10156 results for "cancer rna-seq"

in 25.64 milliseconds.

• The life-saving benefit of dexamethasone in severe COVID-19 is linked to a reversal of monocyte dysregulation

  Assessment of dexamethasone response in human lung through scRNA-seq analysis of bronchoalveolar lavage (BAL) samples from patients with severe COVID-19.

  Study EGAS50000000203

• CITE-seq data of six CK-AML patient samples

  We performed cellular indexing of transcriptomes and epitopes (CITE-seq) of six primary leukemia samples from CK-AML patients. The dataset contains BAM files for each individual sample (D1922 and R0836) or for the hashed pool (HIAML47-HIAML85, P9D-P9R)

  Dataset EGAD50000000633

• PhIP-seq of Japanese subjects with SLE

  Bacteriophage Immunoprecipitation Sequencing (PhIP-Seq) datasets of three eHHV-6B-positive SLE patients (three technical replicates), six eHHV-6B-negative SLE patients (three technical replicates), and a negative control lacking sera or plasma (12 technical replicates; Illumina NextSeq) and sequencing data of HHV-6 peptide phage library (two technical replicates; Illumina NextSeq).

  Dataset EGAD00001015429

• Multi-omics characterization of KMT2A-rearranged infant acute lymphoblastic leukemia

  KMT2A gene rearranged (KMT2A-r) infant acute lymphoblastic leukemia (ALL) is the most refractory subgroup of childhood leukemia, whose molecular heterogeneity remains largely unknown. To better understand the molecular pathogenesis of KMT2A-r infant ALL, we comprehensively analyzed the RNA sequencing, methylation array, whole exome sequencing, single-cell RNA sequencing data of diagnostic samples of KMT2A-r infant ALL. We also performed ChIP sequencing of infant ALL-derived cell lines.

  Study JGAS000385

• DIGEST: Dietary Influences on Glucuronidation, a Cross-Sectional Study of Diet and Metabolism

  Plasma samples derived from a study population of control participants (DIGEST: Dietary Influences on Glucuronidation, a Cross-Sectional Study of Diet and Metabolism) were used to profile miRNA circulating in plasma. RNA was isolated from plasma samples using the Qiagen miRNeasy kit. Libraries were prepared using Illumina TruSeq Small RNA Library Prep Kit. Libraries were sequenced on a HiSeq. Data from this sequencing project will be available through dbGaP.

  Study phs003223

• GermCellTumour

  DNA and RNA sequencing across a number of different germ cell tumours, included mixed components within the same tumour.

  Study EGAS00001003457

• Multi-omics profiling of PSCCE

  We performed whole-exome sequencing, RNA sequencing and immunohistochemistry profiling of primary small cell carcinomas of the esophagus.

  Study EGAS00001004889

• RNA sequencing of paediatric glioblastoma in the ICGC PedBrain project

  RNA sequencing of paediatric glioblastoma in the ICGC PedBrain project

  Dataset EGAD00001001944

• RNA sequencing data of child-mother pairs, maternal smoking.

  RNA sequencing data of whole blood samples from smoking and non-smoking mothers and their children at gestation/birth and follow-up years.

  Dataset EGAD00001002011

• RNA sequencing analysis of lymphoblastoid cell lines with wildtype or defective Epstein-Barr virus

  Lymphoblastoid cell lines established using either wildtype or BALF5-deficient Epstein-Barr virus were analyzed by RNA sequencing.

  Dataset EGAD00001004297

• Strand-specific RNA sequencing of 16 pairs of primary and relapsed IDH-wt glioblastomas

  This dataset contains strand-specific RNA sequencing data from 16 primary/relapsed sample pairs of IDH-wt glioblastomas

  Dataset EGAD00001004564

• RNA sequencing study for 8 pairs of primary NSCLCs and distant metastases

  RNA sequencing study for 8 pairs of primary NSCLCs and distant metastases. This dataset includes a total of 29 samples.

  Dataset EGAD00001005765

• RNA sequencing data of pretreatment tumor biopsies of patients treated in the OpACIN-neo trial

  The dataset includes RNA sequencing on pre-treatment tumor biopsies of lymph node metastases (n=65)

  Dataset EGAD00001006731

• Patient TSO500 RNA

  Original patient tumours from which PDX models were derived. TruSight Oncology RNA panel for 2 samples, sequenced over 4 lanes each, gave 8 pairs of fastq files

  Dataset EGAD00001009659

• Human serum small non-coding RNA sequencing

  Human small non-coding RNA sequencing of serum from sons of PCOS mothers (n=9) and sons of control mothers (n=9), see publication for details.

  Dataset EGAD00001010165

• PrevANZ RNAseq dataset

  Whole blood samples collected at baseline and week 12 in PAXgene Blood RNA tubes. RNA sequencing on the Illumina NovaSeq 6000 System generated 150 base pair length paired end reads.

  Dataset EGAD00001011069

• The Extracellular RNA Quality Control (exRNAQC) study (phase 1)

  mRNA capture sequencing and small RNA sequencing data (FASTQ files) of the exRNAQC study phase 1.

