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• The application of RNA sequencing for the diagnosis and genomic classification of pediatric acute lymphoblastic leukemia

  RNA-seq data for ALL patients as described in "The application of RNA sequencing for the diagnosis and genomic classification of pediatric acute lymphoblastic leukemia"

  Dataset EGAD00001006335

• RNAseq of human intestinal epithelial cell layers cultured in OGM, ENR, and ENRRT

  This dataset contains RNA sequencing data in fastq and bam format from 24 samples of human jejunum organoids grown in 3D configuration or as 2D monolayers on anodisc imaging chambers (AICs) in medium formulations OGM, ENR, and ENRRT. The RNA sequencing samples were sequenced using paired-end sequencing (2x150 bp) on an Illumina NovaSeq 6000 instrument at the SciLifeLab National Genomics Infrastructure (NGI) in Uppsala.

  Dataset EGAD50000001766

• Single-cell Transcriptome Analysis of Plasma Cells Across the Disease Spectrum of Multiple Myeloma

  This dataset includes FastQ files of single-cell RNA sequencing data of 5' GEX and VDJ libraries from CD138+ plasma cells enriched from 72 bone marrow aspirates from patients diagnosed with a monoclonal gammopathy from the multiple myeloma spectrum, including MGUS (n=13), SMM (n = 22), NDMM (n = 17), RRMM (n = 15) and PCL (n = 2); and 3 controls.

  Dataset EGAD50000001179

• Targeted RNA-Seq

  This dataset contains targeted RNA-Seq generated with the Illumina RNA Pan-Cancer panel. It comprises 2200 cancers from children and adults. The cancers represent a wide range of CNS, solid and haematopoietic tumours. Samples are from pathology specimens including FFPE, fresh frozen, bone marrow aspirate and peripheral blood. Samples were tested in a clinical diagnostic lab to identify relevant SNVs, indels and gene fusions.

  Dataset EGAD50000000980

• RNA-sequencing of T-cell Acute Lymphoblastic Leukemia (T-ALL)

  This dataset contains raw fastq files from the RNA-Seq of 96 T-Acute Lymphoblastic Leukemia. Libraries where prepared using Agilent SureSelect XT-HS2 RNA Reagent Kit. As such, reads contain molecular barcodes that could be specifically handled using the AGeNT tool.

  Dataset EGAD00001010273

• Single-cell RNA-seq data of bronchoalveolar lavage (BAL) fluid in late severe COVID-19

  We performed single-cell RNA-sequencing of cells in the bronchoalveolar lavage (BAL) fluid of late severe COVID-19. This study provides detailed insights into the alveolar macrophage response to SARS-CoV-2 infection and reveals a profibrotic macrophage response in severe COVID-19 patients.

  Dataset EGAD00001008161

• He et al. WES data

  This dataset are the bam files of WES data from the paper by He et al.

  Dataset EGAD00001007134

• Genetic alterations in benign breast biopsies of subsequent breast cancer patient

  This dataset consists of amplicon sequencing of fibrocystic breast tissues, subsequent cancer tissue and germline control of 17 patients. The target genes include all exons of 27 protein-coding genes and 2 non-coding genes, as well as mutation hotspots in three cancer genes, frequently mutated in breast cancer. Ion AmpliSeq libraries were generated and sequenced on the Ion S5 XL system.

  Dataset EGAD00001004874

• Whole genome sequencing data of lung adenocarcinomas

  This dataset includes the whole-genome sequencing data from a study entitled "Tracing Oncogene Rearrangements in the Mutational History of Lung Adenocarcinoma". Whole-genome sequencing libraries were generated by PCR-free methods, and sequencing run was made in HiSeq X Ten machines. PCR duplicates-marked, indel-realigned, and base-recalibrarted BAM files are provided in our dataset.

  Dataset EGAD00001004793

• An Ultrasensitive Method for Detection of Cell-Free RNA

  Our study describes the development of a novel method for cell free RNA (cfRNA) analysis called RARE-Seq (Random priming & Affinity capture of cell-free RNA fragments for Enrichment analysis by Sequencing). We find RARE-Seq improves the limit of detection for tumor-naïve cancer detection while maintaining high specificity. We explore the potential utility of RARE-Seq in diverse clinical applications, including non-invasive ctRNA genotyping, treatment resistance monitoring, and molecular characterization of non-malignant conditions.

