11925 results for "cancer rna-seq"

in 20.82 milliseconds.

• Single-cell multi-omics of human clonal hematopoiesis reveals that DNMT3A R882 mutations perturb early progenitor states through selective hypomethylation.

  We profiled CD34+ enriched cells from GCSF mobilized bone marrow samples (n = 4) using single-cell RNA sequencing (10X) with targeted genotyping, and single-cell DNA methylation (RRBS) with single-cell RNA sequencing (Smart-Seq2) and targeted genotyping. A 5th CH bone marrow aspirate sample was obtained to validate observed results.

  Dataset EGAD00001008985

• Single cell RNA sequencing of bone marrow mononuclear cells from healthy donors and B-cell lymphoma patients following CD19 CAR T-cell therapy

  Bone marrow aspirates were obtained from patients with relapsed/refractory large B cell lymphoma (rrLBCL), mononuclear cells isolated by ficoll density-gradient centrifugation, and loaded onto a 10X Chromium for single cell RNA-sequencing using 5’ chemistry without prior cryopreservation. Healthy donor bone marrow mononuclear cells were obtained from healthy allogeneic stem cell transplant donors and analyzed following viable cryopreservation.

  Dataset EGAD00001009774

• Single-Cell RNA Sequencing of Terminal Ileal Biopsies Identifies Signatures of Crohn’s Disease Pathogenesis

  Biopsies from the terminal ileum of healthy individuals and terminal ileum of Crohns disease patients are collected and processed single cells and processed for single-cell RNA-sequencing using 10X Genomics 3' v3 and v3.1 and Illumina sequencing. 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 EGAD00001015692

• Combined Telomerase Vaccination and Pembrolizumab in Advanced Melanoma: WES and RNA sequencing of biopsies from a Phase I Trial

  This dataset contains whole-exome and RNA sequencing of biopsies obtained from patients enrolled in a phase I clinical trial investigating the UV1 vaccine in combination with pembrolizumab in patients with advanced melanoma.

  Dataset EGAD00001011074

• Sequencing data for rare tumors and sarcomas

  This dataset contains DNA and RNA sequencing information for AML, Gliomas, brain tumors (medulloblastoma and ependymoma), DIPG, rhabdoid tumors and soft tissue sarcomas. In total 39 samples are present (14 matched normal, 25 tumor samples). Not all samples have matched normals and not all samples have RNA sequencing data..

  Dataset EGAD00001008974

• RNA sequencing of human intra- and extracranial endothelial cells

  This data set contains the raw .fastq files from one RNA-sequencing experiment. Endothelial cells of the basilar artery and endothelial cells of the carotid artery were post-mortem derived with laser microdissection and sequenced. For this analysis both the basilar- and the carotid artery endothelial cells of eleven individuals were sequenced. For more details please see: DMA Hermkens et al. "Profiling the Unique Protective Properties of Intracranial Arterial Endothelial Cells" Acta Neuropathol Commun. 2019 Oct 14; PMID: 31610812.

  Dataset EGAD00001006203

• Breast Cancer Susceptibility

  Genetic factors account for a large fraction of breast cancer risk and it is estimated that up to 30% of breast cancers have a heritable component. Inherited cancer susceptibility is associated with early-onset of malignancies in general. Although 20% of young women with breast cancer have germline mutations in the best understood breast cancer susceptibility genes, BRCA1, BRCA2 and TP53, in the remaining 80% of women with early-onset breast cancer, the genetic factors contributing to disease remain unexplained. By studying the extreme phenotype of women diagnosed at an early age there is enrichment for genetic factors that contribute to breast cancer. This study contains the whole exome sequence of 384 women diagnosed with invasive breast cancer prior to 40 years of age. Each of the subjects reported a family history of breast cancer and lacked mutations in BRCA1 and BRCA2.

