## 3 Results and Analysis
Single-cell RNA-seq reveals ectopic and aberrant lung-resident cell populations in idiopathic pulmonary fibrosis. _Sci. Adv._**2020**, \(6\), eaba1988. [CrossRef]
* [PERSON] (2014) [PERSON] Single-cell sequencing. _Nat. Methods_**2014**, _11_, 18. [CrossRef]
* [PERSON] et al. (2016) [PERSON]; [PERSON]; [PERSON] Single-cell genome sequencing: Current state of the science. _Nat. Rev. Genet._**2016**, _17_, 175-188. [CrossRef]
* [PERSON] (2010) [PERSON] Sequencing technologies--The next generation. _Nat. Rev. Genet._**2010**, _11_, 31-46. [CrossRef] [PubMed]
* [PERSON] et al. (2016) [PERSON]; [PERSON]; [PERSON]; [PERSON] Comparison of methods to detect differentially expressed genes between single-cell populations. _Brief. Bioinform._**2016**, _18_, 735-743. [CrossRef] [PubMed]
* [PERSON] et al. (2019) [PERSON]; [PERSON]; [PERSON]; [PERSON] Comparative analysis of differential gene expression analysis tools for single-cell RNA sequencing data. _BMC Bioinform._**2019**, _20_, 40. [CrossRef] [PubMed]
* [PERSON] and [PERSON] (2019) [PERSON]; [PERSON] [PERSON] Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression. _Genome Biol._**2019**, _20_, 296. [CrossRef]
* [PERSON] et al. (2019) [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON] Benchmark and Parameter Sensitivity Analysis of Single-Cell RNA Sequencing Clustering Methods. _Front. Genet._**2019**, _10_, 1253. [CrossRef]
* [PERSON] et al. (2015) [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] A survey of human brain transcriptome diversity at the single cell level. _Proc. Natl. Acad. Sci. USA_**2015**, _112_, 7285-7290. [CrossRef]* _[PERSON] et al. (2015)_ [PERSON]; [PERSON]; [PERSON]; [PERSON] ROTS: Reproducible RNA-seq biomarker detector--Prognostic markers for clear cell renal cell cancer. _Nucleic Acids Res._**2015**, _44_, e1. [CrossRef]
* _[PERSON] et al. (2008)_ [PERSON]; [PERSON]; [PERSON]; [PERSON] Reproducibility-Optimized Test Statistic for Ranking Genes in Microarray Studies. _IEEE/ACM Trans. Comput. Biol. Bioinform._**2008**, \(5\), 423-431. [CrossRef]
* _[PERSON] et al. (2014)_ [PERSON]; [PERSON]; [PERSON] HTSeq--A Python framework to work with high-throughput sequencing data. _Bioinformatics_**2014**, _31_, 166-169. [CrossRef]
* [PERSON] et al. (2015) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Single-cell RNA-seq reveals changes in cell cycle and differentiation programs upon aging of hematopoietic stem cells. _Genome Res._**2015**, _25_, 1860-1872. [CrossRef]
* _[PERSON] et al. (2014)_ [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON] voom: Precision weights unlock linear model analysis tools for RNA-seq read counts. _Genome Biol._**2014**, _15_, R29. [CrossRef] [PubMed]
* _[PERSON] et al. (2012)_ [PERSON]; [PERSON]; [PERSON] Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation. _Nucleic Acids Res._**2012**, _40_, 4288-4297. [CrossRef] [PubMed]
* _[PERSON] et al. (2021)_ [PERSON]; [PERSON]; [PERSON] Software Benchmark--Classification Tree Algorithms for Cell Atlases Annotation Using Single-Cell RNA-Sequencing Data. _Microbiol. Res._**2021**, _12_, 20022. [CrossRef]
* _[PERSON] et al. (2018)_ [PERSON]; [PERSON] Bias, robustness and scalability in single-cell differential expression analysis. _Nat. Methods_**2018**, _15_, 255-261. [CrossRef] [PubMed]

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