Project description:Tissue composition is a major determinant of phenotypic variation and a key factor influencing disease outcomes. Although scRNA-Seq has emerged as a powerful technique for characterizing cellular heterogeneity, it is currently impractical for large sample cohorts and cannot be applied to fixed specimens collected as part of routine clinical care. To overcome these challenges, we extended Cell type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) into a new platform for in silico cytometry. Our approach enables the simultaneous inference of cell type abundance and cell type-specific gene expression profiles (GEPs) from bulk tissue transcriptomes. The utility of this integrated framework, called CIBERSORTx, is demonstrated in multiple tumor types, including melanoma, where single cell reference profiles are used to dissect primary clinical specimens, revealing cell type-specific signatures of driver mutations and immunotherapy response. We anticipate that digital cytometry will augment single cell profiling efforts, enabling cost-effective, high throughput tissue characterization without the need for antibodies, disaggregation, or viable cells.

2019-05-06 | GSE127462 | GEO

High-throughput tissue dissection and cell purification with digital cytometry [scRNA-Seq]

2019-05-06 | GSE127471 | GEO

High-throughput tissue dissection and cell purification with digital cytometry [healthy adults]

2019-05-06 | GSE127813 | GEO

High-throughput tissue dissection and cell purification with digital cytometry

Project description:This SuperSeries is composed of the SubSeries listed below.

2019-05-06 | GSE127472 | GEO

High-throughput SuperSAGE for digital gene expression analysis of multiple samples using Next Generation Sequencing

Project description:We established a protocol of the SuperSAGE technology combined with next-generation sequencing, coined “High-Throughput (HT-) SuperSAGE”. SuperSAGE is a method of digital gene expression profiling that allows isolation of 26-bp tag fragments from expressed transcripts. In the present protocol, index (barcode) sequences are employed to discriminate tags from different samples. Such barcodes permit to enable researchers to analyze digital tags from many transcriptomes of many samples in a single sequencing run by simply pooling the libraries. Here, we demonstrated that HT-SuperSAGE provided highly sensitive, reproducible and accurate digital gene expression data. By increasing throughput for analysis in HT-SuperSAGE, various applications were expected and several examples of its applications were introduced in the present study, including analyses of laser-microdissected cells, biological replicates or tag extraction using different anchoring enzymes.

2010-10-01 | GSE20682 | GEO

High-throughput SuperSAGE for digital gene expression analysis of multiple samples using Next Generation Sequencing

2010-09-30 | E-GEOD-20682 | biostudies-arrayexpress

MS2-affinity purification coupled with RNA sequencing (MAPS) reveals S. aureus RsaG sRNA targetome

Project description:MS2-affinity purification coupled with RNA sequencing (MAPS) reveals S. aureus RsaG sRNA targetome. Affinity purification of in vivo regulatory complexes coupled with high throughput RNA sequencing methodology or MAPS standing for “MS2 affinity purification coupled to RNA".

2024-06-01 | GSE176028 | GEO

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