Identification of SARS-CoV-2–specific immune alterations in acutely ill patients
This article has been Reviewed by the following groups
Listed in
- Evaluated articles (ScreenIT)
Abstract
Article activity feed
-
-
SciScore for 10.1101/2020.12.21.20248642: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement Consent: Informed consent was obtained for each patient and is detailed elsewhere(86). Randomization Multivariate prediction of the SARS-CoV-2+, SARS-CoV-2neg and HC status, using as candidate predictor variables the whole set of the immune subpopulations, was performed using a random forest (52) classification models as implemented in the randomForest 4.6-14 R package using 1000 random trees and the default “mtry” (number of variables randomly sampled and tested in each node) parameter. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Software and Algorithms Sentences Resources BD FACSDiva™ CS&T research … SciScore for 10.1101/2020.12.21.20248642: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement Consent: Informed consent was obtained for each patient and is detailed elsewhere(86). Randomization Multivariate prediction of the SARS-CoV-2+, SARS-CoV-2neg and HC status, using as candidate predictor variables the whole set of the immune subpopulations, was performed using a random forest (52) classification models as implemented in the randomForest 4.6-14 R package using 1000 random trees and the default “mtry” (number of variables randomly sampled and tested in each node) parameter. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Software and Algorithms Sentences Resources BD FACSDiva™ CS&T research beads (#655051) were acquired biweekly to ensure the stability of the cytometer. BD FACSDiva™suggested: (BD FACSDiva Software, RRID:SCR_001456)Flow cytometry analysis: Flow cytometric data analysis was performed using FlowJo (version 10.6.2). FlowJosuggested: (FlowJo, RRID:SCR_008520)Using the R packages flowCore 2.0.1 and FlowSOM 1.20.0 in R version 4.0.1, we applied the FlowSOM algorithm(20) on these concatenated files to create a FlowSOM map for each panel. flowCoresuggested: (flowCore, RRID:SCR_002205)The modal value of clusters, as determined by the PhenoGraph clustering algorithm(19) in FlowJo on multiple random samples, was used to determine the number of clusters to input into FlowSOM. PhenoGraphsuggested: (Phenograph, RRID:SCR_016919)FlowSOMsuggested: (FlowSOM, RRID:SCR_016899)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
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: We found the following clinical trial numbers in your paper:
Identifier Status Title NCT04356508 Not yet recruiting COVID-19: A Pilot Study of Adaptive Immunity and Anti-PD1 Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: Please consider improving the rainbow (“jet”) colormap(s) used on page 39. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.
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.
-
