Betacoronavirus-specific alternate splicing

  1. Guy Karlebach
  2. Bruce Aronow
  3. Stephen B. Baylin
  4. Daniel Butler
  5. Jonathan Foox
  6. Shawn Levy
  7. Cem Meydan
  8. Christopher Mozsary
  9. Amanda M. Saravia-Butler
  10. Deanne M. Taylor
  11. Eve Wurtele
  12. Christopher E. Mason
  13. Afshin Beheshti
  14. Peter N. Robinson

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Abstract

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  1. Version published to 10.1016/j.ygeno.2022.110270
  2. ScreenIT

    SciScore for 10.1101/2021.07.02.450920: (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
    SentencesResources
    All these datasets were downloaded from NCBI’s Short Read Archive (SRA) [19].
    Short Read Archive
    suggested: None
    Except for the nasal swab (NSPP) dataset [27], all datasets were processed using a snakemake pipeline that performs the following steps: samples are downloaded from the SRA, quality-control is performed using fastp [30], alignment to Genome Reference Consortium Human Build 38 version 91 is done using STAR [31], and isoform quantification carried out by RSEM [32].
    RSEM
    suggested: (RSEM, RRID:SCR_013027)
    Reads classified as human using Kraken2 [33] were processed as described in https://github.com/asaravia-butler/COV-IRT/blob/main/RNAseq/Raw_to_Aligned_Data_Pipeline.md and https://github.com/asaravia-butler/COV-IRT/blob/main/RNAseq/RSEM_Counts_Pipeline.md. First, adapters and low-quality data were trimmed with Trimmomatic (v0.39) [34].
    Kraken2
    suggested: None
    Trimmomatic
    suggested: (Trimmomatic, RRID:SCR_011848)
    Kraken2-human classified raw and trimmed read quality were evaluated with FastQC (v0.11.9) (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/), and MultiQC (v1.9) [35] was used to generate MultiQC reports.
    FastQC
    suggested: (FastQC, RRID:SCR_014583)
    MultiQC
    suggested: (MultiQC, RRID:SCR_014982)
    Homo sapiens STAR and RSEM references were built using STAR (v2.7.3a) [31] and RSEM (v1.3.1) [32], respectively, with Ensembl release 100 human genome version GRCh38 (Homo_sapiens.GRCh38.dna.primary_assembly concatenated with the SARS-CoV-2 Wuhan-Hu-1 SARS-CoV-2 reference genome ASM985889v3, and the following Ensembl gtf annotation file: Homo_sapiens.GRCh38.100.gtf concatenated with Sars_cov_2.ASM985889v3.101.gtf. rRNA-depleted trimmed reads were aligned to the Homo sapiens and SARS-CoV-2 STAR reference with STAR twopassMode (v2.7.3a) [31].
    STAR
    suggested: (STAR, RRID:SCR_004463)
    Ensembl
    suggested: (Ensembl, RRID:SCR_002344)
    Gene Ontology Analysis: We implemented a version of the Ontologizer [39] analysis code in our Java library phenol (https://github.com/monarch-initiative/phenol).
    Ontologizer
    suggested: (Ontologizer, RRID:SCR_005801)

    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.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2021.07.02.450920v1 on bioRxiv