  Study phs001017

• Exome and RNA sequencing data from 32 ocular and extraocular sebaceous carcinomas

  Sebaceous carcinomas (SeC) are cutaneous malignancies that, in rare cases, metastasize and prove fatal. Here we report whole exome sequencing on 32 SeC, revealing distinct mutational classes that explain both cancer ontogeny and clinical course. A UV-damage signature predominated 10/32 samples, while 9 were instead defined by microsatellite instability (MSI) mutations. UV-damage SeC exhibited poorly differentiated, infiltrative histopathologycompared to MSI signature SeC (p = 0.003), features previously associated with dissemination. Strikingly, UV-damage SeC transcriptomes and anatomic distributionclosely resembling those of cutaneous squamous cell carcinomas (SCC), implicating sun-exposed keratinocytes as a cell of origin. Like SCC, this UV-damage subclass harbors a high somatic mutation burden with >50 mutations/Mb, predicting immunotherapeutic response. In contrast, ocular SeC acquire far fewer mutations without a dominant signature, but show frequent truncating mutations in the ZNF750 epidermal differentiation regulator. Our data exemplify how different mutational processes convergently drive histopathologically related but clinically distinct cancers.

  Study EGAS00001002869

• 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

• Targeted MCC-seq

  The capture panel targets the functional methylome in human whole blood. Regions incorporated in the panel design included hypomethylated windows generated from merged WGBS data.

  Dataset EGAD50000000286

• NICHE - DNA-seq of MMR proficient and MMR deficient early stage colon cancers

  The dataset includes 174 FASTQ files from paired-end WXS sequencing on Illumina HiSeq2500 for 39 patients.

  Dataset EGAD00001006041

• Bulk exome sequencing of primary GBM - SF 10360

  We performed bulk exome-seq on a primary GBM and a blood sample from SF10360

  Dataset EGAD00001002274

• Transcriptomic profiling of human small intestine macrophage and DC subsets

  Using low input SMART-seq protocol, the whole transcriptome of human small intestine macrophage subtypes is characterized.

  Dataset EGAD00001003581

• SCNA-Seq of tumor DNA samples

  Low coverage whole genome sequencing for the identification of somatic copy number alterations (SCNA) and focal amplification mapping of corresponding tumor material

  Dataset EGAD00001002150

• RNA-Sequencing generated from 180 human putamen and substantia nigra

  Dataset EGAD00001005526

• GATCI RNAseq fastqs

  Raw RNA sequence data (fastq) for the GATCI project

  Dataset EGAD00001005810

• Identification of Rare Germline Variants in Familial Patients with Non-medullary Thyroid Cancer

  As the most common malignancy of the endocrine system, thyroid cancer is classified into two major categories, non-medullary thyroid cancer (NMTC) and medullary thyroid cancer (MTC) according to the origins and clinical features. NMTC includes papillary thyroid cancer (PTC), follicular thyroid cancer (FTC), and anaplastic thyroid cancer (ATC). Sporadic non-medullary thyroid cancer (SNMTC) accounts for ~90% of all thyroid cancers. Compared to SNMTC, familial non-medullary thyroid cancer (FNMTC) is rare, constituting only 3 - 9%. FNMTC is a complex genetic disease that often shows an autosomal dominant mode of inheritance. Characterization of the germline variants causing the disease is still challenging given the heterogeneity of affected families. In recent years, some mutations in known cancer susceptive coding genes have been reported using targeted DNA sequencing method in FNMTC cases. Still, little is known for the novel mutations in other thyroid cancer predisposition genes. With the decreasing cost and rapid development of next generation sequencing technology, more rare germline mutations underlying different types of cancer susceptibility in families had been discovered by whole genome sequencing (WGS). In this study, we performed WGS in familial NMTC patients in the U.S. Our aim is to identify rare germline variants with high penetrance that may contribute to thyroid cancer predisposition in NMTC families.