  Dataset EGAD00001007697

• Single-cell RNA and TCR sequencing of PBMC from patients with uveal melanoma

  Single-cell RNA and TCR sequencing of PBMC from patients with uveal melanoma.

  Dataset EGAD00001007913

• Single-cell RNA sequencing of CML patients

  This dataset contains 15 single-cell RNA sequencing samples from 6 CML patients before and after TKI-cessation. The raw data is available as fastq files.

  Dataset EGAD00001012842

• Sequencing data for oesophageal and related samples - Ganguli et al (RNA)

  Data supporting: "TBC" Ganguli et al (RNA for 394 samples)

  Dataset EGAD00001011190

• Genetic architecture of microRNA expression and its link to complex diseases in the Japanese population

  We mapped microRNA expression quantitative trait loci by quantifying microRNA expression using small RNA sequencing.

  Study JGAS000504

• Single-cell RNA-sequencing of nivolumab-treated glioblastoma

  Single-cell RNA-sequencing of 8 patients, from primary and relapse tumour (total of 16 samples). Patients were treated with nivolumab prior to relapse surgery.

  Dataset EGAD00001010843

• The PEMDAC phase 2 study of pembrolizumab and entinostat in patients with metastatic uveal melanoma

  Patients with metastatic uveal melanoma (UM) have an abysmal prognosis. Preclinical studies have suggested that epigenetic therapy could enhance immunogenicity of cancer cells. Here we test if epigenetic therapy would enhance PD-1 immunotherapy in patients with metastatic UM. We report the results of the PEMDAC phase 2 clinical trial (n=29; NCT02697630) where the HDAC inhibitor entinostat was combined with the PD-1 inhibitor pembrolizumab in patients with metastatic UM. The primary endpoint was objective response rate (ORR), and was met with an ORR of 14%. The clinical benefit rate at 18 weeks was 28%, median progression free survival was 2.1 months and the median overall survival was 13.4 months. Toxicities were manageable, and there were no treatment-related deaths. Extensive genomics studies were performed using DNA/RNA and single cell sequencing and flow cytometry. Objective responses and prolonged survival were seen in three patients with BAP1 wildtype tumors, and in one patient with an iris melanoma that exhibited a UV signature. Longer survival also correlated with low baseline ctDNA levels or LDH. In conclusion, HDAC inhibition and anti-PD1 immunotherapy results in durable responses in a subset of patients with metastatic UM. Further exploration of combined immunotherapy and epigenetic therapy in metastatic UM is warranted.

  Study EGAS00001005478

• Longitudinal evaluation of serum microRNAs as biomarkers for neuroblastoma burden and therapeutic p53 reactivation

  Accurate assessment of treatment response and residual disease is indispensable for the evaluation of cancer treatment efficacy. However, performing tissue biopsies for longitudinal follow-up poses a major challenge in the management of solid tumours like neuroblastoma. In the present study, we evaluated whether circulating miRNAs are suitable to monitor neuroblastoma tumour burden and whether treatment-induced changes of miRNA abundance in the tumour are detectable in serum. We performed small RNA sequencing on longitudinally collected serum samples from mice carrying orthotopic neuroblastoma xenografts that were exposed to treatment with idasanutlin or temsirolimus. We identified 57 serum miRNAs to be differentially expressed upon xenograft tumour manifestation, out of which 21 were also found specifically expressed in the serum of human high-risk neuroblastoma patients. The murine serum levels of these 57 miRNAs correlated with tumour tissue expression and tumour volume, suggesting potential utility for monitoring tumour burden. In addition, we describe serum miRNAs that dynamically respond to p53 activation following treatment of engrafted mice with idasanutlin. We identified idasanutlin-induced serum miRNA expression changes upon one day and 11 days of treatment. By limiting to miRNAs with a tumour-related induction, we put forward hsa-miR-34a-5p as a potential pharmacodynamic biomarker of p53 activation in serum.

  Study EGAS00001006678

• Stratifying and Targeting Pediatric Medulloblastoma through Genomics

  In this project, genomic analyses of pediatric medulloblastoma samples, obtained through the international medulloblastoma consortium, will be performed. RNA and miRNA expression profiles of 1000 samples, representing all four subgroups (Wnt, Shh, Group C, and D), will be studied to identify novel subtypes within each subgroup. The resulting subtype-specific expression profiles will support the development of reliable and robust biomarkers to more accurately and reliably classify medulloblastomas for treatment in clinical trials. For that purpose, two assays will be developed: an antibody-based immunohistochemical assay and an orthogonal nucleic acid-based hybridization assay. Additional genomic DNA analysis of the 300 high risk subgroup cases will support the discovery of subgroup specific somatic mutations in order to inform current clinical trials of targeted therapies, and to identify genes and pathways already targeted in other diseases. Such therapies could be rapidly transitioned to Phase II trials in medulloblastoma. Furthermore, the discovery of somatic mutations could be used for developing as well as validating specific biomarkers. The project team will also try to identify risk factors that predispose children to this type of cancer.

