Technical controls MiCA
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB30293 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR3287885_1.fastq.gz | Fastqsanger.gz | |||
| ERR3287885_2.fastq.gz | Fastqsanger.gz | |||
| ERR4674613_1.fastq.gz | Fastqsanger.gz | |||
| ERR4674613_2.fastq.gz | Fastqsanger.gz | |||
| ERR5418250_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 190 |
Similar Datasets
Project description:2-4-8 cell porcine embryo technical repeat dye-swap for Agilent EMPV1 (4x44k Format)
2013-02-25 | GSE34157 | GEO
Project description:Background: RNA-seq is revolutionizing the way we study transcriptomes. mRNA can be surveyed without prior knowledge of gene transcripts. Alternative splicing of transcript isoforms and the identification of previously unknown exons are being reported. Initial reports of differences in exon usage, and splicing between samples as well as quantitative differences among samples are beginning to surface. Biological variation has been reported to be larger than technical variation. In addition, technical variation has been reported to be in line with expectations due to random sampling. However, strategies for dealing with technical variation will differ depending on the magnitude. The size of technical variance, and the role of sampling are examined in this manuscript. Results: Independent Solexa/Illumina experiments containing technical replicates are analyzed. When coverage is low, large disagreements between technical replicates are apparent. Exon detection between technical replicates is highly variable when the coverage is less than 5 reads per nucleotide and estimates of gene expression are more likely to disagree when coverage is low. Although large disagreements in the estimates of expression are observed at all levels of coverage. Conclusions: Technical variability is too high to ignore. Technical variability results in inconsistent detection of exons at low levels of coverage. Further, the estimate of the relative abundance of a transcript can substantially disagree, even when coverage levels are high. This may be due to the low sampling fraction and if so, it will persist as an issue needing to be addressed in experimental design even as the next wave of technology produces larger numbers of reads. We provide practical recommendations for dealing with the technical variability, without dramatic cost increases.
2014-01-15 | GSE54068 | GEO
Project description:Background: RNA-seq is revolutionizing the way we study transcriptomes. mRNA can be surveyed without prior knowledge of gene transcripts. Alternative splicing of transcript isoforms and the identification of previously unknown exons are being reported. Initial reports of differences in exon usage, and splicing between samples as well as quantitative differences among samples are beginning to surface. Biological variation has been reported to be larger than technical variation. In addition, technical variation has been reported to be in line with expectations due to random sampling. However, strategies for dealing with technical variation will differ depending on the magnitude. The size of technical variance, and the role of sampling are examined in this manuscript. Results: Independent Solexa/Illumina experiments containing technical replicates are analyzed. When coverage is low, large disagreements between technical replicates are apparent. Exon detection between technical replicates is highly variable when the coverage is less than 5 reads per nucleotide and estimates of gene expression are more likely to disagree when coverage is low. Although large disagreements in the estimates of expression are observed at all levels of coverage. Conclusions: Technical variability is too high to ignore. Technical variability results in inconsistent detection of exons at low levels of coverage. Further, the estimate of the relative abundance of a transcript can substantially disagree, even when coverage levels are high. This may be due to the low sampling fraction and if so, it will persist as an issue needing to be addressed in experimental design even as the next wave of technology produces larger numbers of reads. We provide practical recommendations for dealing with the technical variability, without dramatic cost increases.
2014-01-15 | GSE54067 | GEO
Project description:Background: Studies recently support that non-HLA antigens could be additional targets of injury in organ transplant recipients, and MICA was associated with an increased risk of graft loss. Methods: A ProtoArray platform was used to study 37 serum samples from 22 unique patients (15 renal recipients and 7 healthy controls). Thirty paired pre- and post-transplant serum samples were analyzed for detection of de novo post-transplant antibody responses in the 15 patients (10 acute rejection (AR), 5 Stable). Probes on ProtoArray and cDNA platforms (GSE: 3931) were re-annotated and compartment specific gene lists were analyzed using the integrated genomics method. Normal and transplant kidney IHC were performed for MICA antigen localization. Results: Mean MICA-Ab (antibody) signal intensity was significantly higher in transplant patients compared with healthy controls and de novo MICA-Ab were detected in 73% transplant patients. The mean post-transplant signal intensity of MICA-Ab was the highest in C4d+AR. Detection of MICA-Ab responses did not correlate with time post-transplantation, but significantly correlated with decline in graft function over the subsequent year. Integrative genomics predicted localization of the MICA antigen to the glomerulus. IHC confirmed cytoplasmic MICA staining solely in glomerular podocytes in normal kidney. In the transplant kidney, infiltrating mononuclear lymphocytes (T, B and NK) in AR had additional MICA staining. Conclusions: MICA can be highly detected regardless of graft dysfunction or AR. The intensity signal of the MICA antibody correlates with subsequent decline in graft function. The MICA antigen localizes to the glomerulus and infiltrating mononuclear cells in AR.
