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 Raw data files have been archived at the European Genome-Phenome Archive (EGA, www.ebi.ac.uk/ega) by the consortium, with restricted access to protect sample donors' identity.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
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 Raw data files have been archived at the European Genome-Phenome Archive (EGA, www.ebi.ac.uk/ega) by the consortium, with restricted access to protect sample donors' identity.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
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\
Project description:In this study, we investigated somatic mutations in T cells in patients with various hematological disorders. To analyze immune cell phenotypes with somatic mutations, we performed scRNA+TCRab sequencing from 9 patients with chronic GVHD and clonal expansions of CD4+ or CD8+ T cells based on T cell receptor sequencing. CD45+ PBMCs (lymphocytes and monocytes) were sorted with BD Influx cell sorter and subjected to sequencing with Chromium VDJ and Gene Expression platform (v1.1, 10X Genomics). Sequencing was performed with Novaseq 6000 (Illumina). The immune cell phenotypes were compared to healthy controls processed in the same laboratory (accession number E-MTAB-11170). Due to data privacy concerns, the raw sequencing data is in the European Genome-Phenome Archive (EGA) under accession code [xxxx] and can be requested through the EGA Data Access Committee.
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).
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).
Project description:Myelodysplastic syndromes and chronic myelomonocytic leukemia (CMML) are characterized by mutations in epigenetic modifiers and aberrant DNA methylation. DNA methyltransferase inhibitors (DMTis) are used to treat these disorders, but response is highly variable with few means to predict which patients will benefit. To develop a molecular means of predicting response at diagnosis, we examined baseline differences in mutations, DNA methylation, and gene expression in 40 CMML patients responsive and resistant to decitabine (DAC). While somatic mutations did not differentiate responders and non-responders, we were able to identify for the first time 158 differentially methylated regions (DMRs) at baseline between responders and non-responders using next-generation sequencing. These DMRs were primarily localized to non-promoter regions and overlapped with distal regulatory enhancers. Using the methylation profiles, we developed an epigenetic classifier that accurately predicted DAC response at the time of diagnosis. We also found 53 differentially expressed genes between responders and non-responders. Genes up-regulated in responders were enriched in the cell cycle, potentially contributing to effective DAC incorporation. Two chemokines overexpressed in non-responders -- CXCL4 and CXCL7 -- were able to block the effect of DAC on normal CD34+ and primary CMML cells in vitro, suggesting their up-regulation contributes to primary DAC resistance. DNA methylation profiling in bone marrow mononuclear cells (BM MNC) from 39 CMML patients (19 decitabine responders vs. 20 non-responders).