  Study EGAS00001000273

• Ewing and Ewing-like-sarcoma tumoroid biobank reveals distinct drug sensitivities: translocation makes the difference

  Ewing sarcoma (ES) and Ewing-like sarcomas (ELS) are highly aggressive tumors found in soft tissues and bone of mostly children and young adults. Despite being different in many aspects, including genetics, possible cell-of-origin, and pathology, patients with any of these entities all receive the same therapeutic regimen. Currently, there is a lack of preclinical cell models that can predict drug response of these entities in vitro. Here, we describe a pediatric ES and ELS tumor organoid (tumoroid) biobank containing tumoroids with different translocations, including EWSR1::FLI1, EWSR1::ERG, CIC::DUX4, and BCOR-rearrangements. Using histology, whole genome sequencing and RNA sequencing, we demonstrate that these tumoroids retain key properties of their matching patient tumors. In addition, we traced tumor subclones in the tumoroids across patient-matched longitudinal samples, which showed that cellular heterogeneity was maintained. We subsequently performed drug screening on the tumoroid models, which unveiled entity-specific drug sensitivity to various cytotoxic compounds and targeted compounds, including MCL-1 inhibitors for CIC::DUX4 sarcomas. Taken together, this newly established ES and ELS patient-derived tumoroid biobank generates a unique source of material for future basic cancer research and drug-screening.

  Study EGAS00001007941

• Strand-specific RNA Sequencing of initial and recurrent gliomas

  Four RNA-sequencing datasets from two patients with initial low-grade glioma and copy number alteration at IDH1 upon recurrence. Data is provided as bam files.

  Dataset EGAD00001003764

• RNA-sequencing (Illumina HiSeq 4000) of tumor-stage mycosis fungoides

  This dataset contains RNA-sequencing data of tumors from 8 patients with mycosis fungoides. The data was generated using the Illumina HiSeq 4000 platform.

  Dataset EGAD00001003983

• Expression profiling of pediatric brain tumors Embryonal Tumor with Multilayered Rosettes (ETMR)

  RNA was prepared using the IlluminaTruSeq RNA sample preparation kit for poly-adenylated mRNA with an average of 97.64 million reads per sample respectively

  Dataset EGAD00001004803

• Hospital for Sick Children Infant Glioma RNA Sequencing

  Whole transcriptome (n=4) and targetted RNA sequencing (n=15) .bam files of infantile glioma samples reported on at the Hospital for Sick Children

  Dataset EGAD00001005092

• RNA Sequencing of mCRC xenografts under cetuximab treatment.

  RNA sequencing on cetuximab treated, untreated and release samples of one metastatic colorectal xenograft. 3 cetuximab treated samples, 3 placebo and 3 release - paired fastq.

  Dataset EGAD00001005185

• RNA-Sequencing data of Human Acute Myleloid Leukemia Stem Cells

  RNA-Sequencing of 27 functionally validated LSC and blast fractions from 9 AML patients. Three healthy hematopoietic stem and progenitor cells from age-matched controls.

  Dataset EGAD00001006112

• Single nuclei RNA-sequencing of glioblastoma tumors

  Single nuclei RNA-sequencing of snap frozen glioblastoma tumor tissue with 10x Genomics 3' expression (v2 chemistry). Aligned to GRCh38 reference genome with intron using CellRanger.

  Dataset EGAD00001006802

• Single cell RNA-sequencing of glioblastoma stem cell lines

  Single cell RNA-sequencing of glioblastoma stem cell (GSC) lines with 10x Genomics 3' expression (v2 chemistry). Aligned to GRCh38 reference genome using CellRanger.

  Dataset EGAD00001006804

• The Extracellular RNA Quality Control (exRNAQC) study (phase 2)

  mRNA capture sequencing and small RNA sequencing data (FASTQ files) of the exRNAQC study phase 2 (interaction study)

  Dataset EGAD00001009724

• Multi-omics characterisation of immune cells in Long Covid

  We generated 10X Multiomics (paired RNA+ATAC) for Long Covid patients with up to 14 months follow-up.

  Study EGAS50000000142

• Single-cell RNA sequencing of 43 BALF samples from CAPA and COVID-19 patients

  Single-cell RNA sequencing of 43 bronchoalveolar lavage fluid (BALF) samples from 15 CAPA and 22 COVID-19 mechanically ventilated patients.

  Dataset EGAD00001011342

• Single-cell bam files and RNA sequencing of viral RNA stocks

  244 infected single-cell alveolar bam files, 48 empty well bam files, and 52 RNA sequencing of amplicons (4 SARS-CoV-2 variants with 12 batches and 4 viral variants pool samples). 244 alveolar single cells were captured over 12 experimental batches and experimental condition is written in metadata uploaded as "infected_cells_final_revision.csv". on github (https://github.com/twkim-0510/SARS-CoV-2_viral_competition). Each bam file name corresponds to the sample_name column of the metadata.

