11768 results for "cancer rna-seq"

in 25.32 milliseconds.

• BLUEPRINT release August 2015, ChIP-Seq for effector memory CD8-positive, alpha-beta T cell, terminally differentiated, on genome GRCh38

  ChIP-Seq data for 1 effector memory CD8-positive, alpha-beta T cell, terminally differentiated sample(s). 4 run(s), 4 experiment(s), 4 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001577

• BLUEPRINT release August 2015, ChIP-Seq for CD34-negative, CD41-positive, CD42-positive megakaryocyte cell, on genome GRCh38

  ChIP-Seq data for 1 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 7 run(s), 6 experiment(s), 6 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001557

• BLUEPRINT release August 2016, ChIP-Seq for mature neutrophil - G-CSF/Dex. Treatment (16-20 hrs), on genome GRCh38

  ChIP-Seq data for 3 mature neutrophil - G-CSF/Dex. Treatment (16-20 hrs) sample(s). 23 run(s), 23 experiment(s), 23 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002470

• BLUEPRINT release August 2015, ChIP-Seq for CD8-positive, alpha-beta T cell, on genome GRCh38

  ChIP-Seq data for 5 CD8-positive, alpha-beta T cell sample(s). 26 run(s), 26 experiment(s), 26 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001513

• BLUEPRINT release August 2015, ChIP-Seq for mesenchymal stem cell of the bone marrow, on genome GRCh38

  ChIP-Seq data for 1 mesenchymal stem cell of the bone marrow sample(s). 9 run(s), 7 experiment(s), 7 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001578

• BLUEPRINT release August 2015, ChIP-Seq for CD3-negative, CD4-positive, CD8-positive, double positive thymocyte, on genome GRCh38

  ChIP-Seq data for 1 CD3-negative, CD4-positive, CD8-positive, double positive thymocyte sample(s). 2 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001570

• BLUEPRINT release August 2015, ChIP-Seq for effector memory CD8-positive, alpha-beta T cell, on genome GRCh38

  ChIP-Seq data for 2 effector memory CD8-positive, alpha-beta T cell sample(s). 10 run(s), 10 experiment(s), 10 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001472

• BLUEPRINT release August 2015, ChIP-Seq for cytotoxic CD56-dim natural killer cell, on genome GRCh38

  ChIP-Seq data for 4 cytotoxic CD56-dim natural killer cell sample(s). 17 run(s), 17 experiment(s), 17 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001518

• BLUEPRINT release August 2015, ChIP-Seq for CD14-positive, CD16-negative classical monocyte, on genome GRCh38

  ChIP-Seq data for 9 CD14-positive, CD16-negative classical monocyte sample(s). 56 run(s), 53 experiment(s), 53 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001552

• BLUEPRINT release August 2016, ChIP-Seq for CD4-positive, alpha-beta T cell, on genome GRCh38

  ChIP-Seq data for 9 CD4-positive, alpha-beta T cell sample(s). 68 run(s), 63 experiment(s), 63 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002444

• BLUEPRINT release August 2016, ChIP-Seq for CD8-positive, alpha-beta T cell, on genome GRCh38

  ChIP-Seq data for 7 CD8-positive, alpha-beta T cell sample(s). 38 run(s), 38 experiment(s), 38 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002455

• Basal-to-Inflammatory Transition Contributes to Basal Cell Carcinoma Therapy Resistance via Crosstalk with a Pro-Inflammatory Stromal Niche

