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Systems-Level Insights into Bronchopulmonary Dysplasia from Meta-Analysis of Genome- Scale Studies

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Happs C   +11 more
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Single-Cell RNAseq Clustering

2022
Single-cell RNA sequencing (scRNA-seq) allows the creation of large collections of individual cells transcriptome. Unsupervised clustering is an essential element for the analysis of these data, and it represents the initial step for the identification of different cell types to investigate the cell subpopulation organization of a sample.
Beccuti M., Calogero R. A.
openaire   +3 more sources

Single-Cell RNAseq Complexity Reduction

2022
An important step in single-cell RNAseq data analysis is the preparation of the single cell transcription data for cell sub-population partitioning. In this chapter, we describe how to perform complexity reduction for 3' end single-cell RNAseq transcriptomics data.
Cordero, Francesca, Calogero, Raffaele A
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Single-Cell RNAseq Analysis of lncRNAs

2021
Mammalian genomes are pervasively transcribed and a small fraction of RNAs produced codify for proteins. The importance of noncoding RNAs for the maintenance of cell functions is well known (e.g., rRNAs, tRNAs), but only recently it was first demonstrated the involvement of microRNAs (miRNAs) in posttranscriptional regulation and then the activity of ...
Cagnin S.   +3 more
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[RNAseq in routine oncology].

Annales de pathologie, 2021
High throughput RNA sequencing, also know as RNAseq, can easily be performed on the gold-standard technique of formalin-fixed paraffin-embedded tissue, which has long been successfully used in routine practice by pathologists. For this reason, RNAseq has been fully adopted in a very short period of time in most French molecular platforms of cancer ...
Nicolas, Piton   +4 more
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