  Study phs001758

• Multimodal epigenetic sequencing analysis for colon cancer

  Targeted methylation sequencing (enzymatic conversion) data of plasma samples collected from colon cancer patients and non-cancer subjects.

  Study EGAS50000000052

• Converging and evolving immuno-genomic routes towards immune escape in breast cancer

  This study explores the evolution of tumor and blood immune microenvironment and related mechanisms that shape breast cancer progression, culminating in a heterogeneous lethal cancer.

  Study EGAS00001004956

• BHD-associated kidney cancer

  Background Birt-Hogg-Dub? (BHD) syndrome is a hereditary kidney cancer syndrome, which predisposes patients to develop kidney cancer, cutaneous fibrofolliculomas and pulmonary cysts. The responsible gene, FLCN is a tumor suppressor for kidney cancer which plays an important role for energy homeostasis through the regulation of mitochondrial oxidative metabolism. However, how FLCN-deficiency leads to renal tumorigenesis is unclear. Results Whole-exome sequencing analysis of BHD-associated kidney cancer revealed that copy number variations (CNV) of BHD-associated kidney cancer are considerably different from those already reported in sporadic cases. Somatic mutation analysis revealed BHD-associated kidney cancer has quite few common mutations in specific genes; however, chromatin remodeling genes in total were frequently mutated in BHD-associated kidney cancer (17/29 tumors, 59%). Metabolite analysis revealed that glycolysis, pentose phosphate pathway and lipid metabolism were upregulated whereas the rate of beta oxydation and TCA cycle is decreased in BHD-associated kidney cancer compared to normal adjacent kidney. Conclusions BHD-associated kidney cancer displays a unique molecular characteristics which is totally different from that of sporadic kidney cancer, providing the mechanistic insight into tumorigenesis under FLCN deficiency as well as the foundation for the development of novel therapeutics for kidney cancer.

  Study JGAS000115

• Dataset for leiomyosarcoma-RNA

  Rare cancer sequencing data of 87 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008849

• Dataset for head_and_neck_cancer-RNA

  Rare cancer sequencing data of 92 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008861

• Base modification analysis using single molecule real-time sequencing

  Based on the kinetic characteristics of single-molecule real-time sequencing, we implement a method to directly detect DNA modifications such as 5mC. However, there are room to further improve the accuracy of whole-genome-wide DNA modifications. Therefore, this study aims to utilize deep learning methods for the comprehensive profiling of multiple DNA modifications, including 5mC, 5hmC, and 6mA, using SMRT-seq.

  Study EGAS50000000366

• scMethylation data of 5 regionally sampled GBM tissue for 2 patients

  This dataset contains snRNA-seq data of 5 regionally sampled GBM tissue (peritumoral region, tumor edge, and tumor core). Regionally sampled GBM patient tissue was dissociated and nuclei were processed in an unbiased manner without any sorting procedure. Nuclei dissociation was performed following the nuclei isolation for single-cell ATAC-seq (10x Genomics; CG000169) with matched peri-tumoral and tumor core samples. Subsequent single-cell methylation sample preparation followed Scale Biosciences single-cell methylation kit protocol v1.0. mplification adaptors through ligation and adding a second barcode though indexed PCR reaction following Scale Biosciences single-cell methylation kit protocol v1.0. We employed the TWIST human methylome panel for targeted enrichment of informative methylation sites.

  Dataset EGAD50000001837

• Gremlin 1 + fibroblastic niche maintains dendritic cell homeostasis in lymphoid tissues

  Although cross-species transcriptional analysis has been generated for DCs37, transcriptomic conservation between mouse and human FRCs at single-cell resolution has been unclear. To test whether GREM1+ FRCs might also play a role in DC homeostasis in humans, we performed scRNA-seq of CD45–PDPN+ stromal cells, as well as CD45+CD11c+ immune cells from healthy human LNs of three donors.