  Dataset EGAD00001009711

• Rheumatoid Arthritis Finger Stick RNA Sequence Data

  This is a longitudinal study of 355 blood samples collected weekly from 5 patients with Rheumatoid Arthritis with varying disease activity over the course of one to five years. Blood samples were self collected from finger sticks and mailed from home. RNA was extracted, purified and sequenced.

  Study phs003179

• RNA-seq study of longitudinal blood cell samples from children at risk of type 1 diabetes

  The appearance of type 1 diabetes (T1D)-associated autoantibodies is the first and only measurable parameter to predict progression toward T1D in genetically susceptible individuals. However, autoantibodies indicate an active autoimmune reaction, wherein the immune tolerance is already broken. Therefore, there is a clear and urgent need for new biomarkers that predict the onset of the autoimmune reaction preceding auto-antibody positivity or reflect progressive b-cell destruction. Here we report the mRNA sequencing–based analysis of 306 samples including fractionated samples of CD4+ and CD8+ T cells as well as CD4, CD8 cell fractions and unfractionated PBMC samples longitudinally collected from seven children who developed beta-cell autoimmunity (Case subjects) at a young age and matched control subjects.

  Study EGAS00001004071

• Identification of cardiovascular biomarkers through an integrative omics approach

  Recent GWAS studies have made extensive use of large eQTL data sets to functionally annotate index SNPs. With a large number of association signals located outside coding regions there has been an intense search among sequence variants affecting gene expression at the transcriptional level. However, little progress has been made in mapping regulatory variants that affect protein levels at the translational or post-translational level. It is now possible to undertake a protein QTL scan for focused sets of e.g. oxidized proteins by mass spectrometry. We have established a collaboration with a longitudinal, family-based study in France, the Stanislas cohort, which comprises circa 1000 nuclear families (4,295 individuals) and has follow up data for 10 years (three visits). We have undertaken a pilot study in a focus set of 257 subjects from 79 families with the aim to integrate GWAS, transcriptomic and DNA methylation data with proteomic data on a set of 100 proteins measured in PBMCs. We have already generated GWAS data using Illumina's core-exome chip as well as DNA methylation profiles with the 450K array. We propose to use RNA seq to generate transcriptomic data of the corresponding PBMCs. 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 EGAD00001002197

• RNA sequencing, ATACseq, and TCR-seq of Tfh cells and CXCR5- CD4+ T cells in HIV infected lymph nodes

  The high dimensional analyses of CD4+ T cells in human lymph nodes are case-based analyses of the TCR repertoire, transcriptome, and epigenetic signatures of various CD4+ T cells in human lymph nodes. The study aims to determine clonal overlap between phenotypically distinct CD4+ T cells and the similarities between these populations on transcriptional and epigenetic levels. This study performs TCR repertoire sequencing using Molecular Identifier Clustering-based Immune Repertoire Sequencing (MIDCIRS). We found clonal overlap between a population of CXCR5- T cells and follicular helper T (Tfh) cells. We also show epigenetic and transcriptional similarities between CXCR5-PD-1+ T cells and Tfh cells. This study shares an overlapping set of donors with phs001548.

  Study phs001849

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_T=6days from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_T=6days from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002914

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_LPS_T=4hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_LPS_T=4hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002922

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_T=24hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_T=24hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002921

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_LPS_T=1hr from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_LPS_T=1hr from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002913

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_T=1hr from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_T=1hr from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002919

• BLUEPRINT September 2016, ATAC-seq for germinal center B cell from tonsil, on Genome GRCh38

  ATAC-seq data for 2 sample(s) for germinal center B cell from tonsil, on Genome GRCh38. 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002917

• BLUEPRINT September 2016, ATAC-seq for germinal center B cell from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for germinal center B cell from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002911

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=4hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=4hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002910

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=24hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=24hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002909

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=1hr from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=1hr from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002906

• BLUEPRINT September 2016, ATAC-seq for unswitched memory B cell from venous blood, on Genome GRCh38

  ATAC-seq data for 3 sample(s) for unswitched memory B cell from venous blood, on Genome GRCh38. 3 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002905

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=24hrs_RPMI_T=5days from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=24hrs_RPMI_T=5days from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002904

• BLUEPRINT September 2016, ATAC-seq for naive B cell from venous blood, on Genome GRCh38

  ATAC-seq data for 3 sample(s) for naive B cell from venous blood, on Genome GRCh38. 3 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002902

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_LPS_T=24hrs_RPMI_T=5days from venous blood, on Genome GRCh38

  ATAC-seq data for 2 sample(s) for monocyte RPMI_LPS_T=24hrs_RPMI_T=5days from venous blood, on Genome GRCh38. 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002901

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_LPS_T=24hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_LPS_T=24hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002900

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_T=4hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_T=4hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002899

• smRNA-seq of human post-mortem brain data of frontal lobe (Tuebingen part)

  This dataset contains smRNA-seq data from post-mortem human brain tissue of the frontal lobe of patients with FTD and healthy controls. The smRNA-sequencing was done in two parts, this dataset depicts the data generated at the DZNE Tübingen.