  Overcoming tumor evolution and inducible resistance states remain the main challenge to creating successful anti-tumor therapies. The body's cancer-associated inflammatory response is a double-edged sword having ill-defined pro- and anti-tumor properties. Our group previously identified a basal cell carcinoma (BCC) tumor-intrinsic resistance pathway called basal to squamous cell carcinoma transition (BST). However, tumor resistance driven through the complex dynamics of tumor interactions with the inflammatory response remains poorly studied. Here, employing a multipronged approach combining human tumor single-cell transcriptomics, single-cell chromatin accessibility (scATAC-Seq) study, CODEX multiplexed imaging, spatial transcriptomic along with functional validation, we have identified a surprising inflammation-associated SMOi therapy enriched tumor epithelial cell state we term basal-to-inflammatory transition (BIT). Marked by CHI3L1, TAGLN, ITGAV, and VCAM1, BIT arises in spatially distinct neighborhoods from BST in a subset of naive BCCs. While BST tumor epithelium occurs within the central cores of tumor nodules, BIT tumor epithelium arises in a specialized inflammatory environment defined by a tumor associated TREM1 myeloid signature. IL1 and OSM secreted by TREM1 myeloid cells activate the inflammatory NF-kB family of transcription factors within the BIT tumor epithelium. Strikingly, IL1 and OSM ligands are sufficient not only in inducing the BIT tumor state in vitro and in vivo in a synergistic fashion but also in lowering the sensitivity of human BCC explant tumors to SMOi treatment. This work provides critical insights into the BIT-resistant state as a novel targetable tumor state driven by a specialized inflammatory microenvironment.

  Study phs003437

• HiChIP fastq files

  HiChIP experiments with two sequencing libraries each. Illumina HiSeq 4000/2500.

  Dataset EGAD00001006278

• FusionSeq: a modular framework for finding gene fusions by analyzing Paired-End RNA-Sequencing data

  We have developed FusionSeq to identify fusion transcripts from paired-end RNA-sequencing. FusionSeq includes filters to remove spurious candidate fusions with artifacts such as misalignments or random pairing of transcript fragments and it ranks candidates according to several statistics. It also has a module to identify exact sequences at breakpoint junctions. FusionSeq detected known and novel fusions in a specially sequenced calibration data set, including 8 cancers with and without known rearrangements.

  Study phs000311

• Total RNA expression in benign ovarian and malignant ovarian tumours

  This study investigates the total RNA expression profiles of fresh-frozen ovarian tumors, providing a comprehensive analysis of 112 samples from 111 women in Sweden, two samples being replicates. The dataset includes 18 benign and 94 malignant tumours, collected as part of the U-CAN initiative from Uppsala Biobank. The sequencing data offers valuable insights into ovarian tumour biology and can be used to enhance understanding of tumour classification and molecular characteristics.

  Study EGAS50000001045

• Bulk RNAseq from in vitro generated macrophages and T cells, and mUM tumour biopsies

  Monocyte derived macrophages were polarised into M1 or M2 using IFNg+ ILP or IL-4 respectively (n =4) . Pan T cells were cultured with or without IL-2 for 4 days (n=4 - 6). Pan T cells were co-cultured with THP1 tumour cells for 20 hours in the presence or absence of ImmTAC molecules and in the presence or absence of M2 macrophages. Sorted T cells and macrophage populations prior and post co-culture were analysed by bulk RNA sequencing (60 million reads per sample) using the Illumina NovaSeq system. Tumour biopsies were obtained from uveal melanoma patients (n = 35) pre and 16 days post treatment with tebentafusp. Biopsies, which were either snap frozen or put in RNA later, were analysed by bulk RNA sequencing (50 million reads per sample) using the Illumina NovaSeq system

  Dac EGAC50000000518

• Single nuclei RNA sequencing on Primary and Maladaptive FSGS patient samples

  We used single-nucleus RNA-sequencing to identify differentially expressed transcriptional signatures in kidney biopsies of well-phenotyped primary vs. maladaptive FSGS patients. We included cryopreserved kidney biopsy cores from adult patients with newly diagnosed primary FSGS (n = 9, all nephrotic), maladaptive FSGS (n = 9, not nephrotic), proteinuric controls (PLA2R-positive membranous nephropathy, n = 3), and healthy controls (n = 4). We identified 120,751 high-quality nuclei, including 2,471 podocytes and 1,574 parietal epithelial cells (PECs).

