9a11ec6d-5f16-4422-8dff-6687bc802c9b - samples
Ontology highlight
ABSTRACT:
PROVIDER: EGAD00001007863 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:CTCF ChIP-seq of 39 primary samples derived from human acute leukemias, namely AML, T-ALL and mixed myeloid/lymphoid leukemias with CpG Island Methylator Phenotype (CIMP). Due to patient confidentiality considerations, the raw data files for this dataset have been deposited to the EGA controlled-access archive under the accession numbers EGAS00001007094 (study); EGAD00001011059 (dataset).
2023-08-31 | E-MTAB-13117 | biostudies-arrayexpress
Project description:RNAseq data set of BCL11B, 519 samples
| EGAD00001007670 | EGA
Project description:H3K27ac ChIP-seq of 79 primary samples derived from human acute leukemias, namely AML, T-ALL and mixed myeloid/lymphoid leukemias with CpG Island Methylator Phenotype (CIMP). In addition, 4 samples derived from CD34+ cord blood cells of healthy donors were included. Due to patient confidentiality considerations, the raw data files for this dataset have been deposited to the EGA controlled-access archive under the accession numbers EGAS00001007094 (study); EGAD00001011060 (dataset).
2023-08-31 | E-MTAB-13119 | biostudies-arrayexpress
Project description:Aim: We aim to compare current (MeDIP-seq), new (Illumina Infinium 450K BeadChip) and future (PacBio) methods for whole genome DNA methylation analysis. As the interest in determination of disease methylation profiles increases, the scope, advantages and limitations of these methods requires assessment. There are key questions to answer and specific challenges to overcome. For example, how much detail/resolution is sufficient to identify regions of differential methylation and regions of biological/medical significance within a sample? How much coverage of the genome is required for accurate methylation analysis? Is it important to confirm which regions of the genome are unmethylated in addition to focusing on those that are methylated? Loss of methylation may be of equal importance within the cell since this may also contribute to disease pathogenesis. A multi-method (affinity enrichment/bisulphite-conversion based/direct sequencing of methyl-cytosine) and technology platform (Illumina HiSeq/PacBio/Illumina Infinium BeadChip) comparison will enable us to determine the strengths and weakness of each method. We propose to compare four methods using two DNA samples from the Coriell Institute for Cell Repository to assess both current and future capabilities for whole genome methylation analysis in parallel: A) MeDIP-seq using Illumina HiSeq B) Illumina Infinium HumanMethylation 450K BeadChip and C) whole genome methylation sequencing using PacBio. Existing single molecule deep bisulphite sequencing data generated previously from these same samples at the WTSI for targeted regions (30-40 genes) on the human X chromosome will be used to assess performance of each method. The methods selected for this study will generate data covering a range of resolutions from a whole genome scan to array (target defined) resolution and up to single base pair, single molecule resolution; the highest level of detail possible with methods currently available.Samples: DNA from sibling pair GM01240 (female) and GM01240 (male).Requirements: Both samples will be analysed using;A.MeDIP-seq using Illumina HiSeq (one HiSeq lane, 75bp paired end, per sample) B.Illumina Infinium HumanMethylation 450K BeadChipWe are expecting a potentially unnecessary high coverage using one HiSeq lane per sample. However, for the MeDIP procedure we do not have a multiplexing procedure in place. Our requirements for PacBio sequencing have been discussed with and will be supported by the Sequencing Technology Development group.
2013-01-22 | E-ERAD-139 | biostudies-arrayexpress
Project description:Previously, we published a dataset of human blood plasma and serum samples of 10 healthy males and 10 healthy females, fractionated on a set of sorbents (cation exchange Toyopearl CM-650M, CM Bio-Gel A, SP Sephadex C-25 and anion exchange QAE Sephadex A-25) and analyzed by LC-MS/MS individually and pooled in equal amounts (Supplementary Table S1, Sheet 1) [33]. The mass spectrometry peptidomics data was deposited to the ProteomeXchange Consortium via the PRIDE partner repository (dataset identifiers PXD008141 and 10.6019/PXD008141). Direct download link: http://www.ebi.ac.uk/pride/archive/projects/PXD008141. We analyzed this dataset again within this work. The detailed information about the dataset of blood plasma/serum samples of 20 healthy donors fractionated on a set of sorbents is available in the original paper [33], including the clinical parameters of the donors, sample collection, plasma/serum fractionation, peptide extraction and LC-MS/MS analysis. 33. Arapidi, G. et al. Peptidomics dataset: Blood plasma and serum samples of healthy donors fractionated on a set of chromatography sorbents. Data Brief 18, 1204–1211 (2018).