  Study EGAS00001006211

• Whole exome sequencing of colorectal cancer

  To elucidate immune status of solid tumors including gastrointenstinal cancer, we performed whole exome sequencing of colorectal cancer 7 patients.

  Study JGAS000279

• Identification of genetic mutations characteristic for recurrence of serous ovarian cancer.

  Establishment of novel therapeutic strategy to overcome intractable cancer by molecular profiling of serous ovarian cancer

  Study JGAS000104

• RNA Editing Exome

  Exome sequencing data for tumor and matched normal samples of the EGAS00001000495 project.

  Dataset EGAD00001000626

• RNA Editing AZIN1 amplicon sequencing

  AZIN1 amplicon sequencing data of the EGAS00001000495 project.

  Dataset EGAD00001000708

• Saliba Lab Data Access Committee

  DAC for data generated by Saliba Lab at Helmholtz institute for RNA-based Infection Research, Würzburg, Germany

  Dac EGAC50000000152

• UTUC RNAseq data

  RNA sequencing of upper urinary tract urothelial carcinoma

  Dataset EGAD00001007667

• Prostate Cancer Genome Sequencing Project

  Prostate cancer is a prevalent cause of cancer morbidity and mortality in men. In order to characterize the full range of somatic mutations in protein-coding genes that may drive the growth of prostate cancer, we sequenced the exonic regions of genomic and tumor DNA from over 100 patients with high-risk primary prostate cancer. Using hybrid capture and paired end DNA sequencing, we identified mutations in several novel putative prostate cancer genes. We interrogated copy number changes across tumor genomes using high-density SNP arrays, and identified a molecular subtype of cancer characterized by mutation of the ubiquitin ligase subunit SPOP and copy number loss at specific genomic loci.

  Study phs000447

• Colorectal_organoids_and_tumoroids___pulldown

  Targeted capture of cancer gene panel bait set in single cell derived organoids from colon tissue and colorectal cancer from 1 patient.

  Study EGAS00001000869

• Comparison of WGBS, EPIC array, EM-seq, and Nanopore sequencing in assessing DNA methylation marks

  Bisulfite sequencing has long been the default method for analyzing methylation marks due to its single base resolution. However, the associated DNA degradation poses a concern for fragmented samples. Although several methods have been proposed to circumvent this issue, there has yet to be a clear consensus on which method is best suited for detecting methylation. We present an overview of the two mostly used and two alternative approaches: whole-genome bisulfite sequencing (WGBS), Illumina methylation microarray (EPIC), Enzymatic Methyl-sequencing (EM-seq) and third-generation sequencing by Oxford Nanopore Technologies (ONT). We evaluated DNA methylation levels in three human genomes derived from tissue, cell line, and whole blood.

  Study EGAS00001008014

• ABIS_1_MeDIP-seq

  We investigated changes in whole genome DNA-methylation in a group of 48 healthy five-year-old children differentiated by their hair cortisol levels. By combining this novel biomarker for chronic stress with methylated DNA immunoprecipitation sequencing (MeDIP-seq), we found that high cortisol were associated with a genome-wide decrease in DNA-methylation targeted to specific zinc finger transcription factor binding sites, repetitive elements and genes important for neurodevelopment and calcium transport. Large scale hypomethylation of repetitive regions, as well as a deficient calcium transport, have been reported in many stress related diseases, as well as in many cancers and biological aging. Thus our findings may aid in our understanding of how susceptibility to these diseases develops.

  Study EGAS00001001099

• scRNA-seq of HSPC treated with gemcitabine and carboplatin

  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. The raw FASTQ-files are available as read 1 and read 2 files from 4 lanes for each sample giving a total of 16 FASTQ-files. The FASTQ-files were also 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 (dge) for each cell of each sample. This has resulted in one dge text file and one dge summary text file per sample. These 8 text-files with dge data are found in the zip-compressed analysis data-file.

