Integrated network-based multiple computational analyses for identification of co-expressed candidate genes associated with neurological manifestations of COVID-19

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1. Version published to 10.1038/s41598-022-21109-3

   Oct 13, 2022
2. 

   ScreenIT

   Apr 13, 2022

   SciScore for 10.1101/2022.04.10.487761: (What is this?)

   Please note, not all rigor criteria are appropriate for all manuscripts.

   Table 1: Rigor

   NIH rigor criteria are not applicable to paper type.

   Table 2: Resources

   Software and Algorithms
   Sentences	Resources
   The terms or keywords of neurological symptoms (represented by nodes) related to COVID-19 were found by systematic PubMed bibliographic literature search.	PubMed suggested: (PubMed, RRID:SCR_004846)
   Finding of the co-expressed genes of COVID-19: The important nodes (Hub-bottlenecks and driver nodes) evaluated from TN were considered as co-regulated in tissue and used as query genes to identify a set of co-expressed genes from RNA-Seq data59 (NCBI-GEO accession ID: GSE164332) of brain frontal cortex of COVID-19 patients (n=9) with healthy matched controls (n=7), using geneRecommender …

   SciScore for 10.1101/2022.04.10.487761: (What is this?)

   Please note, not all rigor criteria are appropriate for all manuscripts.

   Table 1: Rigor

   NIH rigor criteria are not applicable to paper type.

   Table 2: Resources

   Software and Algorithms
   Sentences	Resources
   The terms or keywords of neurological symptoms (represented by nodes) related to COVID-19 were found by systematic PubMed bibliographic literature search.	PubMed suggested: (PubMed, RRID:SCR_004846)
   Finding of the co-expressed genes of COVID-19: The important nodes (Hub-bottlenecks and driver nodes) evaluated from TN were considered as co-regulated in tissue and used as query genes to identify a set of co-expressed genes from RNA-Seq data59 (NCBI-GEO accession ID: GSE164332) of brain frontal cortex of COVID-19 patients (n=9) with healthy matched controls (n=7), using geneRecommender algorithm60,61 in R software and environment.	geneRecommender suggested: None
   In silico modeling of STRING-PPI network using selected co-expressed genes and genes of TN: A combined set of 225 genes collected from minet output (co-expressed genes) and all 189 genes of TN, were incorporated as a query in STRING database56 using ‘STRING-PPI combined score’ (SPPICS) 0.60 as threshold, to construct a PPI-based ‘combined gene network’ (CGN).	STRING suggested: (STRING, RRID:SCR_005223)
   Topology analysis of networks to find ‘hub’, ‘bottleneck’ and ‘driver’ nodes: The centrality measurements of networks were analyzed using the CentiScaPe module58 in Cytoscape software57 to find ‘hub’ (high degree) and ‘bottleneck’ (high-betweenness/shortest-path) nodes that having higher scores than cut-off values i.e.,	Cytoscape suggested: (Cytoscape, RRID:SCR_003032)
   The GO terms (BP, CC, MF), KEGG pathway, disease modules (DisGeNET, Jensen Disease) analyses were performed using the Enrichr platform79, 80, an intuitive web-tool for gene over-representation study with an inclusive functional annotation set, by considering each gene-set as query.	KEGG suggested: (KEGG, RRID:SCR_012773) Enrichr suggested: (Enrichr, RRID:SCR_001575)
   The pairwise SSS-II scores for statistically confident enriched terms were calculated using mclusterSim function in GOSemSim package75 as previously described methods.	GOSemSim suggested: None

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   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).

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   Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:

   The PPI model of STRING-database includes genes from prior knowledge and therefore has its own limitation56. The PPI model developed by semantic similarity scores has GO annotation biasness and unable to include genes not having sufficient annotation information. The integration of networks is supposed to perform better by filtering out the false positive interactions81,90. An approach has been reported to evaluate integrated score by combining semantic similarity scores of anatomy-based gene network and STRING-based PPI network by introducing ‘accuracy values of ROC’ as weightages to the respective scores followed by summation of weighted scores81. The same principal of weightage (‘accuracy values of ROC) was applied in the present study and the integrated scores (WHMS) were evaluated using harmonic mean of weightage scores for those gene-pairs which appeared to fulfil the criteria of having (a) three individual scores (SPPICS, SSS-I, SSS-II) and (b) at least one score with value above respective threshold level (Fig. 5b). Total 21 gene-pairs (solid edges in Fig. 5f) having integrated scores provided excellently strong fitted (AUC>0.9) and most accurate (95%) interactions (Fig. 5b) for prediction of 21 ‘candidate genes’ (Fig. 5c and Fig. 5f) involved in neurological insults (Fig. 5f) in COVID-19. All 21 gene-pairs/PPIs of ‘candidate genes’ showed SSS-I values (Fig. 3d, Fig. 4d, vide Point 4.2 in results section) above the respective threshold value and therefore represented ...

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   Results from TrialIdentifier: No clinical trial numbers were referenced.

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   Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

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   Results from JetFighter: We did not find any issues relating to colormaps.

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   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.

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   Results from scite Reference Check: We found no unreliable references.

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3. 

   Version published to 10.1101/2022.04.10.487761v1 on bioRxiv

   Apr 11, 2022