2024-06-14 | PXD027587 | Pride
Project description:This experiment contains a subset of data from the BLUEPRINT Epigenome project ( http://www.blueprint-epigenome.eu ), which aims at producing a reference haemopoetic epigenomes for the research community. 74 samples of primary cells or cultured primary cells of different haemopoeitc lineages from cord blood, venous blood, bone marrow and thymus are included in this experiment. This ArrayExpress record contains only meta-data. Raw data files have been archived at the European Genome-Phenome Archive (EGA, www.ebi.ac.uk/ega) by the consortium, with restricted access to protect sample donors' identity. There are 32 EGA data set accessions, which can be found under the Comment[EGA_DATA_SET] column in the 'Sample Data Relationship Format' (SDRF) file of this ArrayExpress record (http://www.ebi.ac.uk/arrayexpress/files/E-MTAB-3827/E-MTAB-3827.sdrf.txt). Details on how to apply for data access via the BLUEPRINT data access committee are on the EGA data set pages. Likewise, mapping of samples to these EGA accessions can be found in the SDRF file. Please note that the raw data files for 11 sequencing runs have yet been deposited at EGA, so they are marked with \\ot available\\ under the Comment[SUBMITTED_FILE_NAME] field in the SDRF file, and were included for the sake of completeness. Further iInformation on individual samples and sequencing libraries can also be found on the BLUEPRINT data coordination centre (DCC) website: http://dcc.blueprint-epigenome.eu\
2015-09-30 | E-MTAB-3827 | biostudies-arrayexpress
Project description:This experiment contains a subset of data from the BLUEPRINT Epigenome project ( http://www.blueprint-epigenome.eu ), which aims at producing a reference haemopoetic epigenomes for the research community. 4 samples of primary cells from tonsil with cell surface markes CD20med/CD38high in young individuals (3 to 10 years old) are included in this experiment. This ArrayExpress record contains only meta-data. Raw data files have been archived at the European Genome-Phenome Archive (EGA, www.ebi.ac.uk/ega) by the consortium, with restricted access to protect sample donors' identity. The relevant accessions of EGA data sets is EGAD00001001523. Details on how to apply for data access via the BLUEPRINT data access committee are on the EGA data set pages. The mapping of samples to these EGA accessions can be found in the 'Sample Data Relationship Format' file of this ArrayExpress record. Information on individual samples and sequencing libraries can also be found on the BLUEPRINT data coordination centre (DCC) website: http://dcc.blueprint-epigenome.eu
2016-05-12 | E-MTAB-4754 | biostudies-arrayexpress
Project description:This experiment contains a subset of data from the BLUEPRINT Epigenome project ( http://www.blueprint-epigenome.eu ), which aims at producing a reference haemopoetic epigenomes for the research community. 29 samples of primary cells or cultured primary cells of different haemopoeitc lineages from cord blood are included in this experiment. This ArrayExpress record contains only meta-data. Raw data files have been archived at the European Genome-Phenome Archive (EGA, www.ebi.ac.uk/ega) by the consortium, with restricted access to protect sample donors' identity. The relevant accessions of EGA data sets is EGAD00001001165. Details on how to apply for data access via the BLUEPRINT data access committee are on the EGA data set pages. The mapping of samples to these EGA accessions can be found in the 'Sample Data Relationship Format' file of this ArrayExpress record. Information on individual samples and sequencing libraries can also be found on the BLUEPRINT data coordination centre (DCC) website: http://dcc.blueprint-epigenome.eu
2015-09-30 | E-MTAB-3819 | biostudies-arrayexpress
Project description:Since short reads from Illumina RNA-seq data are challenging to map to repetitive elements , we wanted to confirm the bulk RNA-seq findings using an orthogonal method, namely, using the long read technology of Pacific Biosciences (PacBio) full-length transcriptome sequencing. This dataset provided around 1.1 (WT) and 1.3 (RBM4 KO) million sequence reads of 2.6 kb average length mapping to the human genome.
2020-10-20 | GSE147896 | GEO
Project description:In the past decades, the incidence of esophageal adenocarcinoma has increased dramatically in Western populations. Better understanding of disease etiology along with the identification of novel prognostic and predictive biomarkers are urgently needed to improve the dismal survival probabilities. Here, we performed comprehensive RNA (both coding and non-coding) profiling in various samples from 17 patients diagnosed with esophageal adenocarcinoma, high-grade dysplastic or non-dysplastic Barrett’s esophagus. Per patient, a blood plasma sample, and a healthy esophageal and disease tissue sample were included. In total, this comprehensive dataset consists of 102 RNA-seq libraries from 51 samples. The raw data for this study have been deposited to the controlled access archive EGA under submission EGAS00001004939.
2022-01-01 | E-MTAB-10004 | biostudies-arrayexpress