  Study EGAS50000001070

• Single-cell RNA sequence analysis of iPS cell-derived cardiomyocytes treated with S-RBD-sfGFP or GFP

  To determine the transcriptional response in human cardiomyocytes treated with SARS-CoV-2 spike receptor-binding domain (S-RBD-sfGFP), human cardiomyocytes differentiated from induced pluripotent stem cells (iPSC-CMs) were replated on day 21 after differentiation and treated with S-RBD-sfGFP or control-GFP for 48 hours on day 26-28. iPSC-CMs were dissociated and the single cell suspension was analyzed by single cell RNA-sequence.

  Study JGAS000620

• single-cell RNA-sequencing of human/mouse colonic crypts

  Human colonic stem cells are slow cycling compared with murine rapid cycling stem cells. Our study aims to identify slow cycling stem cell in human normal colon in vivo and to analyze gene signatures among rapid cycling stem cells, slow cycling stem cells and secretory progenitor cells using single cell RNA-seqencing . We further investigated in vivo dynamics of human colonic stem cell using patient-derived gene-enginered organoids and orthotopic xenotransplantation.

  Study JGAS000550

• RNA sequencing in primary human macrophages overexpressing ETS2

  We investigated an intergenic haplotype on chr21q22, linked to five different inflammatory diseases, and discovered a mechanism that orchestrates macrophage responses during chronic inflammation. We delineated how the risk haplotype increases expression of the causal gene, ETS2, and demonstrated that ETS2 is necessary for inflammatory macrophage effector functions. To establish whether ETS2 is sufficient to drive inflammatory responses, we overexpressed ETS2 in a dose-dependent manner and performed RNA-sequencing to characterise the transcriptional effects.

  Study EGAS00001007554

• An IL-1β driven neutrophil-stromal cell axis fosters a BAFF-rich microenvironment in multiple myeloma

  This depository contains data from two bulk RNA sequencing experiments: 1) Bulk RNA sequencing data of peripheral blood neutrophils from healthy donors cultured with a) human adipose-derived stromal cells (ADSC) as a model for mesenchymal stromal cells (MSC), and b) IL-1β stimulated ADSC as a model for inflammatory MSC as found in multiple myeloma (MM). 2) Bulk RNA sequencing data from ADSCs cultured a) without stimuli, b) with recombinant human IL-1β, c) with supernatant from iMSC-like cells, d) with neutrophils previously cultured with MSC, e) with neutrophils previously cultured with iMSC, f) with neutrophils previously cultured with iMSC in the presence of anti-human IL-1β or g) with neutrophils previously cultured with iMSC in the presence of an isotype control.

  Dataset EGAD00001010080

• RNAseq data of polyA+ RNA from Leukocytes from 624 individuals of the ProgeNIA cohort.

  We sequenced the polyA+ fraction of the RNA of the leukocytes from 624 sardinian individuals with RNAseq. Prior to library preparation we added either ERCC ExFold RNA Spike-In. An average of 60M reads per samples with 51 bp paired-end reads were generated on a HiSeq 2000 (Illumina). Sequencing reads were then aligned using STAR-2.2.0c2 to the h37d5 reference genome supplemented with the ERCC spike-ins sequences. We further provided an exon-exon junction database that we generated from the GENCODE v14 annotation. In order to remove a contamination from a parallel experiment, we discarded any reads that mapped to the genomic regions of CBLB (chr3:105370773-105592330) and BCL11A (chr2:60672555-60784156). Filtered aligned reads (bam format) are shared.

  Dataset EGAD00001003102

• RNA sequencing data of in vitro differentiated megakaryocyte cells transduced with E527K and WT SRC

  RNA sequencing data of in vitro differentiated megakaryocyte cells transduced with E527K and WT SRC. CD34+ hematopoietic stem cells (HSC) were isolated from healthy controls before transduction with WT-SRC and E527K-SRC lentiviral vectors in triplicate and differentiation to MK. Three replicates each of two pools were generated for both WT and E527K SRC transduced cells, resulting in 3 WT pool 1 samples, 3 WT pool 2 samples, 3 E527K pool 1 samples and 3 E527K pool 2 samples for a total of 12 samples. RNA was extracted and sequenced with following parameters: Platform: Illumina HiSeq4000, Library Prep Kit: TruSeq stranded mRNA, Sequencing Kit: Illumina HiSeq4000 100 cycles (76-8-8-7), Fragments: single end / fr-firststrand.

