models (fixed effect: severity, random variable: patient identity). Blinding not detected. Power Analysis not detected. Table 2: Resources
Software and Algorithms Sentences Resources Analysis of immunofluorescent … SciScore for 10.1101/2021.06.21.449178: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics IRB: Ethics statement: This study was approved by the ethics committee of the University of Navarra, Spain (15/05/2020) and the Medical Sciences Interdivisional Research Ethics Committee of the University of Oxford (Approval R76045/RE001). Sex as a biological variable not detected. Randomization Differential gene expression and over-representation analysis: Differential gene expression was calculated for each gene between areas of mild/moderate and severe alveolar damage using linear mixed models (fixed effect: severity, random variable: patient identity). Blinding not detected. Power Analysis not detected. Table 2: Resources
Software and Algorithms Sentences Resources Analysis of immunofluorescent images for cell counts: The number of nuclei, CD3+ and CD68+ cell counts were determined using CellProfiler software. CellProfilersuggested: NoneWe therefore corrected the quantile normalized expression values for this technical factor using Limma “removeBatchEffect” function. Limmasuggested: (LIMMA, RRID:SCR_010943)Over-representation analysis for Gene Ontology Biological Processes Ontology Biologicalsuggested: NoneThe over-representation of Gene Ontology (GO) categories, KEGG pathways and Reactome pathways in module gene members was tested using one-sided Fishers exact tests (https://github.com/sansomlab/gsfisher) using the union of gene members from all the modules as the background geneset. Reactomesuggested: (Reactome, RRID:SCR_003485)Immune signalling genes from the KEGG ‘cytokine-cytokine receptor interaction’ pathway (hsa04060) (human) were included if they i) correlated with the positively expressed gene modules for a given spatial group and ii) showed a median expression above the expression detection threshold (as defined in the pre-processing section) in a given AOI group. KEGGsuggested: (KEGG, RRID:SCR_012773)Results from OddPub: Thank you for sharing your code.
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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