Profiling of Sarcomas from Archival Tissues [snRNA-Seq]
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ABSTRACT:
PROVIDER: PRJNA1018225 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Profiling of Sarcomas from Archival Tissues
| PRJNA1018223 | ENA
Project description:We performed single nuclei RNA-sequencing (snRNA-seq) with matched T cell receptor sequencing (TCR-seq), and pool matched low pass whole genome sequencing (WGS) of eight specimens from six patients, encompassing four undifferentiated polymorphic sarcomas (UPS) and four intimal sarcomas (INS), and paired specimens from two patients (one UPS and INS each) treated with immune checkpoint blockade (ICB).
2024-06-21 | GSE243380 | GEO
Project description:Profiling of Sarcomas from Archival Tissues [TCR-Seq]
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Project description:Profiling of Sarcomas from Archival Tissues [lp-WGS]
| PRJNA1018219 | ENA
Project description:We performed single nuclei RNA-sequencing (snRNA-seq) with matched T cell receptor sequencing (TCR-seq), and pool matched low pass whole genome sequencing (WGS) of eight specimens from six patients, encompassing four undifferentiated polymorphic sarcomas (UPS) and four intimal sarcomas (INS), and paired specimens from two patients (one UPS and INS each) treated with immune checkpoint blockade (ICB).
2024-06-21 | GSE243379 | GEO
Project description:We performed single nuclei RNA-sequencing (snRNA-seq) with matched T cell receptor sequencing (TCR-seq), and pool matched low pass whole genome sequencing (WGS) of eight specimens from six patients, encompassing four undifferentiated polymorphic sarcomas (UPS) and four intimal sarcomas (INS), and paired specimens from two patients (one UPS and INS each) treated with immune checkpoint blockade (ICB).
2024-06-21 | GSE243377 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below.
2024-06-21 | GSE243381 | GEO
Project description:Single cell sequencing technologies have revolutionized our understanding of biology by mapping cell diversity and gene expression in healthy and diseased tissues. While single-cell RNA sequencing (scRNA-seq) has been widely used, interest in single-nucleus RNA sequencing (snRNA-seq) is growing due to its benefits, including the ability to analyze archival tissues and capture rare cell types that are challenging to dissociate. However, comparative studies across tissues have yielded mixed results, with some reporting enhanced cell type retention using snRNA-seq while others finding cell type identification to be challenging in snRNA-seq data. The GUDMAP consortium aims to construct a molecular atlas of the lower urinary tract (LUT); thus, we set out to determine the strengths and limitations of each approach in characterizing LUT cell types. Using the human bladder, we determined that scRNA-seq offered more discriminative gene sets for identification while snRNA-seq could facilitate capture of previously underrepresented cell types.
2024-11-18 | GSE267964 | GEO
Project description:Over 20 million archival tissue samples are stored annually in the United States as formalin-fixed, paraffin-embedded (FFPE) tissue blocks, but only recently has whole-genome expression profiling from these samples become technically feasible. Here, we introduce novel general methods for assessing, summarizing, and visualizing expression data quality from archival samples. We validated these methods in technical study of 144 clinical breast cancer and autopsy samples and in an overview of all current publicly available FFPE whole-genome expression data. We additionally performed a case study incorporating over 1,000 colorectal cancer (CRC) samples collected from patients across the United States over a period of more than 25 years, integrating clinicopathological information, tumor molecular data, and archival tissue gene expression on an unparalleled scale. Both large-scale clinical studies presented a much greater range of data quality than previous smaller studies, emphasizing the need for rigorous quality control in translational applications of archival tissue gene expression profiling.
2012-10-02 | GSE32651 | GEO
Project description:Over 20 million archival tissue samples are stored annually in the United States as formalin-fixed, paraffin-embedded (FFPE) tissue blocks, but only recently has whole-genome expression profiling from these samples become technically feasible. Here, we introduce novel general methods for assessing, summarizing, and visualizing expression data quality from archival samples. We validated these methods in technical study of 144 clinical breast cancer and autopsy samples and in an overview of all current publicly available FFPE whole-genome expression data. We additionally performed a case study incorporating over 1,000 colorectal cancer (CRC) samples collected from patients across the United States over a period of more than 25 years, integrating clinicopathological information, tumor molecular data, and archival tissue gene expression on an unparalleled scale. Both large-scale clinical studies presented a much greater range of data quality than previous smaller studies, emphasizing the need for rigorous quality control in translational applications of archival tissue gene expression profiling. This series includes 1,003 FFPE-preserved CRC tumors, assayed by Illumina HumanRef-v3 WG-DASL microarray.
2012-10-02 | E-GEOD-32651 | biostudies-arrayexpress