  Dataset EGAD00001006846

• 4C-seq in endometrial healthy and tumor tissues

  4C-seq performed on 10 slices (30um thick) of fresh frozen endometrial tissues. These tissue include 2 healthy tissues and 4 tumor tisseus (post-menopausal patients) in replicate. The library has been performed using DpnII (primary) and NlaIII (secondary) restriction enzymes. Raw single-end fastq.gz files are provided.

  Dataset EGAD00001010897

• Multiomic snRNAseq/snATACseq of human implantation sites, placenta and decidua

  This dataset is part of a study that aims to provide a spatially resolved single-cell multiomics map of human trophoblast differentiation in early pregnancy. This dataset contains 10x multiome snRNA-seq/snATAC-seq from human implantation sites, decidual and placental samples from 8-9 PCW.

  Dataset EGAD00001010038

• PhIP-Seq Serum 1000IBD

  PhIP-Seq experiment conducted in Eran Sigal's group at WIS.

  Dataset EGAD00001010118

• DAC of the 300BCG ATAC-seq data

  To investigate human population variation of trained immunity, we immunized healthy individuals with Bacillus Calmette-Guérin (BCG). This live attenuated vaccine induces not only an adaptive immune response against tuberculosis, but also triggers innate immune activation and memory. We established personal chromatin accessibility maps over a time course of BCG vaccination in 323 individuals using ATAC-seq.

  Dac EGAC50000000056

• Poikiloderma syndrome RNAseq

  We will sequence the RNA of lymphoblast samples, transformed with EBV, which have poikiloderma syndrome with mutations in c16orf57. The aim of the experiment is to characterise RNA structural effects in this disease.

  Dataset EGAD00001000324

• Characterizing the tumor immune microenvironment of ependymomas using targeted gene expression profiles and RNA-sequencing the pros and cons

  RNA sequencing data of a collection of 6 pediatric ependymoma cases

  Dataset EGAD00001009301

• Whole exome and RNA sequencing of 5 samples of patient-derived xenograft (PDX).

  Whole exome and RNA sequencing of 5 samples of patient-derived xenograft (PDX). Available files are raw sequencing fastq files.

  Dataset EGAD00001010102

• 16SV4 ribosomal RNA gene sequencing data

  16SV4 ribosomal RNA gene sequencing data of GI samples and associated mixed community cultures collected from pediatric patients at risk for IBD.

  Dataset EGAD50000000485

• RNA data of neuroblastoma patients

  94 sample with multi-omics analysis of ALT-positive neuroblastoma tumors, rna sequencing

  Dataset EGAD00001006587

• Paired RNA sequencing of 30 samples RRMM (multiple myeloma)

  Paired RNA sequencing of 30 samples RRMM using Illumina TruSeq stranded mRNA kit and either HiSeq2000 or HiSeq X Ten for sequencing.

  Dataset EGAD00001009680

• Transcriptome - Uveal Melanomas

  Total RNA sequencing on 9 uveal melanomas. Libraries were prepared using the TruSeq Stranded Total RNA Library Prep Gold (Illumina, 20020599). Paired-end libraries (2 x 100 bp) were sequenced on a NovaSeq 6000 instrument (Illumina).

  Dataset EGAD50000000763

• scRNA-seq

  Dac EGAC00001000963

• Single-cell proteogenomics of MDS upon AZA

  To study the evolution of the clonal molecular and cellular architecture of MDS upon the treatment with AZA, we performed scDNA-seq of an amplicon panel of 53 genes recurrently mutated in myeloid malignancies, as well as typically lost or gain DNA regions, and scProt-seq of 42 cell-surface proteins to provide a simultaneous landscape of the genetic setting and immunophenotype using the Tapestri platform (MissionBio). We sequenced thousands of cells from 14 MDS patients, where paired bone marrow samples were obtained at the timepoint of diagnosis and after AZA treatment.

  Study EGAS00001007427

• Single Cell Analysis of Sporadic Human Basal Cell Carcinomas

  To explore tumor heterogeneity in sporadic human basal cell carcinoma tumors, we profiled three individual patient tumors by scRNA-Seq and scATAC-Seq. Basal cell carcinomas (BCCs) are driven by hedgehog signaling with GLI1 representing the key downstream transcription factor that drives tumor growth. GLI1 as such is a readout of active hedgehog signaling. We identified that LY6D can mark squamous populations such as in squamous cell carcinomas (SCCs) that are negative for GIL1 and hedgehog signaling. As such, both GLI1 and LY6D can be used as biomarkers of BCCs and SCCs and their related states.

  Study phs003103

• Separation, characterization, and identification of individuals from multi-person blood mixtures with single cell ATAC-seq

  We report a deconvolution and identification strategy of scATAC-seq datasets using mixed PMBCs data. After sequencing the data were processed with the de-goulash pipeline and analyzed with aim to identify and acquire biogeogrpahical ancestry of the involved individuals. The study includes samples of biological mixtures and in silico mixtures in different mixed ration and cell volumes.