  Dataset EGAD00001008356

• Whole genome, exome and RNA sequencing of TFCP2-rearranged rhabdomyosarcoma

  Whole genome, exome and RNA sequencing of TFCP2-rearranged rhabdomyosarcoma, 86 samples of paired fastq files, sequenced on: Illumina HiSeq 2500 using Agilent SureSelect WGS, Illumina HiSeq 2500 using Illumina TruSeq RNA, Illumina HiSeq 2500 using Agilent SureSelect v5 WES (+UTRs), Illumina HiSeq 4000 using Agilent SureSelect WGS, Illumina HiSeq 4000 using Illumina TruSeq stranded mRNA Kit, Illumina HiSeq 4000 using Agilent SureSelect v5 WES stranded mRNA Kit, Illumina NovaSeq 6000 using Illumina TruSeq Stranded mRNA, Illumina NovaSeq 6000 using Illumina TruSeq Nano DNA, Illumina HiSeq X Ten using TruSeq Nano DNA.

  Dataset EGAD00001010108

• RNA-sequencing of a representative cohort of 209 AML cases

  Sample libraries were prepped using 500 ng of input RNA according to the KAPA RNA HyperPrep Kit with RiboErase (HMR) (Roche) using Unique Dual Index adapters (Integrated DNA Technologies, Inc.). Amplified sample libraries were paired-end sequenced (2x100 bp) on the Novaseq 6000 platform (Illumina) and aligned against the human genome (hg19) using STAR v2.5.4b2.

  Dataset EGAD00001007581

• Total RNA sequencing of 32 chronic lymphocytic leukemia (CLL) patients

  Peripheral blood mononuclear cells (PBMC) of CLL patients were isolated by density-gradient centrifugation over Linfosep (Biomedics, Madrid, Spain). B cells were purified with a CD19+ magnetic-bead system (MidiMACS, Miltenyi Biotec, Bergish Gladbash, Germany) according to the manufacturers’ instructions. Mean B-cell purity was >99% and the mean percentage of CD5+/CD19+ cells after purification was >98%, as measured by flow cytometry. Total RNA was extracted from purified cells in a single step using TriPure Isolation Reagent (Roche Applied Science, Vilvoorde, Belgium).Whole transcriptome sequencing libraries were prepared using the TruSeq Stranded Total RNA Sample Preparation Kit (Illumina). Libraries underwent 2 × 76 bp paired-end sequencing on a HiSeq 2500 instrument (Illumina). The median number of paired-end reads was 60.5 million (range, 49.7-79.7 million).

  Dataset EGAD00001004047

• RNA Sequencing of Surgically Resected Colorectal Liver Metastases

  Dac EGAC00001000904

• RNA sequencing of sorted human RCC immune populations

  Dac EGAC00001002861

• CNA differences between RNA-based subtypes of PDAC

  Dac EGAC50000000730

• SiMSen‑Seq

  High resolution amplicon-bases sequencing o screen for PIK3CA hot spot mutations

  Dataset EGAD50000001668

• Dataset for WGS and RNA samples of acute myeloid leukemia with MNX1 expression

  This dataset contains 10 samples of WGS, ATAC, 4C and RNAseq samples of patients with acute myeloid leukemia. The sequencing was performed on Illumina HiSeq 4000, 2000 and HiSeq X using Illumina TruSeq Nano DNA and Agilent Strand Specific RNA Kits. The sequencing was always paired.

  Dataset EGAD50000001098

• Single-cell RNA-sequencing of CSF cells and PBMCs from individuals with neurological disorders

  We undertook single-cell RNA sequencing to establish gene expression and lymphocyte receptor sequences of CSF and peripheral blood leukocytes derived from patients with a variety of inflammatory, infectious and non-inflammatory neurological disorders. The aim of the study was the investigation of functional changes of the cells involved in neuroinflammatory responses.

