Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA277488 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology (Illumina_HT12)
| PRJNA277480 | ENA
Project description:Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology (Affymetrix_HTA2.0)
| PRJNA277540 | ENA
Project description:Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology (Agilent_4x44K)
| PRJNA277482 | ENA
Project description:Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology (RNA-seq_RiboZero)
| PRJNA277468 | ENA
Project description:Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology (RNA-seq_ClonTech)
| PRJNA277470 | ENA
Project description:Spatial transcriptomic technologies are promising tools to reveal fine anatomical profiles of tissues. In the case of methodologies utilizing barcoded probe arrays, achieving a balance among probe barcoding complexity, cost, gene capture sensitivity, and spatial resolution is crucial for accelerating the spreading speed of spatial transcriptomic in basic science and clinical work. Here, we developed spatially cellular-level RNA-capture probe arrays using miniaturized microfluidic and microarray technologies. By leveraging the predetermined and cost-effective probe fixation characteristics of this methodology, we significantly reduced the consumable cost of the probe array to $0.31/mm2 and fabrication time to approximately 2 hours. Furthermore, the modification of the RNA-capture probe on sequencing slides by microfluidic chip does not rely on large imaging or printing instruments. Notably, the efficiency of the transcript captured by the probe array is even comparable to conventional single-cell RNA sequencing. Based on this technology, the stacked three-dimensional transcriptome atlas and the spatial cell heterogeneity of mouse brains were successfully visualized. Taken together, we present an experimental and analytical framework for the spatial investigation of mouse brain structures and cell phenotypes.
2024-05-01 | GSE247834 | GEO
Project description:In this study we performed a genome wide analysis of the entire complement of mRNAs in clear cell renal cell carcinomas (ccRCC) by means of the Affymetrix Exon Array platform. The analyses were performed both at gene and exon level. Under our parameters over 2,000 genes resulted differentially expressed, and about 250 genes resulted alternative spliced showing differential inclusion of specific cassette exons comparing tumor and non tumoral tissues. 20 total samples were used for exon array analysis: 10 ccRCC tumor sample (T) and their matched non-tumor (NT) kidney tissues samples. All exon array data were analyzed using Partek Genomic Suite 6.4 software (Partek). The robust multi-array average (RMA) algorithm was used for the gene- and exon-level intensity analyses. Data were M-oM-,M-^Altered to consider only those probe sets included in the M-bM-^@M-^\Core Meta-ProbesetM-bM-^@M-^]. Lists of genes and exons with significant variation of the expression levels were generated by using a 0.01 FDR criterion as a significant cutoff. Partek list of significant exon-level probesets (FDR corrected p-value < 0.01) and exon level ANOVA test list were used to create - by an ad hoc Python script - a database of significant probesets from Exon Array experiments. To make more stringent the analysis criteria we excluded from the final exon lists all those cases in which Exon Array revealed a significant change at gene-level. This database we created has been used to explore simple exon skipping events using as reference ASPicDB single exon skipping splicing events after mapping Affymetrix probesets on ASPicDB .gtf files. A single exon from the Partek list was defined significantly skipped only if its adjacent exons were not, by using 0.01 and 0.05 p-value criterions as a significant cutoff for the M-bM-^@M-^\skippedM-bM-^@M-^] and adjacent exons, respectively.
2013-09-06 | E-GEOD-47032 | biostudies-arrayexpress
Project description:cDNA and cRNA hybridization technologies have different, probe-specific sensitivities. We used samples from an etanercept trial (GSE11903) to explore in a real-life setting the uniqueness of each platform.
2013-01-28 | GSE41663 | GEO
Project description:Proteomic technologies based on mass spectrometry (MS) have greatly evolved in the past years, and nowadays it is possible to routinely identify thousands of peptides from complex biological samples in a single LC-MS/MS experiment. Despite the advancements in proteomic technologies, the scientific community still faces important challenges in terms of depth and reproducibility of proteomics analyses. Here, we present a multicenter study designed to evaluate long-term performance of LC-MS/MS platforms within the Spanish Proteomics Facilities Network (ProteoRed-ISCIII). The study was performed under well-established standard operating procedures, and demonstrated that it is possible to attain high qualitative and quantitative reproducibility over time. Our study highlights the importance of deploying platform quality assessment metrics in multi-laboratory studies in early LC-MS/MS system troubleshooting.
2015-07-20 | PXD000205 | Pride