  Study EGAS00001007380

• Histone Acetylome-wide Association Study of Autism Spectrum Disorder

  H3K27ac ChIP-seq were performed on postmortem samples from autism spectrum disorder and matched control brains. Tissues were chosen from three brain regions: prefrontal cortex, temporal cortex and cerebellum.

  Study EGAS00001001943

• Human T-bet governs innate and innate-like adaptive IFN-g immunity against mycobacteria.

  We report a patient with mycobacterial disease due to inherited deficiency of the transcription factor T-bet. PBMCs from the patient was analyzed with scRNA-seq.

  Study EGAS00001004504

• BLUEPRINT release August 2014, Bisulfite-Seq for Multiple myeloma

  Bisulfite-Seq data for 2 Multiple myeloma sample(s). 16 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001000934

• BLUEPRINT release January 2015, Bisulfite-Seq for Multiple myeloma

  Bisulfite-Seq data for 2 Multiple myeloma sample(s). 16 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001152

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=24hrs_RPMI_T=5days_LPS_T=4hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=24hrs_RPMI_T=5days_LPS_T=4hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002915

• BLUEPRINT September 2016, ATAC-seq for class switched memory B cell from venous blood, on Genome GRCh38

  ATAC-seq data for 2 sample(s) for class switched memory B cell from venous blood, on Genome GRCh38. 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002908

• BLUEPRINT release August 2016, ChIP-Seq for macrophage - T=6days B-glucan, on genome GRCh38

  ChIP-Seq data for 2 macrophage - T=6days B-glucan sample(s). 6 run(s), 6 experiment(s), 6 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 EGAD00001002314

• BLUEPRINT release August 2016, ChIP-Seq for macrophage - T=6days untreated, on genome GRCh38

  ChIP-Seq data for 2 macrophage - T=6days untreated sample(s). 6 run(s), 6 experiment(s), 6 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 EGAD00001002458

• BLUEPRINT release August 2016, ChIP-Seq for macrophage - T=6days LPS, on genome GRCh38

  ChIP-Seq data for 2 macrophage - T=6days LPS sample(s). 6 run(s), 6 experiment(s), 6 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 EGAD00001002498

• BLUEPRINT September 2016, ATAC-seq for venous blood, on Genome GRCh38

  ATAC-seq data for 136 sample(s) from venous blood, on Genome GRCh38. 141 run(s), 139 experiment(s), 139 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002709

• smRNA-seq of human post-mortem brain data from the frontal lobe (goettingen part)

  This dataset contains smRNA-seq data from human post-mortem brain tissue of the frontal lobe of patients with FTD and healthy controls. These samples depict the data generated at the DZNE Göttingen and should be used together with the data generated at the DZNE Tübingen.

  Dataset EGAD00001006845

• Peripheral Blood Leukocytes 10x Genomics scRNA-seq

  This dataset contains 10x Genomics Single Cell 3’ Solution (version 2) scRNA-seq data from peripheral blood leukocytes of a single healthy donor. Data from 20939 cells were collected over 8 lanes and 2 sequencing runs.

  Dataset EGAD00001008590

• IBMsnRNAseq

  snRNA-seq and spatial transcriptomic data and analysis of healthy (CTRL) and inflamed (immune-mediated necrotizing myopathy (IMNM) and inclusion body myositis (IBM)) human quadriceps muscle. This data set includes 19 snRNA-seq (7 CTRL, 4 IMNM, 8 IBM) and 8 ST samples (3 CTRL, 2 IMNM, 3 IBM).

  Dataset EGAD50000000449

• scRNA seq Data set

  This data set contains the raw FASTq files and processed files of scRNA seq experiment which were conducted on 3 EMD samples. The libraries were generated using 10x genomics Dual index Single Cell 3' v3.1. The processed files are TSV files of features, barcodes, and gene expression matrix

  Dataset EGAD50000000334

• Genomic Analysis of Low Grade B-Cell Lymphoma

  We included tumors from 64 newly diagnosed or untreated Low Grade B-Cell Lymphoma (LGBCL) patients, consisting of SMZL (n = 48), NMZL (n = 6), EMZL (n = 2), LPL (n = 5), and B-NOS (n = 3) in this study. Samples were selected from cases consented to the Molecular Epidemiology Resource (MER) of the University of Iowa and Mayo Clinic Lymphoma Specialized Program of Research Excellence (SPORE). RNA or DNA were extracted from 64 frozen LGBCLs tumors (with available matched germline DNA for N=61. For RNA sequencing, library preparation was done using the Illumina TruSeq RNA Exome Kit and sequenced with 100 nucleotide paired-end reads using the HiSeq 4000. For WES, library preparation was done using the Agilent SureSelect XT kit and sequenced with 100 nucleotide paired-end reads using the Illumina HiSeq 4000.