  Dataset EGAD50000001173

• Single-cell transcriptome sequencing

  Raw reads from single-cell RNA-sequencing of peripheral blood of five TET2 mutation carriers as well as three non-carrier family members. Single-cells were captured into 10x barcoded gel beads and RNA-sequencing library preparation was done using Chromium Single Cell 3' v2 chemistry (10x Genomics, Pleasanton, CA, USA). Sequencing was performed as recommended with 98bp length of read 2 using HiSeq4000 sequencer.

  Dataset EGAD00001004778

• Transcriptome profiling of human lung fibroblasts in COPD

  Primary lung fibroblast were isolated from well-matched control donors (no COPD, n=3) and patients with COPD (GOLD stage I-IV, n=8). Total RNA of cultured human lung fibroblast were isolated at passage 3 and rRNA was depleted. 75 bp single-end reads were generated from RNA libraries on Illumina NextSeq 500.

  Dataset EGAD00001009405

• Single-cell RNA sequencing generated from 11 glioma patient samples

  This dataset includes paired-end fastq files from 6 IDH-mutant, 5 IDH-wild-type glioma patient samples of unmatched initial and recurrent timepoints profiled using single-cell RNA sequencing.

  Dataset EGAD00001007772

• Transcript read counts derived from RNA sequencing data collected for NABUCCO cohort 1 (NCT03387761)

  Data from NABUCCO cohort 1 (NCT03387761). This dataset includes the Transcript read counts derived from the RNA sequencing data. The samples are pre-treatment (n=18) and post-treatment (n=18), and not all samples are paired. The data processing pipeline can be found on the Methods section from the Nature Medicine paper (https://doi.org/10.1038/s41591-020-1085-z)

  Dataset EGAD00001006854

• FASTQ files of the cell-free RNA from the maternal blood

  cell-free RNA from the maternal plasma obtained at round the 12, 20, 28 and 36 week gestational age from the cases of preeclampsia combined with fetal growth restriction (n=39) and their matched controls (n=156). All samples are from the Pregnancy Outcome Prediction (POP) study.

  Dataset EGAD00001015416

• RNA expression profiling of melanoma patient-derived xenograft

  Patient-derived xenografts (n=96) were derived from metastatic melanoma patients. RNA expression profiling will be preformed to study 1. HLA-typing and 2. the effect of the tumour microenvironment on tumour growth This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001002230

• A Pilot Study of Rapid Autopsy and Procurement of Tissue in Thoracic Malignancy Cancer Patients to Investigate Tumor Heterogeneity

  Integrated proteo-genomics studies to characterize tumor heterogeneity of metastatic lung adenocarcinoma and thymic carcinoma are lacking. We carried out whole exome sequencing, RNA sequencing, copy number estimation and mass spectrometry-based proteomics of 40 tumors from five rapid/warm autopsy patients. We found highly variable mutational heterogeneity that was largely driven by APOBEC-mutagenesis with the expression of APOBEC3B (Gene ID: 9582) and APOBEC3A_B (Gene ID: 100913187) due to underlying APOBEC3 region germline variants as the likely mediating mechanism. APOBEC3A_B expression was associated with increased immune tumor microenvironment and CD274 (Gene ID: 29126) expression while smoking was associated with increased APOBEC-mutagenesis in TP53 (Gene ID: 7157) mutant tumors with high APOBEC3B expression. Heterogeneity at the level of the transcriptome and proteome occurred in association with copy number heterogeneity, not APOBEC-induced mutational heterogeneity. Arm and focal copy number alterations (CNAs) occurred as an evolutionarily late event in a subset of patients, with corresponding changes in the transcriptome and proteome, implicating CNAs as a driving force of heterogeneity in the evolution of metastatic disease.