  Study phs004091

• Comparison of the diagnostic yield of aCGH and NGS across different neurodevelopmental disorders

  Current recommendations for the genetic diagnosis of neurodevelopmental disorders (NDDs) do not include the use of next generation sequencing (NGS) and are still based on chromosomal microarrays, such as comparative genomic hybridization array (aCGH). The present study compares the diagnostic yield obtained by aCGH and clinical exome sequencing in NDD globally and its spectrum of disorders. To that end, 1412 patients clinically diagnosed with NDDs and studied with aCGH were classified into phenotype categories: Global developmental delay/intellectual disability (GDD/ID); autism spectrum disorder (ASD); and Other NDDs. These categories were further subclassified into subcategories, based on the most frequent accompanying signs and symptoms: isolated forms, forms with epilepsy; forms with micro or macrocephaly and syndromic forms. A subset of 245 patients of the 1412 were subjected to clinical exome sequencing. Diagnostic yield of aCGH and clinical exome sequencing, expressed as the number of solved cases, was compared for each phenotype category and subcategory. Clinical exome sequencing was superior than aCGH for all cases except for isolated ASD, with no cases solved by NGS. Globally, clinical exome sequencing solved 20% of cases (versus 5.7% by aCGH) and the diagnostic yield was highest for all forms of GDD/ID and lowest for Other NDDs (7.1% versus 1.4% by aCGH) and ASD (6.1% versus 3% by aCGH). In the majority of cases, diagnostic yield was higher in the phenotype subcategories than in the mother category. These results support the use of NGS as the first-tier test in the diagnostic algorithm of all NDDs followed by aCGH when necessary.

  Study EGAS00001004949

• DAC for "Uncovering the potential of circulating tumor DNA for pediatric precision oncology"

  Dac for "Uncovering the potential of circulating tumor DNA for pediatric precision oncology" with Stefan Pfister (s.pfister@kitz-heidelberg.de) and Kendra Maass (k.maass@kitz-heidelberg.de)

  Dac EGAC50000000269

• Whole-exome sequencing and RNA-seq of paired normal-tumour samples from MMR-proficient early-onset colorectal cancer patients

  This dataset contains fastq files obtained from paired samples of normal colonic mucosa and tumour tissue, collected from 19 patients diagnosed with MMR-proficient colorectal cancer at an age of 50 years or younger. It includes both whole-exome sequencing and RNA-seq data, generated on the Illumina HiSeq 3000 platform. Additionally, the dataset includes phenotypic information from the patients.

  Dataset EGAD50000001844

• Small-RNA sequencing of pheochromocytoma and paraganglioma arising from germline SDHB mutations

  Single-end 75 basepair small-RNA sequencing of 90 SDHB-deficient non-metastatic and metastatic pheochromocytoma and paraganglioma. Samples were prepared using the NEXTFLEX® Small RNA-Seq Kit v3 (Bioo Scientific ). Samples were sequenced at the molecular genomics core (Peter MacCallum Cancer Centre) using 50bp single end sequencing on the Illumina NextSeq 500 (Illumina, USA). This dataset contains raw sequencing reads in FASTQ format.

  Dataset EGAD50000000501

• subset of DEEP IHEC release 2016 (EGAS00001001937), as used in EGAS00001001656 (bidirectional promotors paper, Fatemeh et al. 2018)

  part of the DEEP project results resulted in the publication of 'Integrative analysis of single-cell expression data reveals distinct regulatory states in bidirectional promoters', Epigenetics & Chromatin (2018), Fatemeh et al., DOI: 10.1186/s13072-018-0236-7, PMID: 30414612, PMCID: PMC6230222. This dataset contains the subset of DEEP data related to that study.

  Dataset EGAD00001005953

• Recalibrated whole-exome sequencing alignment data of papillary thyroid cancer of Saudi Arabia

  The dataset consists of samples from papillary thyroid cancer patients. A total of 11 DNA samples from blood/normal and cancer tissue are subjected to whole exome sequencing using Illumina. The fastq files generated were aligned with reference genome ‘hg19’, duplicates were marked, realignment around indels and quality recalibration were performed to produce good quality variants. The recalibrated “.bam” files are included with this dataset.