  Dataset EGAD00001006080

• 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

• RNA isoform repertoire of neuropsychiatric risk genes in human brain

  Neuropsychiatric disorders are highly complex conditions and the risk of developing a disorder has been tied to hundreds of genomic variants that alter the expression and/or products (isoforms) made by risk genes. However, how these genes contribute to disease risk and onset through altered expression and RNA splicing is not well understood. Here we show our current understanding of gene isoforms is far from complete and reveal the precise splicing profiles of neuropsychiatric disorder risk genes. Combining our new bioinformatic pipeline IsoLamp with nanopore long-read amplicon sequencing, we deeply profiled the RNA isoform repertoire of 31 high-confidence neuropsychiatric disorder risk genes in human brain. We show most risk genes are more complex than previously reported, identifying 443 novel isoforms and 28 novel exons, including isoforms which alter protein domains, and genes such as ATG13 and GATAD2A where most expression was from previously undiscovered isoforms. The greatest isoform diversity was present in the schizophrenia risk gene ITIH4. Mass spectrometry of brain protein isolates confirmed translation of a novel exon skipping event in ITIH4, suggesting a new regulatory mechanism for this gene in brain. Our results emphasize the widespread presence of previously undetected RNA and protein isoforms in brain and provide an effective approach to address this knowledge gap. Uncovering the isoform repertoire of neuropsychiatric risk genes will underpin future analyses of the functional impact these isoforms have on neuropsychiatric disorders, enabling the translation of genomic findings into a pathophysiological understanding of disease.

  Study EGAS00001007744

• Frequent mutation of the FOXA1 untranslated region in prostate cancer

  We sequenced the coding and untranslated regions of 72 prostate cancer driver genes in 712 plasma cell free DNA samples from 428 men with metastatic prostate cancer, in an effort to understand the role of untranslated region mutations in late stage prostate cancer.

  Study EGAS00001003113

• Shanghai Breast Cancer Genetics Study (SBCGS)

  The Shanghai Breast Cancer Genetics Study (SBCGS) includes data from four population-based studies conducted among Chinese women in urban Shanghai: the Shanghai Breast Cancer Study (SBCS), the Shanghai Breast Cancer Survival Study (SBCSS), the Shanghai Women's Health Study (SWHS), and the Shanghai Endometrial Cancer Study (SECS, contributing controls only). Shanghai Breast Cancer Study (SBCS): The SBCS is a population-based, case-control study conducted in urban Shanghai. Subject recruitment in the initial phase of the SBCS (SBCS-I) was conducted between August 1996 and March 1998. The second phase (SBCS-II) of recruitment occurred between April 2002 and February 2005. Breast cancer cases were identified through the population-based Shanghai Cancer Registry and supplemented by a rapid case-ascertainment system. Controls were randomly selected using the Shanghai Resident Registry. Approximately 3500 cases and 3500 controls were recruited in the study. Shanghai Breast Cancer Survival Study (SBCSS) and Shanghai Endometrial Cancer Study (SECS): The SBCSS also used the population-based Shanghai Cancer Registry to identify newly diagnosed breast cancer cases. A total of 5,046 breast cancer patients were recruited. In-person interviews were conducted to collect information on known breast cancer risk factors and anthropometrics by using protocols and questionnaires similar to those used in the SBCS. For genetic studies, controls for the SBCSS cases came from the SECS, which recruited healthy women between January 1997 and December 2003. With the exception of a few questions related specifically to breast or endometrial cancer risk, the questionnaires used in the SECS and the SBCS were very similar. Shanghai Women's Health Study (SWHS): The SWHS is a population-based prospective cohort study of approximately 75,000 adult women who were recruited between 1997 and 2000. The cohort has been followed by a combination of record linkage and active follow-ups. Breast cancer patients identified in the SWHS and non-cases were included in the current study.

