Advances in single-cell RNA sequencing (scRNA-Seq) have allowed for comprehensive analyses of single cell data. However, current analyses of scRNA-Seq data usually start from unsupervised clustering or visualization. These methods ignore prior knowledge of transcriptomes and the probable structures of the data. Moreover, cell identification heavily relies on subjective and possibly inaccurate human inspection afterwards. To address these analytical challenges, we developed SCINA (Semi-supervised Category Identification and Assignment), a semi-supervised model that exploits previously established gene signatures using an expectation-maximization (EM) algorithm. SCINA is applicable to scRNA-Seq and flow cytometry/CyTOF data, as well as other data of similar format. We applied SCINA to a wide range of datasets, and showed its accuracy, stability and efficiency, which exceeded most popular unsupervised approaches. SCINA discovered an intermediate stage of oligodendrocytes from mouse brain scRNA-Seq data. SCINA also detected immune cell population changes in cytometry data in a genetically-engineered mouse model. Furthermore, SCINA performed well with bulk gene expression data. Specifically, we identified a new kidney tumor clade with similarity to FH-deficient tumors (FHD), which we refer to as FHD-like tumors (FHDL). Overall, SCINA provides both methodological advances and biological insights from perspectives different from traditional analytical methods.
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http://dx.doi.org/10.3390/genes10070531 | DOI Listing |
Ecotoxicol Environ Saf
December 2024
Istituto Zooprofilattico Sperimentale della Sicilia "A. Mirri", Via Gino Marinuzzi 3, Palermo 90100, Italy.
The presence of microplastics (MPs), trace metals (TM) and metalloids (Ms) in surface seawater is a severe emerging issue of global concern. Information about the distribution of these pollutants is often lacking, and large-scale studies come with uncertainties because of difficult comparisons of results obtained using different methods to collect and process data. This study presents a comprehensive investigation of microplastics (MPs), trace metals (TM) and metalloids (Ms) in surface seawater during two transatlantic sampling campaigns, covering approximately 17,000 nautical miles.
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April 2024
Department of Hepatobiliary Surgery, the Affiliated Drum Tower Hospital, Medical School, Nanjing University, Nanjing, Jiangsu Province, China.
Background: Single-cell annotation plays a crucial role in the analysis of single-cell genomics data. Despite the existence of numerous single-cell annotation algorithms, a comprehensive tool for integrating and comparing these algorithms is also lacking.
Methods: This study meticulously investigated a plethora of widely adopted single-cell annotation algorithms.
Viruses
September 2023
Department of Biological Sciences, University of Cyprus, Aglantzia, 2109 Nicosia, Cyprus.
Commencing in December 2019 with the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), three years of the coronavirus disease 2019 (COVID-19) pandemic have transpired. The virus has consistently demonstrated a tendency for evolutionary adaptation, resulting in mutations that impact both immune evasion and transmissibility. This ongoing process has led to successive waves of infections.
View Article and Find Full Text PDFComput Struct Biotechnol J
July 2023
Biomedical Informatics Research Lab, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing 211198, China.
We propose PreCanCell, a novel algorithm for predicting malignant and non-malignant cells from single-cell transcriptomes. PreCanCell first identifies the differentially expressed genes (DEGs) between malignant and non-malignant cells commonly in five common cancer types-associated single-cell transcriptome datasets. The five common cancer types include renal cell carcinoma (RCC), head and neck squamous cell carcinoma (HNSCC), melanoma, lung adenocarcinoma (LUAD), and breast cancer (BC).
View Article and Find Full Text PDFViruses
December 2022
Department of Biological Sciences, University of Cyprus, Aglantzia, Nicosia 2109, Cyprus.
The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in December 2019 resulted in the coronavirus disease 2019 (COVID-19) pandemic, which has had devastating repercussions for public health. Over the course of this pandemic, the virus has continuously been evolving, resulting in new, more infectious variants that have frequently led to surges of new SARS-CoV-2 infections. In the present study, we performed detailed genetic, phylogenetic, phylodynamic and phylogeographic analyses to examine the SARS-CoV-2 epidemic in Cyprus using 2352 SARS-CoV-2 sequences from infected individuals in Cyprus during November 2020 to October 2021.
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