  Dataset EGAD00001004490

• Axes of Biological Variation in Diffuse Large B-Cell Lymphoma

  To explore the DLBCL molecular and genetic environment, we conducted genome-wide NGS sequencing on 103 DLBCL biopsy samples (named as Cornell-NCI cohort) with NGS platforms, including bulk WES, etc. The raw fastq files of the bulk WES were deposited on the EGA for user access. For additional information regarding the genomic data associated with the study, please also see the paper companion website at https://llmpp.ccr.cancer.gov/local/DLBCL_singlecell/

  Study EGAS50000001227

• Whole Genome Sequencing from patients with multiple myeloma treated with BCL2 inhibitor based treatment

  Samples was collected at the Mayo Clinic. MM tumor samples were enriched using the StemCell EasySep Human CD138 positive selection kit II (StemCell, Cambridge, MA). DNA from CD138+ MM cell (tumor) or peripheral blood samples (germline control) at Mayo Clinic (Rochester or Arizona) underwent WGS. For samples collected at Mayo Clinic Rochester, library preparation was completed using the NEB Ultra II (New England Biolabs, Ipswich, MA) and the Nextera Flex systems (Illumina, San Diego, CA) and sequenced at the Mayo Clinic Genome Analysis Core with an approximate depth of 30X for tumor samples and 60X for the germline control. For samples collected at Mayo Clinic Arizona, Novogene was used for WGS following random shearing of the DNA, end-repairs, A-tailed and ligated with Illumina adapters. Sequencing was performed on the Illumina Novaseq 6000 sequencer Reference Genome: GRCh38.

  Dataset EGAD50000002132

• A Pharmcogenetic Study of Bipolar Disorder in a Taiwanese Han Chinese Population (TWBP)

  Objective: To identify genetic variants associated with response to lithium prophylaxis treatment. Materials: 294 bipolar I (BPI) patients receiving lithium treatment, a subset of 1761 bipolar I (BPI) patients recruited by the Taiwan Bipolar Consortium. Lithium response was assessed based on the Alda Scale. Methods: Responders to lithium treatment were defined if the patients' Alda Scale > 4, 5, 6, and 7. Genome-wide association (GWA) analysis was carried out on the 294 BPI patients for the 4 definitions of responders. The SNPs showing strongest association in the GWAS were then tested for association in a replication sample of 100 patients and further tested in a prospective follow-up series of 24 patients. Results: Two SNPs on GADL1 showed the strongest associations in the four GWA analyses and in the replication set of 100 patients. These two SNPs had a sensitivity of 0.93 for predicting lithium response and differentiated between the good and poor responders in the follow-up cohort. Summary: These genetic variants are associated with response to lithium prophylaxis treatment for BPI.

  Study phs000692

• The dataset for Genome-wide analyses of cell-free DNA for therapeutic monitoring of patients with pancreatic cancer

  The dataset for “Genome-wide analyses of cell-free DNA for therapeutic monitoring of patients with pancreatic cancer” includes 496 cram files from whole genome next-generation sequencing on the Illumina NovaSeq 6000. The samples analyzed include tumor tissue, matched buffy coat and longitudinal plasma samples from individuals with pancreatic cancer.

  Dataset EGAD50000001353

• Single Cell Genome Variation Induced by Mutational Processes in Cancer - HGSOC Trios Study

  Mutational signatures derived from whole genome sequencing have potential prognostic significance. Identification of high grade serous ovarian cancer patients with deficiency in homologous recombination repair pathways could identify a subset of patients that would benefit from homologous recombination deficiency-specific treatments independent of identification of a pathological BRCA1/2 gene mutation. Clinical protocols rely on a pathologist's assessment of formalin-fixed paraffin-embedded (FFPE) tissues, and thus FFPE tissue samples are readily available. However, the bulk of mutational signature analyses have been performed on fresh frozen tissues. In this study, we aimed to assess the reliability of whole genome sequencing, variant calling, and mutational signature analysis from FFPE tissue samples.

  Study phs003036

• Single-Cell Profiling of Premature Neonate Airways Reveals a Continuum of Myeloid Differentiation

  We set out to develop a reference single-cell transcriptomic profile of airway aspirate samples from extremely premature neonates (collected within an hour of birth). In this study, we profiled samples from 10 subjects. We identified cells in the airways of premature neonates representing a continuum of myeloid differentiation, including fetal monocytes, differentiating myeloid cells, and macrophages. Trajectory analysis identified two trajectories consistent with interstitial and alveolar macrophages, and a bridging trajectory providing an alternative route between these terminal states. We defined 259 alveolar-specific genes, 666 interstitial-specific genes, and 285 bridging-specific genes providing the first single-cell transcriptional map of differentiating airway macrophages in humans.