  Study phs001088

• Shanghai Breast Cancer Genetics Study (SBCGS)

  The Shanghai Breast Cancer Genetics Study (SBCGS) includes data from four population-based studies conducted among Chinese women in urban Shanghai: the Shanghai Breast Cancer Study (SBCS), the Shanghai Breast Cancer Survival Study (SBCSS), the Shanghai Women's Health Study (SWHS), and the Shanghai Endometrial Cancer Study (SECS, contributing controls only). Shanghai Breast Cancer Study (SBCS): The SBCS is a population-based, case-control study conducted in urban Shanghai. Subject recruitment in the initial phase of the SBCS (SBCS-I) was conducted between August 1996 and March 1998. The second phase (SBCS-II) of recruitment occurred between April 2002 and February 2005. Breast cancer cases were identified through the population-based Shanghai Cancer Registry and supplemented by a rapid case-ascertainment system. Controls were randomly selected using the Shanghai Resident Registry. Approximately 3500 cases and 3500 controls were recruited in the study. Shanghai Breast Cancer Survival Study (SBCSS) and Shanghai Endometrial Cancer Study (SECS): The SBCSS also used the population-based Shanghai Cancer Registry to identify newly diagnosed breast cancer cases. A total of 5,046 breast cancer patients were recruited. In-person interviews were conducted to collect information on known breast cancer risk factors and anthropometrics by using a protocol and questionnaire similar to those used in the SBCS. For genetic studies, controls for the SBCSS cases came from the SECS, which recruited healthy women between January 1997 and December 2003. With the exception of a few questions related specifically to breast or endometrial cancer risk, the questionnaires used in the SECS and the SBCS were very similar. Shanghai Women's Health Study (SWHS): The SWHS is a population-based prospective cohort study of approximately 75,000 adult women who were recruited between 1997 and 2000. The cohort has been followed by a combination of record linkage and active follow-ups. Breast cancer patients identified in the SWHS and non-cases were included in the current study.

  Study phs000799

• H3K27ac HiChIP Dataset for 19 T-ALL patients and one normal control sample

  19 H3K27ac HICHIP from T-ALL patient samples and one healthy normal control sample. Reads were aligned to HG38 reference.

  Dataset EGAD50000000023

• scRNA-seq analysis of HGSC tumors, including immune TME, before and after NACT

  Gene expression profiles of single cells from 26 tumor and ascites samples samples from 17 patients

  Dataset EGAD50000000862

• Bulk exome sequencing of primary GBM - SF 10282

  We performed bulk exome-seq on a primary GBM and a blood sample from SF10282

  Dataset EGAD00001002275

• Bulk exome sequencing of primary GBM - SF 10345

  We performed bulk exome-seq on a primary GBM and a blood sample from SF10345

  Dataset EGAD00001002273

• NiCOL Study Target-seq dataset

  10 samples sequenced in Target-sequencing of a panel of 571 genes (Illumina NovaSeq 6000) - Raw FASTQ data - Annotated VCF

  Dataset EGAD00001010911

• Paired-end Whole Exome-seq analysis of the 3D spatially mapped GBM samples.

  Dataset contains 50 paired-end Whole Exome sequencing samples from 3 patients. 3 normal blood samples are also included.

  Dataset EGAD00001010289

• ChIP sequencing from a collection of PFA tumors

  ChIP data from PFA (n = 10). Raw data provided as FASTQ. Data generated on Illumina NovaSeq 6000 PE50.

  Dataset EGAD00001009045

• H3K27ac ChIPseq of cohesin-mutated and wildtype adult AMLs

  ChIP-seq targeting the H3K27ac histone modification in cohesin-mutated (STAG2 or RAD21 mutation) and cohesin wildtype (CTRL-AMLs) AMLs.

  Dataset EGAD00001011204

• ChIPseq of neuroblastoma

  This dataset contains 4 samples (2x input and 2x H3K27ac ChIPseq) in the IC-pPDXC-63 cell line.

  Dataset EGAD00001006557