DNA methylation profiles for Standardized control samples
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE174390 | GEO | 2021/05/14
REPOSITORIES: GEO
Shared Molecules
Only show the datasets with similarity scores above: 0.5
Threshold
0.5
Similar Datasets
Project description:Genome-wide DNA methylation profiling of blood duplicate samples (n=128) From Sister Study were used to evaluate how concordance between duplicates were improved at sample level by various methylation preprocessing pipelines
2021-05-14 | GSE174422 | GEO
Project description:The Affymetrix oligonucleotide microarrays measure gene expression by quantifying intensity of fluorescently labeled gene fragments that bind to sets of 25-mer oligonucleotide probes on the chip with specific sequences tailored to be complementary to the target genes. Each gene is associated with a "probe set" containing several pairs (usually 11) of "perfect match" (perfectly complementary to target sequence) and "mismatch" (different base at position 13 of 25) probes. The raw measurements of each probe set consist of a set of intensities from the probes, which require in silico preprocessing by (1) correcting for background variability, (2) normalizing intensities across samples, and (3) summarizing intensities across the probe set into a single expression value. The output of the summarization step corresponds to the background-adjusted value for the mRNA of interest. We preprocess using GCRMA, which corrects for background variability by accounting for optical noise, probe affinity, and mismatch probe adjustment; normalizes intensities by quantile normalization; and summarizes intensities using a median polish method. To minimize preprocessing batch effects, it is desirable to preprocess all samples in the dataset together. However, preprocessing across multple platforms requires a consolidation of probes with identical sequences, precluding global preprocessing on datasets with multiple platforms using the standard preprocessing pipelines. To address this problem, we have developed and applied a custom preprocessing pipeline to combine the raw .CEL files from multiple platforms that share the same probe sets.
2014-09-18 | GSE60486 | GEO
Project description:DNA methylation profiles for Standardized control samples
| PRJNA729728 | ENA
Project description:We constructed a targeted cDNA microarray consisting of 147 rainbow trout (Oncorhynchus mykiss) genes with known function to examine the transcriptional response to a standardized handling stress.
2006-01-31 | E-MEXP-622 | biostudies-arrayexpress
Project description:The study employs a standardized whole-blood stimulation systems to test the hypothesis that responses to Toll-like receptor ligands or whole microbes can be defined by the combined transcriptional signatures of key effector cytokines.
2016-08-04 | GSE85176 | GEO
Project description:Preprocessing data in a reproducible and robust way is one of the current challenges in untargeted metabolomics workflows. Data curation in liquid chromatography-mass spectrometry (LC-MS) involves the removal of unwanted features (retention time; m/z pairs) to retain only high-quality data for subsequent analysis and interpretation. The present work introduces a package for the Python programming language for pre-processing LC-MS data for quality control procedures in untargeted metabolomics workflows. It is a versatile strategy that can be customized or fit for purpose according to the specific metabolomics application. It allows performing quality control procedures to ensure accuracy and reliability in LC-MS measurements, and it allows preprocessing metabolomics data to obtain cleaned matrices for subsequent statistical analysis. The capabilities of the package are showcased with pipelines for an LC-MS system suitability check, system conditioning, signal drift evaluation, and data curation. These applications were implemented to preprocess data corresponding to a new suite of plasma candidate plasma reference materials developed by the National Institute of Standards and Technology (NIST; hypertriglyceridemic, diabetic, and African-American plasma pools) to be used in untargeted metabolomics studies. in addition to NIST SRM 1950 – Metabolites in Frozen Human Plasma. The package offers a rapid and reproducible workflow that can be used in an automated or semi-automated fashion, and it is an open and free tool available to all users.
2020-11-21 | MTBLS1919 | MetaboLights
Project description:The study employs a standardized whole-blood stimulation systems to test the hypothesis that responses to Toll-like receptor ligands or whole microbes can be defined by the combined transcriptional signatures of key effector cytokines. The study encompasses the analysis of 21 distinct whole blood stimulations from 25 healthy donors from the Milieu Interieur Cohort (www.clinicaltrials.gov identifier: NCT01699893)
2016-08-04 | E-GEOD-85176 | biostudies-arrayexpress
Project description:Long non-coding RNAs (lncRNAs) play fundamental roles in cellular processes and pathologies, regulating gene expression at multiple levels. Despite being highly cell-type specific, their study at single-cell level has been challenging due to their less accurate annotation and low expression. Here, we show that single-cell RNA-seq (scRNA-seq) preprocessing workflows using the pseudoaligner Kallisto enhance the detection and quantification of lncRNAs. Further, using single-cell multiome data, we demonstrate that the ATAC-seq profiles exhibit higher concordance when the scRNA-seq is processed by Kallisto. We then experimentally confirmed the expression patterns of cell-type specific lncRNAs exclusively detected by Kallisto and unveiled biologically relevant lncRNAs, such as AL121895.1, a previously undocumented cis-repressor lncRNA, whose role in proliferation of breast cancer cells was detected by Kallisto and overlooked by other pipelines. Our results emphasize the necessity for an alternative scRNA-seq preprocessing workflow tailored to lncRNAs that sheds light on the multifaceted roles of lncRNAs.
2024-09-16 | GSE246142 | GEO
Project description:We combined the tissue preservation and single-cell resolution of laser capture with an improved preamplification procedure enabling RNA sequencing of 10 microdissected cells. This in situ 10-cell RNA sequencing (10cRNA-seq) can exploit fluorescent reporters of cell type in genetically engineered mice and is compatible with freshly cryoembedded clinical biopsies from patients. By using small pools of microdissected cells, 10cRNA-seq thus results in improved per-cell reliability and sensitivity beyond existing approaches for single-cell RNA sequencing (scRNA-seq). Accordingly, in multiple tissue and tumor settings, we observe 1.5–2-fold increases in genes detected and overall alignment rates compared to scRNA-seq. Combined with existing approaches to deconvolve small pools of cells, 10cRNA-seq offers a reliable, unbiased, and sensitive way to measure cell-state heterogeneity in tissues and tumors.
2019-03-24 | GSE120261 | GEO
Project description:Microarray-based gene expression analysis of peripheral whole blood is a common strategy in the development of clinically relevant biomarker panels for a variety of human diseases. However, the results of such an analysis are often plagued by decreased sensitivity and reliability due to the effects of relatively high levels of globin mRNA in whole blood. Globin reduction assays have been shown to overcome such effects, but they require large amounts of total RNA and may induce distinct gene expression profiles. The Illumina whole-genome DASL (WG-DASL) assay can detect gene expression levels using partially degraded RNA samples and has the potential to detect rare transcripts present in highly heterogeneous whole blood samples without the need for globin reduction. We therefore assessed the utility of the WG-DASL assay in the analysis of peripheral whole blood gene expression profiles. We find that gene expression detection is significantly increased with the use of WG-DASL compared to the standard in vitro transcription-based direct hybridization (IVT), while globin-probe-negative WG-DASL did not exhibit significant improvements over globin-probe-positive WG-DASL. Globin reduction increases the detection sensitivity and reliability of both WG-DASL and IVT with little effect on raw intensity correlations: raw intensity correlations between total RNA and globin-reduced RNA were 0.970 for IVT and 0.981 for WG-DASL. Overall, the detection sensitivity of the WG-DASL assay is higher than the IVT-based direct hybridization assay, with or without globin reduction, and should be considered in conjunction with globin reduction methods for future blood-based gene expression studies.
2011-04-01 | GSE28064 | GEO