  Study phs003427

• Molecular Genetics of Heroin Dependence in China

  Our principal goal was to determine the chromosomal locations of genetic variations associated with increased vulnerability to heroin dependence. This goal was attained by identifying specific DNA markers that are genetically linked to heroin dependence. We collected blood and diagnostic information (using a structured diagnostic interview) from 1230 people (sib-pairs) having DSM-IV defined heroin dependence as well as from their parents and other affected and unaffected siblings, when possible. Genotype and clinical data was archived using database software. We conducted a multipoint linkage analysis using the guidelines of Lander and Kruglyak to assert statistical significance, and followed up on regions of interest with a dense set of markers to evaluate candidate genes.

  Study phs001213

• Pathologically Expanded Peripheral B Cell-Helper T Cells in Rheumatoid Arthritis

  PROSET-HD aims to identify and study immune cell populations altered in patients with autoimmune and inflammatory diseases. We have identified a population of PD-1hi CXCR5- 'peripheral helper' T (Tph) cells that are expanded in the joints and circulation of patients with seropositive rheumatoid arthritis. This T cell population uniquely combines potent B cell-helper function with a migratory program that directs homing to inflamed tissues. RNA sequencing was performed on sorted memory CD4+ T cell subpopulations to compare the global gene expression profiles of PD-1hi CXCR5- CD4+ T cells, PD-1hi CXCR5+ follicular helper T cells, and other T cell populations obtained from blood of rheumatoid arthritis patients.

  Study phs001262

• HDAC inhibitors in synovial sarcoma cells

  Histone deacetylase (HDAC) inhibition has been shown in previous studies to disrupt the synovial sarcoma oncoprotein complex, resulting in apoptosis. To understand the molecular effects of HDAC inhibition, RNA-Seq transcriptome analysis was undertaken in six human synovial sarcoma cell lines. HDAC inhibition induced pathways of cell cycle arrest, neuronal differentiation and response to oxygen-containing species, effects also observed in other cancers treated with this class of drugs. More specific to synovial sarcoma, polycomb-group targets were reactivated including tumor suppressor CDKN2A, and pro-apoptotic transcriptional patterns were induced. Functional analyses revealed that ROS-mediated FOXO activation and pro-apoptotic factors BIK, BIM and BMF were important to apoptosis induction following HDAC-inhibition in synovial sarcoma

  Study EGAS00001002637

• Blood transcriptome profiling links immunity to disease severity in myotonic dystrophy type 1 (DM1).

  The blood transcriptome was examined in relation to disease severity in type I myotonic dystrophy (DM1) patients who participated in the Observational Prolonged Trial In DM1 to Improve QoL- Standards (OPTIMISTIC) study. This sought to a) ascertain if transcriptome changes were associated with increasing disease severity, as measured by the muscle impairment rating scale (MIRS) and b) es-tablish if these changes in mRNA expression and associated biological pathways were also observed in the Dystrophia Myotonica Biomarker Discovery Initiative (DMBDI) microarray dataset in blood (with equivalent MIRS/DMPK repeat length). The changes in gene expression were compared using a number of complementary pathways, gene ontology and upstream regulator analyses, which suggested that symptom severity in DM1 was linked to transcriptomic alterations in innate and adaptive im-munity associated with muscle wasting. Future studies should explore the role of immunity in DM1 in more detail to assess its relevance to DM1.

  Study EGAS00001006926

• RNAseq in pleural mesothelioma primary cell lines

  Pleural mesothelioma (PM) requires new treatments. Drug repurposing offers a potential approach to finding effective therapies. This study aimed to explore new therapeutic options for PM using RNA sequencing. RNA sequencing was performed on 58 patient-derived PM cell lines. Drug screening of over 1300 compounds was conducted on 11 lines, with further testing of selected drugs on 48 lines. Top candidates were validated in 3D culture and mouse models.