  Study phs001432

• Immunogenomics of colorectal cancer response to immune checkpoint blockade

  Molecular and cellular determinants of response to immune checkpoint inhibitors are mostly unknown. Here we use whole exome, RNA and T cell receptor sequencing, imaging mass cytometry, immunohistochemistry and PD1-PDL1 interaction detection to profile 543 regions from 16 colorectal cancers (CRCs) subsequently treated with Pembrolizumab or Nivolumab. Independent of treatment response, CRCs express low levels of PD1 and PDL1 proteins and form less PD1-PDL1 complex than other cancers. Non hypermutated CRCs have no benefit from treatment, show WNT activation and low T cell infiltrates. Among hypermutated CRCs, those with durable benefit have clonal immunogenic alterations, clonally expanded T cells and potential for immune escape through dysfunctional antigen presentation. Responsive tumours are enriched in PD1-expressing cytotoxic and proliferating CD8 T cells and PDL1-expressing antigen presenting macrophages, which form high-density clusters of interacting cells. Our study shows that immune checkpoint inhibitors are most effective in highly infiltrated CRCs where they may release the interactions between macrophages and CD8 T cells thus promoting their priming and expansion in intra-tumour niches.

  Study EGAS00001004438

• Human Biofluid RNA Atlas Project - raw data

  Study EGAS00001003917

• Single Cell Analysis Program - Transcriptome (SCAP-T)

  This initiative is part of the Single Cell Analysis Program (SCAP) and is funded through the NIH Common Fund (See http://nihroadmap.nih.gov/), which supports cross-cutting programs that are expected to have exceptionally high impact. Common Fund initiatives address key roadblocks in biomedical research that impede basic scientific discovery and its translation into improved human health. In addition, these programs capitalize on emerging opportunities to catalyze progress across multiple biomedical fields. Single cell analysis has recently emerged as an important field of research because technologies have improved in sensitivity and throughput sufficiently to begin measuring and understanding heterogeneity in complex biological systems and correlating it with changes in biological function and disease processes. By profiling individual cells it is possible to resolve rare cells, transient cell states, and the influence of organization and environment on such cells and states, which cannot be described by ensemble measurements. The long-term goal of the SCAP is to accelerate this move towards personalizing health to the cellular level by understanding the link between cell heterogeneity, tissue function and emergence of disease through the discovery, development and translation of innovative approaches which will dramatically change the way cells are characterized. The SCAP will focus on research, which will systematically measure, analyze and model cell-to-cell variation, and identify crucial differences and rare biological states, which may have important functional consequences. Under SCAP, there are three studies to evaluate the cellular heterogeneity using transcriptional profiling of single cells (U01): University of Pennsylvania: Role of single cell mRNA variation in systems associated electrically excitable cells University of Southern California: Evaluation of cellular heterogeneity using patchclamp and RNA-seq of single cells University of California at San Diego: Single cell sequencing and in situ mapping of RNA transcripts in human brains The SCAP has been designed as a five-year program with several components: (1) the collection, analysis and sharing of comprehensive expression datasets to understand the role of heterogeneity in tissues and systemically and identify critical parameters and states; (2) the discovery of new, innovative tools for spatiotemporal imaging, manipulation, analysis and modeling of a biologically relevant population of cells with minimal perturbation; (3) milestone-driven validation and translation of technologies for characterizing single cells in situ meeting the needs of end-users; and (4) development and coordination of a multidisciplinary research community through workshops and other collective endeavors. Further details about the NIH SCAP-T program can be found here http://commonfund.nih.gov/singlecell/. The SCAP-T data sets include the detailed phenotype information, experimental protocols, QC information, RNA-sequencing data and NGS results from human heart and human brain cells. The first data release includes 697 single cells from human brain and heart. The second data release includes an additional 978 single cells from human brain and heart. The third data release includes an additional 1631 single cells from human brain and heart. The fourth data release is a correction to this study, but adds no new cells. The fifth data release includes an additional 2984 single cells from human brain and heart. The sixth data release includes an additional 944 single cells from human brain and heart. The seventh data release includes an additional 1977 single cells from human brain and heart. The SCAP-T data portal provides a customized interface for users to quickly identify and retrieve files by phenotypes, and data properties such as sequencing facility or coverage for all of these 9231 single cells. For more information about the SCAP-T study and the data portal, please visit http://www.scap-t.org.

