Results 31 to 40 of about 81,661 (282)
Improved SNV discovery in barcode-stratified scRNA-seq alignments [PDF]
Genes, 2021 AbstractSingle cell SNV analysis is an emerging and promising strategy to connect cell-level genetic variation to cell phenotypes. At the present, SNV detection from 10x Genomics scRNA-seq data is typically performed on the pooled sequencing reads across all cells in a sample.
Prashant N. M. +6 more
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Pulmonary alveolar type I cell population consists of two distinct subtypes that differ in cell fate. [PDF]
, 2018 Pulmonary alveolar type I (AT1) cells cover more than 95% of alveolar surface and are essential for the air-blood barrier function of lungs. AT1 cells have been shown to retain developmental plasticity during alveolar regeneration.
Cai, Tao +11 more
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Global Gene Expression Analysis Identifies Age-Related Differences in Knee Joint Transcriptome during the Development of Post-Traumatic Osteoarthritis in Mice. [PDF]
, 2020 Aging and injury are two major risk factors for osteoarthritis (OA). Yet, very little is known about how aging and injury interact and contribute to OA pathogenesis.
Christiansen, Blaine A +7 more
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GNN-based embedding for clustering scRNA-seq data
Bioinformatics, 2021 Abstract Motivation Single-cell RNA sequencing (scRNA-seq) provides transcriptomic profiling for individual cells, allowing researchers to study the heterogeneity of tissues, recognize rare cell identities and discover new cellular subtypes.
Madalina Ciortan, Matthieu Defrance
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Cancer Communications, 2020 Single‐cell RNA sequencing (scRNA‐seq) is a novel technology that allows transcriptomic analyses of individual cells. During the past decade, scRNA‐seq sensitivity, accuracy, and efficiency have improved due to innovations including more sensitive ...
Shuning Ding, Xiaosong Chen, Kunwei Shen
doaj +1 more source
Identification of cell barcodes from long-read single-cell RNA-seq with BLAZE
Genome Biology, 2023 Long-read single-cell RNA sequencing (scRNA-seq) enables the quantification of RNA isoforms in individual cells. However, long-read scRNA-seq using the Oxford Nanopore platform has largely relied upon matched short-read data to identify cell barcodes. We
Yupei You +6 more
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constclust: Consistent Clusters for scRNA-seq [PDF]
, 2020 1AbstractUnsupervised clustering to identify distinct cell types is a crucial step in the analysis of scRNA-seq data. Current clustering methods are dependent on a number of parameters whose effect on the resulting solution’s accuracy and reproducibility are poorly understood. The adjustment of clustering parameters is therefore ad-hoc, with most users
Isaac Virshup +3 more
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Tumor Functional Heterogeneity Unraveled by scRNA-seq Technologies [PDF]
Trends in Cancer, 2020 Effective cancer treatment has been precluded by the presence of various forms of intratumoral complexity that drive treatment resistance and metastasis. Recent single-cell sequencing technologies are significantly facilitating the characterization of tumor internal architecture during disease progression.
González Silva, Laura +2 more
openaire +5 more sources
Inferring spatial and signaling relationships between cells from single cell transcriptomic data. [PDF]
, 2020 Single-cell RNA sequencing (scRNA-seq) provides details for individual cells; however, crucial spatial information is often lost. We present SpaOTsc, a method relying on structured optimal transport to recover spatial properties of scRNA-seq data by ...
Cang, Zixuan, Nie, Qing
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