  Dataset EGAD00001015408

• scRNA-seq

  This dataset gather scRNAseq data performed for MM.1S cell line in control and dex conditions at 4h and 24h

  Dataset EGAD00001011139

• mapped Bam files from whole transcriptome RNA-seq

  In this study we characterized genomic alterations in two to five metachronous bladder tumors from 29 patients initially diagnosed with early stage disease. Fourteen patients (32 tumors) had non progressive disease (NPD) and 15 patients (34 tumors) had progressive disease (PD). Whole exome sequencing (WES, ~50x mean read depth and whole transcriptome RNA-seq was performed (RNA was not advalible for 4 tumors). Data provided here consist of 71 mapped Bam files form whole transcriptome RNA-seq.

  Dataset EGAD00001002718

• unmapped Bam files from whole transcriptome RNA-seq

  In this study we characterized genomic alterations in two to five metachronous bladder tumors from 29 patients initially diagnosed with early stage disease. Fourteen patients (32 tumors) had non progressive disease (NPD) and 15 patients (34 tumors) had progressive disease (PD). Whole exome sequencing (WES, ~50x mean read depth and whole transcriptome RNA-seq was performed (RNA was not advalible for 4 tumors). Data provided here consist of 71 unmapped Bam files form whole transcriptome RNA-seq.

  Dataset EGAD00001002717

• Centers for Common Disease Genomics (CCDG) - Whole Genome Sequencing in Type 1 Diabetes (T1DGC)

  The Type 1 Diabetes Genetics Consortium (T1DGC) was established to collect resources (biological samples and data) and conduct research to better understand the genetic basis of type 1 diabetes (T1D). Collection was initiated by ascertaining affected sib-pair families (both parents, two affected siblings and, when available, an unaffected sibling), collected from five geographic regions through four recruitment networks (Asia-Pacific, Europe, North America, United Kingdom). In addition, the T1DGC collected trio families (both parents and affected child) and cases and controls from low-prevalence populations (African-American, with four grandparents self-reporting as African ancestry; Mexican-American, with four grandparents self-reporting as ancestry from Mexico). The T1DGC also served as a repository for contributed collections from other studies, all meeting the broad data-sharing policy of the T1DGC, for inclusion in the genetic studies. These collections include T1D case samples ascertained from the UK Genetic Resource Investigating Diabetes (UK GRID) cohort, SEARCH for Diabetes in Youth (SEARCH), The Genetics of Kidneys in Diabetes (GoKinD), and control samples obtained from the British 1958 Birth Cohort, the UK National Blood Services collection, CLEAR (Consortium for the Longitudinal Evaluation of African-Americans with Early Rheumatoid Arthritis), the New York Cancer Project (NYCP), and other cohorts. For the NHGRI-funded Centers for Common Disease Genomics (CCDG) project, participants with T1D and ancestry-matched controls were identified through the T1DGC, either through direct ascertainment or by contribution from other sources to the T1DGC. As the CCDG has focused initially on non-Caucasian populations for whole genome sequencing, T1DGC participants of African, Mexican and Asian ancestry (targeting ~1200 cases and ~1200 controls in each ancestral group) and a small group of participants of Northern European ancestry (~100 cases, ~100 controls) were to be contributed to the study. Whole genome sequencing of T1DGC samples would be conducted at Washington University McDonnell Genome Institute and based upon matching case-control status within an ancestry group and prioritization by the CCDG.

  Study phs001222

• Therapy-Induced APOBEC3A Drives Evolution of Resistance to Targeted Therapies in Non-Small Cell Lung Cancer

  The purpose of this study was to identify mechanisms of resistance and associated mutational signatures in non-small cell lung cancers (NSCLCs) treated with targeted therapies. Whole genome sequencing (WGS) and whole exome sequencing (WES) were performed on tumor tissue or cell lines derived from oncogene-driven NSCLCs before and after treatments with tyrosine kinase inhibitors. Somatic mutations were called and mutational signature analysis was performed, revealing enrichment of APOBEC mutational signatures mutational signatures in post-treatment tumors after the development to resistance to targeted therapies. The cohort includes WGS and WES data of tumor and normal tissues from patients with oncogene-driven NSCLCs harboring EGFR mutations, ALK fusions or NTRK1 fusions, who were treated with molecularly targeted therapies that target these oncogenes.