  Study phs000833

• Bulk-tissue RNA-sequencing of anterior cingulate cortex samples derived from Lewy body disease patients

  Parkinson’s disease (PD), Parkinson’s disease with dementia (PDD) and dementia with Lewy bodies (DLB) are three clinically, genetically and neuropathologically overlapping neurodegenerative diseases collectively known as the Lewy body diseases (LBDs). A variety of molecular mechanisms have been implicated in PD pathogenesis, but the mechanisms underlying PDD and DLB remain largely unknown, a knowledge gap that presents an impediment to the discovery of disease-modifying therapies. Transcriptomic profiling can contribute to addressing this gap, but remains limited in the LBDs. Here, we applied paired bulk-tissue and single-nucleus RNA-sequencing to anterior cingulate cortex samples derived from 28 individuals, including healthy controls, PD, PDD and DLB cases (n = 7 per group), to transcriptomically profile the LBDs. Using this approach, we (i) found transcriptional alterations in multiple cell types across the LBDs; (ii) discovered evidence for widespread dysregulation of RNA splicing, particularly in PDD and DLB; (iii) identified potential splicing factors, with links to other dementia-related neurodegenerative diseases, coordinating this dysregulation; and (iv) identified transcriptomic commonalities and distinctions between the LBDs that inform understanding of the relationships between these three clinical disorders. Together, these findings have important implications for the design of RNA-targeted therapies for these diseases and highlight a potential molecular “window” of therapeutic opportunity between the initial onset of PD and subsequent development of Lewy body dementia.

  Study EGAS00001005305

• Bulk-tissue RNA-sequencing paired nuclear and cytoplasmic fractions of anterior prefrontal cortex, cerebellar cortex and putamen tissues from post-mortem neuropathologically-confirmed control individuals.

  Gaining insight into the genetic regulation of gene expression in human brain is key to the interpretation of genome-wide association studies for major neurological and neuropsychiatric diseases. Expression quantitative trait loci (eQTL) analyses have largely been used to achieve this, providing valuable insights into the genetic regulation of steady-state RNA in human brain, but not distinguishing between molecular processes regulating transcription and stability. RNA quantification within cellular fractions can disentangle these processes in cell types and tissues which are challenging to model in vitro. We investigated the underlying molecular processes driving the genetic regulation of gene expression specific to a cellular fraction using allele-specific expression (ASE). Applying ASE analysis to genomic and transcriptomic data from paired nuclear and cytoplasmic fractions of anterior prefrontal cortex, cerebellar cortex and putamen tissues from 4 post-mortem neuropathologically-confirmed control human brains, we demonstrate that a significant proportion of genetic regulation of gene expression occurs post-transcriptionally in the cytoplasm, with genes undergoing this form of regulation more likely to be synaptic. These findings have implications for understanding the structure of gene expression regulation in human brain, and importantly the interpretation of rapidly growing single-nucleus brain RNA-sequencing and eQTL datasets, where cytoplasm-specific regulatory events could be missed.