  Study phs002552

• National Cancer Institute (NCI) Biospecimen Pre-analytical Variables (BPV) Analysis

  The Biospecimen Pre-analytical Variables (BPV) Program is a National Cancer Institute-sponsored study to systematically assess the effects of pre-analytical factors on the molecular profile of biospecimens. A robust biospecimen collection infrastructure was established to prospectively collect biospecimens using rigorous standard operating procedures to control for most variables while introducing experimental conditions to study specific biospecimen handling issues, including the cold ischemic time (delay to formalin fixation), time in formalin, freezing methods, and storage temperatures and durations. RNA and DNA from biospecimens collected under these conditions was analyzed on multiple molecular platforms. The potential effects of these pre-analytical conditions on protein integrity and detection of metabolites were also examined. Data from this study will be used to develop evidence-based biospecimen standard operating procedures and best practices for fit-for-purpose collection, processing, and storage of biospecimens. The BPV Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following sub-studies below or in the "Substudies" box located on the right hand side of this top-level study page phs001304 BPV Cohort. The substudy links will be active once they are released by dbGaP. Preanalytical Impacts on Global Metabolite Profiling - plasma (MassSpec by Metabolon) This study was to evaluate the impact of the storage temperature (s) (-80°C and LN2 vapor) and the length of storage on human plasma quality using LC-MS/MS (liquid-chromatography-mass spectrometry/mass spectrometry) based global metabolite profiling. The study includes 240 plasma samples collected from 40 donors. Investigate the effect of the delay to fixation on the proteome and phosphoproteome -FFPE (MassSpec by Caprion). The study is to do proteome and phosphoproteome analysis on Delay to fixation was carried out using FFPE tumor samples from colon and ovarian cancer patients comparing 2, 3, and 12hr delay to fixation to the 1hr time point. The study includes 100 samples 20 donors. Investigate the effect of storage conditions of tumor specimens on the proteome and phosphoproteome profiling- Frozen tissue and plasma (MassSpec by Caprion). The study was to evaluate the effects of storage conditions on tumor specimens. Plasma samples from 40 cancer patients stored at two different temperatures (-80°C and LN2) for a given period (0-2, 6-8, and 12-14 months) were evaluated. Frozen kidney tumor samples from 20 patients were compared for effects of different snap frozen (dry ice vs. LN2) and storage temperatures (-80°C and LN2). The study includes 100 tissue and 240 plasma samples from 60 donors. Preanalytical Impacts on Genomic Sequencing by Next Generation Sequencing (NGS) technology (mRNA/miRNA and WES by Expression Analysis). The goal of the study is to determine the effects of cold ischemic delay-to-fixation (4 time points) and formalin preservation (FFPE) on the nature and quality of genomic profiles using the matched freshly frozen sample as the gold standard, which including WES, RNAseq. The study includes 395 samples from 37 donors. Preanalytical Impacts on Copy Number Variation (CNV) Detection by aCGH technology (aCGH by Georgetown University). This study was to use aCGH to evaluate the effect of variation in cold ischemia time and time in formalin fixation on CNV in DNA extracted from kidney cancer specimens. The study includes 235 samples from 40 donors. Evaluation of frozen conditions on mRNA profiling by TaqMan assay (mRNA expression by Georgetown University). This study was to utilize gene expression profiling, using custom TaqMan arrays, to compare the molecular profiles of RNA from frozen tumor samples collected using two freezing methods (dry ice or LN2), two storage temperatures (-80°C or LN2 vapor), as well as Optimal Cutting Temperature (OCT) compound and non-OCT embedded. The study includes 100 samples from 20 donors. mRNA signature for stratification by cold ischemia time (mRNA expression by IBBL). The study was to determine the effects of cold ischemic time (delay-to-fixation) and formalin preservation (FFPE) on mRNA detection by Taqman assay using tumor tissue specimens from kidney, colon and ovarian cancer patients. There are160 samples from 40 donors. The Biospecimen PV cohort is utilized in the following dbGaP individual studies. To view molecular data, and derived variables collected in these individual studies, please click on the following individual studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs001304 Biospecimen PV cohort. phs001634 CIT mRNA phs001635 CNV aCGH phs001636 Fixation Delay phs001637 Global Metabolite Profiling phs001638 mRNA TaqMan phs001639 NGS phs001640 Tumor Storage

  Study phs001304

• Transcriptomic analysis of human hematopoietic populations sorted from umbilical cord blood.

  We isolated by fluorescence-activated cell sorting highly purified populations (long term hematopoietic stem cells (LT-HSCs), short term hematopoietic stem cells (ST-HSCs), multipotent progenitors (MPPs), common myeloid progenitor (CMPs), granulocyte and monocyte progenitors (GMPs), multilymphoid progenitors (MLPs), Myeloid-erythorid Progenitor (MEP), Granulocytes, Monocytes, B cells, T cells, Dendritic cells, Natural Killer cells and Erythrocyte Progenitors from 3 to 4 cord blood pools. We extracted RNA from 5K cells of each population and performed RNA-sequencing.

