Data analysis guidelines for single-cell RNA-seq in biomedical studies and clinical applications.

The application of single-cell RNA sequencing (scRNA-seq) in biomedical research has advanced our understanding of the pathogenesis of disease and provided valuable insights into new diagnostic and therapeutic strategies. With the expansion of capacity for high-throughput scRNA-seq, including clinical samples, the analysis of these huge volumes of data has become a daunting prospect for researchers entering this field. Here, we review the workflow for typical scRNA-seq data analysis, covering raw data processing and quality control, basic data analysis applicable for almost all scRNA-seq data sets, and advanced data analysis that should be tailored to specific scientific questions. While summarizing the current methods for each analysis step, we also provide an online repository of software and wrapped-up scripts to support the implementation. Recommendations and caveats are pointed out for some specific analysis tasks and approaches. We hope this resource will be helpful to researchers engaging with scRNA-seq, in particular for emerging clinical applications.

Prognostic Nomogram on Admission Predicting Progression for Patients with Nonsevere COVID-19

The present study aimed to establish a prognostic nomogram to stratify high-risk patients with Coronavirus Disease 2019 (COVID-19) who progressed from the nonsevere condition on admission to severe during hospitalization. This multicenter retrospective study included patients with nonsevere COVID-19 on admission from Jan 10, 2020 to Feb 7, 2020. In the training cohort, independent risk factors associated with disease progression were identified by univariate and multivariate analyses. The prognostic nomogram was established and then validated externally using C-index. The study included 351 patients (293 and 58 in the training and validation cohorts, respectively), with 27 (9.2%) and 5 (8.6%) patients progressed, respectively. In the training cohort, older age (OR 1.036, 95% CI 1.000-1.073), more lobes involved on chest CT (OR 1.841, 95% CI 1.117-3.035), comorbidity present (OR 2.478, 95% CI 1.020-6.018), and lower lymphocyte count (OR 0.081, 95% CI 0.019-0.349) were identified as independent risk factors. The prognostic nomogram was established in the training cohort with satisfied external prognostic performance (C-index 0.906, 95% CI 0.806-1.000). In conclusion, older age, comorbidity present, more lobes involved on chest CT, and lower lymphocyte count are independent risk factors associated with disease progression during hospitalization for patients with nonsevere COVID-19.

Sex differences in clinical characteristics and risk factors for mortality among severe patients with COVID-19: a retrospective study.

The coronavirus disease 2019 (COVID-19) became a global pandemic. Males, compared to females, seem to be more susceptible to COVID-19, but related evidence is scarce, especially in severe patients. We explored sex differences in clinical characteristics and potential risk factors for mortality in severe COVID-19 patients. In this retrospective cohort study, we included all severe COVID-19 patients admitted to Eastern Renmin Hospital of Wuhan University, Wuhan, China, with a definitive clinical outcome as of Apr 10, 2020. Of the included 651 patients, 332 were male, and 319 were female. Males and females did not differ in age and underlying comorbidities. Males were more likely than females to report fever and develop serious complications, including acute respiratory distress syndrome, secondary infection, acute cardiac injury, coagulopathy, acute kidney injury and arrhythmia. Further, males had much higher mortality relative to females. Multivariable regression showed neutrophilia (odds ratio 6.845, 95% CI 1.227-38.192, p=0.028), thrombocytopenia (19.488, 3.030-25.335, p=0.002), hypersensitive troponin I greater than 0.04 pg/mL (6.058, 1.545-23.755, p=0.010), and procalcitonin greater than 0.1 ng/mL (6.350, 1.396-28.882, p=0.017) on admission were associated with in-hospital death. With either of these risk factors, the cumulative survival rate was relatively lower in males than in females. In conclusion, males are more likely than females to develop serious complications and progress to death. The potential risk factors of neutrophilia, thrombocytopenia, hypersensitive troponin I greater than 0.04 pg/mL and procalcitonin more than 0.1 ng/mL may help clinicians to identify patients with poor outcomes at an early stage, especially in males.