  Study EGAS00001006380

• scRNA-seq of HSPC treated with gemcitabine and carbplatin

  The study used cryopreserved hematopoietic stem and progenitor cells (HSPCs) harvested from one patient with chronic myelogenous leukemia (CML). The cells were thawed and acclimatized for 48 hours in StemMACS HSC Expansion Media XF (Miltenyi Biotec) supplemented with StemMACS HSC Expansion Cocktail (Miltenyi Biotec) at 37°C in a humidified atmosphere containing 5% CO2. 4 samples of 2000000 HSPCs in 2 ml media each were then prepared and treated for 24 hours: carboplatin-high: 150 µg/ml carboplatin carboplatin-low: 18.75 µg/ml carboplatin gemcitabine: 25 ng/ml gemcitabine control: no drug Single-cells were subsequently extracted using the ddSEQ™ Single-Cell Isolator (Bio-Rad) and later sequenced using the SureCell™ Whole Transcriptome Analysis 3' Library Prep Kit (Illumina) on the NextSeq 500 System (Illumina) using the NextSeq 500/550 High Output Kit v2.5 150 Cycles (Illumina) all following the manufacturer's instructions. FASTQ-files were then processed following the ddSeeker (Romagnoli, D., et al., BMC Genomics 2018, doi:10.1186/s12864-018-5249-x) and Drop-seq (Macosko, E.Z., et al., Cell 2015, doi:10.1016/j.cell.2015.05.002) protocols for processing scRNA-seq data to yield the final digital gene expression for each cell.

  Study EGAS00001004381

• Palindromic Amplification of The ERBB2 Oncogene in HER2-Positive Breast Cancer

  DNA Inverted Repeats as an At-risk Motif for Palindromic Gene Amplificatio defines oncogene amplification that is configured as a series of inverted duplications (palindromic gene amplification). There are several, recurrently amplified oncogenes throughout the human genome. However, it remains unclear whether this recurrent amplification is solely a manifestation of increased fitness resulting from random amplification mechanisms, or if genomic locus-specific amplification mechanism plays a role. In this study, we show that the ERBB2 oncogene at 17q12 is susceptible to palindromic gene amplification in HER2-positive breast tumors. We investigated eight tumors in this study, of which five tumors were HER2-positive, and three tumors were HER2-negative. HER2-status was determined by clinical FISH tests. We applied three genomic approaches to investigate the amplification mechanism: (1) copy number analysis by array-CGH on the Affymetrix SNP6.0 platform (8 files), (2) sequencing of DNA libraries enriched with tumor-derived palindromic DNA (Genome-wide Analysis of Palindrome Formation, GAPF-seq) (8 files) and (3) unbiased whole genome sequencing (WGS) (1 file). These molecular data is made available in the dbGaP. Genomic studies using tumor DNA was approved under the Internal Institutional Review Board at the Cleveland Clinic (IRB07-136: EXEMPT: Chromosome Breakage and DNA Palindrome Formation). Specimens were obtained and methods were carried out under the auspices of IRB 7881 (Evaluation of Genetic and Molecular Markers in Patients with Breast Cancer). All patients consented to allow their cancer specimens to be used by researchers in an anonymized fashion. The consent form indicates that publication will take place without identifiers to protect the identity of any specific individual. We observed significant and enrichment of palindromic DNA within amplified ERBB2 genomic segments in four out of five HER2-positive tumors. None of three HER2-negative tumors showed such enrichment. Palindromic DNA was particularly enriched at amplification peaks and boundaries between amplified and normal copy-number regions. Thus, palindromic gene amplification shaped the amplified ERBB2 locus. The moderate enrichment of palindromic DNA throughout the amplified segments leads us to propose that the ERBB2 locus is amplified through a mechanism that repeatedly generates palindromic DNA, such as Breakage-Fusion-Bridge cycles. Our results reveal a potential interaction between local genomic environments and gene amplification mechanisms. This study is published under the title "Palindromic amplification of the ERBB2 oncogene in primary HER2-positive breast tumors" (PMID:28211519).

  Study phs001261

• Complete sequencing dataset of study EGAS00001002795

  Dataset EGAD00001004572

• DAC IBMsnRNAseq

  This DAC manages the data access to our snRNA-seq and spatial transcriptomic data set on healthy and inflamed human skeletal muscle.

  Dac EGAC50000000220

• DLBCL cfDNA seq

  Sequencing dataset of 290 DLBCL and HGBL cfDNA samples of paired end 150bp sequencing runs.

  Dataset EGAD50000000602

• NABEC Exome-Seq

  Exome sequencing of North American Brain Expression Consortium (NABEC) subject.

  Dataset EGAD00001002886