2009-01-16 | GSE14329 | GEO
Project description:RNA-seq: technical variability and sampling
| PRJNA234515 | ENA
Project description:Analysis of technical variance of ChIP-on-Chip studies by characterization of Myc-binding in HL60 cells. Keywords: Chip-on-chip
2008-11-01 | GSE8448 | GEO
Project description:We profiled DNA from liver and placenta technical replicate samples on the Illumina HumanMethylation450 BeadChip array. There technical replicates represent a single liver and a single placenta sample.
2014-02-19 | GSE52731 | GEO
Project description:Background: Studies recently support that non-HLA antigens could be additional targets of injury in organ transplant recipients, and MICA was associated with an increased risk of graft loss. Methods: A ProtoArray platform was used to study 37 serum samples from 22 unique patients (15 renal recipients and 7 healthy controls). Thirty paired pre- and post-transplant serum samples were analyzed for detection of de novo post-transplant antibody responses in the 15 patients (10 acute rejection (AR), 5 Stable). Probes on ProtoArray and cDNA platforms (GSE: 3931) were re-annotated and compartment specific gene lists were analyzed using the integrated genomics method. Normal and transplant kidney IHC were performed for MICA antigen localization. Results: Mean MICA-Ab (antibody) signal intensity was significantly higher in transplant patients compared with healthy controls and de novo MICA-Ab were detected in 73% transplant patients. The mean post-transplant signal intensity of MICA-Ab was the highest in C4d+AR. Detection of MICA-Ab responses did not correlate with time post-transplantation, but significantly correlated with decline in graft function over the subsequent year. Integrative genomics predicted localization of the MICA antigen to the glomerulus. IHC confirmed cytoplasmic MICA staining solely in glomerular podocytes in normal kidney. In the transplant kidney, infiltrating mononuclear lymphocytes (T, B and NK) in AR had additional MICA staining. Conclusions: MICA can be highly detected regardless of graft dysfunction or AR. The intensity signal of the MICA antibody correlates with subsequent decline in graft function. The MICA antigen localizes to the glomerulus and infiltrating mononuclear cells in AR. Pre- and post-transplant serum antibodies were profiled for each patient, using the Invitrogen ProtoArray® Human Protein Microarray v3.0 platform (Invitrogen, Carlsbad, CA). This platform contains 5,056 non-redundant human proteins expressed in a baculovirus system, purified from insect cells and printed in duplicate onto a nitrocellulose-coated glass slide. Each protein is spotted twice on each array, to measure the quality of the signal intensity. Details for experiment processing and analysis follow the previous publication from our group (13). Prospector software was used to retrieve the expression based on immune response profiling of the .gal files.
2010-05-06 | E-GEOD-14329 | biostudies-arrayexpress
Project description:Five aliquots of the same RNA sample were labeled and hybridized in parallel to the L. vannamei microarray, in order to assess the technical reproducibility of the tool Keywords: technical validation
2006-06-01 | GSE4954 | GEO
Project description:Technical variance is a major confounding factor in single-cell RNA sequencing, not least because measurements on the same cell are not replicable. We developed BEARscc, a tool that simulates experiment-specific technical replicates based on a probabilistic model of technical variance trained on RNA spike-in measurements. We demonstrate that the tool improves the unsupervised classification of cells and aids the interpretation of single-cell RNA-seq experiments.
2018-04-03 | GSE95155 | GEO