sc-ImmuCC: hierarchical annotation for immune cell types in single-cell RNA-seq
Frontiers in Immunology, 2023 Accurately identifying immune cell types in single-cell RNA-sequencing (scRNA-Seq) data is critical to uncovering immune responses in health or disease conditions.
Ying Jiang +4 more
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Identifying cell types from single-cell data based on similarities and dissimilarities between cells
BMC Bioinformatics, 2021 Background With the development of the technology of single-cell sequence, revealing homogeneity and heterogeneity between cells has become a new area of computational systems biology research.
Yuanyuan Li +3 more
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Label-Free Metabolic Classification of Single Cells in Droplets Using the Phasor Approach to Fluorescence Lifetime Imaging Microscopy. [PDF]
, 2019 Characterization of single cell metabolism is imperative for understanding subcellular functional and biochemical changes associated with healthy tissue development and the progression of numerous diseases.
Aghaamoo, Mohammad +4 more
core +1 more source
Automatic cell type identification methods for single-cell RNA sequencing
Computational and Structural Biotechnology Journal, 2021 Single-cell RNA sequencing (scRNA-seq) has become a powerful tool for scientists of many research disciplines due to its ability to elucidate the heterogeneous and complex cell-type compositions of different tissues and cell populations. Traditional cell-type identification methods for scRNA-seq data analysis are time-consuming and knowledge-dependent ...
Bingbing Xie +3 more
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Shape-dependent optoelectronic cell lysis [PDF]
, 2014 We show an electrical method to break open living cells amongst a population of different cell types, where cell selection is based upon their shape.
Bao +28 more
core +1 more source
scAnnotatR: framework to accurately classify cell types in single-cell RNA-sequencing data
BMC Bioinformatics, 2022 Background Automatic cell type identification is essential to alleviate a key bottleneck in scRNA-seq data analysis. While most existing classification tools show good sensitivity and specificity, they often fail to adequately not-classify cells that are
Vy Nguyen, Johannes Griss
doaj +1 more source
Putative cell type discovery from single-cell gene expression data [PDF]
Nature Methods, 2020 We present a novel method for automated identification of putative cell types from single-cell RNA-seq (scRNA-seq) data. By iteratively applying a machine learning approach to an initial clustering of gene expression profiles of a given set of cells, we simultaneously identify distinct cell groups and a weighted list of feature genes for each group ...
Zhichao Miao +5 more
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Mapping single-cell atlases throughout Metazoa unravels cell type evolution [PDF]
eLife, 2020 AbstractComparing single-cell transcriptomic atlases from diverse organisms can elucidate the origins of cellular diversity and assist the annotation of new cell atlases. Yet, comparison between distant relatives is hindered by complex gene histories and diversifications in expression programs.
Alexander J. Tarashansky +6 more
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Lineage dynamics of murine pancreatic development at single-cell resolution. [PDF]
, 2018 Organogenesis requires the complex interactions of multiple cell lineages that coordinate their expansion, differentiation, and maturation over time.
Byrnes, Lauren E +8 more
core +2 more sources
Phenotypically supervised single-cell sequencing parses within-cell-type heterogeneity
iScience, 2021 To better understand cellular communication driving diverse behaviors, we need to uncover the molecular mechanisms of within-cell-type functional heterogeneity. While single-cell RNA sequencing (scRNAseq) has advanced our understanding of cell heterogeneity, linking individual cell phenotypes to transcriptomic data remains challenging.
Kevin Chen +7 more
openaire +5 more sources