  Study EGAS00001004968

• Drug screen in iPSC-Neurons identifies nucleoside analogs as inhibitors of (G4C2)n expression in C9orf72 ALS/FTD

  To investigate the mode of action and potential side-effects we analyzed differential gene expression in Postmitotic C9orf72 iPSC-Neurons by RNAseq. The cells were treated in a 2 dose regime at 10 µm in 0.1 % DMSO for 9 days. Compound treated iPSC-Neurons were washed with PBS, frozen on dry ice and stored at -80°C until RNA isolation. The RNA was isolated using miRNA Mini Kit (Qiagen) using 700 μl of Qiazol. A total of 250 ng of RNA per sample was processed for mRNA library preparation as per the manufacturer’s instructions for Illumina® Stranded mRNA Prep Ligation to be used with the IDT® for Illumina® RNA UD Indexes Set B and sequenced using NextSeq 500/550 High Output Kit v2.5 (Illumina) on NextSeq 550 (Illumina). The data was processed and analyzed using CLC genomics workbench (Version 21.0.3, Qiagen)

  Dataset EGAD00001008674

• Transcriptome sequencing of fibroblast-dependent alveolar organoids derived from patient-specific iPS cells with SFTPC^Y104H variant and their gene-corrected (monoallelic wild type SFTPC) ones.

  A disease-specific iPS cell line derived from a pulmonary fibrosis patient with SFTPC^Y104H and its gene-corrected (monoallelic wild type SFTPC) one were established. Then lung progenitor cells were differentiated from each cell line and co-cultured with human fetal lung fibroblasts to generate alveolar organoids, respectively. Alveolar epithelial cells and fibroblasts were isolated by fluorescence-activated cell sorting and each RNA was extracted. We performed transcriptome analysis of those samples by RNA-sequencing.

  Study JGAS000617

• Genetic Effects on miRNA Expression During Mid-Gestation Neocortical Development

  In this study we aimed to find common genetic variants that influence miRNA expression during mid-gestation neocortical development. Small RNA-sequencing from 212 fetal cortical tissue samples between 14 and 21 weeks gestation were used to profile miRNA expression. Combined with donor genotypes, we were able to find miRNA-eQTLs during neocortical development. The dataset provided here includes 212 Small RNA-sequencing files in FASTQ format from cortical wall samples. Also provided here are 212 donor genotypes in PLINK format (hg19).

  Study phs003106

• Single Suture Craniosynostosis: Gene and Pathway Discovery

  Craniosynostosis is the premature fusion of one or more of the calvarial sutures. In this work, we used genomics and network modeling to reveal genetic and developmental pathways which, when disrupted, result in premature calvarial fusion. Calvarial bone explants were obtained from children undergoing surgery for single suture craniosynostosis. Primary osteoblast cell lines were established from calvarial explants and used as an RNA source.  The data available includes subject sex, affected suture, RNA sequence variants and counts.

  Study phs002684

• Single cell RNA sequencing of CD19 CAR T-cell infusion products

  We performed single cell RNA sequencing of remnants from CD19 CAR T-cell infusion products used for standard of care treatment for relapsed/refractory large B-cell lymphoma. Libraries were prepared using 10X 5’ GEX chemistry and sequenced on an Illumina HiSeq 4000 to obtain >50,000 reads per cell.

  Study EGAS00001004576

• Oxford Nanopore RNA sequencing for HLA typing

  A targeted RNA-based method for typing of 12 classical HLA genes using Oxford Nanopore sequencing. In the method, were enriched HLA genes from cDNA of 50 individuals using gene-specific reverse primers. The library molecules were then barcoded, pooled into 2 separate gene pools, and sequenced on MinION R9.4 SpotON flow cells.

  Study EGAS00001004918

• RNA sequencing of pretreatment, on-treatment and posttreatment gastric and gastroesophageal junction tumors treated with neoadjuvant anti-PD-L1 plus chemotherapy

  This set contains a total of 78 files cram files with RNA sequencing data from 20 patients included in the PANDA study treated with 1 cycle of monotherapy atezolizumab and 4 cycles atezolizumab plus chemotherapy (docetaxel, oxaliplatin and capecitabine). RNA was isolated from fresh frozen material and sequenced at 4 timepoints baseline, after monotherapy atezolizumab, after combination atezolizumab plus chemotherapy and at resection (due to 2 missing samples, there is a total of 78 samples).

  Dataset EGAD50000000241

• RNA-sequence analysis in patients with inclusion body myositis

  This study aimed to elucidate the molecular features of inclusion body myositis(IBM). We performed RNA sequencing analysis of muscle biopsy samples from myositis patients with the pathological finding of CD8-positive T cells invading non-necrotic muscle fibers expressing major histocompatibility complex class I (IBM, polymyositis, and unclassifiable myositis), and controls.

  Study JGAS000068

• Total RNA sequencing from the TNT trial (NCT00532727)

  Primary tumours from 186 TNT participants (13 matched recurrences) were profiled using total RNA-sequencing. Four transcriptional DDR-related and 25 immune-related signatures were evaluated. We assessed their association with objective-response-rate (ORR) and progression-free-survival (PFS) and performed conditional inference forest clustering to integrate multi-modal data.

  Study EGAS00001007398