  Study phs003256

• Multi-omics analysis of serial samples from metastatic TNBC patients on PARP inhibitor monotherapy provide insight into rational PARP inhibitor therapy combinations

  In a pilot study, we evaluated the safety and efficacy of olaparib/durvalumab combination treatment in mTNBC patients and the feasibility of real-time deep analysis of serial tumor samples from triple negative breast cancer patients to identify mechanisms of resistance and treatment opportunities. This study used the SMMART analytic platform at OHSU KCI and incorporated comprehensive multi-omic analysis of serial liquid and tumor biopsies. Deep analysis of longitudinal biopsies combined with a robust computational biology pipeline identified multiple PARPi-induced changes in immune activation, DNA damage checkpoint activation, apoptosis and signaling pathways including RTK, PI3K-AKT and RAS-MAPK. These emergent tumor and immune state changes could act as biomarker targets to be used in selecting patient specific combination therapies.

  Study EGAS00001005479

• Transcriptomic data of a discordant monozygotic twin pair for ALS

  The dataset contains bulk RNAseq data of a discordant monozygotic twin pair for ALS; in particular the matrix with gene names and TPM counts for each sample. For both healthy and ALS twin, RNA sequencing was performed on RNA samples collected at two different time points (T1 and T2), for a total of seven samples. RNA extracted from PBMCs was used for library preparation according to Illumina TruSeq Stranded mRNA kit and processed on Illumina NextSeq 550 sequencer. Reads were aligned to the reference human genome GRCh38/hg38 and annotations were provided by the Ensembl v100 database.

  Dataset EGAD50000001330

• Genomics of Malignant Peripheral Nerve Sheath Tumor (MPNST)

  The Genomics of MPNST (GeM) Consortium dataset includes de-identified whole genome sequencing data (.bam) for germline samples (DNA primarily derived from blood) sequenced at standard (30x) coverage (n=88) and for tumor samples (DNA derived from fresh frozen tissue) sequenced at 90x coverage (n=105). This dataset also includes transcriptome profiling data (.fastq) for paired normal nerve samples (n=7) and for tumor samples (n=132).

  Dataset EGAD00001008608

• The immunological characterization of expanded tumor-infiltrating lymphocytes in renal cell carcinoma patients

  In this study, we comprehensively characterized the non-expanded and expanded tumor-infiltrating lymphocytes (TILs) from treatment-naïve RCC patients, as well as the corresponding “young” TILs (pre-REP TILs) and “rapidly expanded” TILs (REP TILs) following a clinical-grade TIL production protocol. From our scRNA+TCRαβ-seq and TCRβ-seq analyses, we show that the REP protocol preferentially favors the expansion CD4+ T-cells that originate from small T-cell clones in the tumor microenvironment (TME), indicating that the large, exhausted T-cell clones in the tumor do not expand during the protocol. We further identified RCC-associated TCR motifs that were validated in multiple TCRαβ-seq and scRNA+TCRαβ-seq datasets, as well as quantified the RCC-associated TCRs from the REP protocol. Overall, the T-cells carrying the RCC-associated TCRs remained high in the tumors and corresponding pre-REP TILs, but the frequency was reduced in the REP TILs. Furthermore, the overall anti-viral TCRs remained low throughout the REP protocol. Our results provide an in-depth understanding of the origin, phenotype, and specificity of the TCRs in RCC TILs.

  Study EGAS00001006952

• Single cell multi modal dataset of bone marrow samples from follicular lymphoma patients at diagnosis et one year post treatment

  This dataset contains transcriptome, BCR, TCR and HTO data at the single cell level from follicular lymphoma bone marrow samples at diagnosis (n=19) and one year post rituximab therapy (n=16).

  Dataset EGAD50000001843

• LongVar low-coverage data

  This dataset includes sequencing data from participants of the LongVar study. Specifically, it comprises low-coverage whole genome sequencing (WGS) data which was derived from cell-free DNA from blood samples. These data were generated to compare imputation accuracy. 133 individuals agreed to share their data, and are healthy volunteers.

  Dataset EGAD50000001607

• Melanoma transcriptomic data from patients undergoing immunotherapy

  This dataset contains raw RNA sequencing data from melanoma patient tumor samples collected before and during immunotherapy. The data support investigation of treatment-related changes in tumor cell populations. Samples were analyzed as part of a study exploring cellular responses to immune-based therapies.

  Dataset EGAD50000001569

• RNAseq dataset of ovarian cancer patients

  Dataset of transcriptomics data from a cohort of individuals diagnosed with ovarian cancer. This dataset includes RNAseq sequencing data from 68 individuals. A total of 109 tumor samples were sequenced. Samples were prepared with the Illumina TruSeq Stranded RNA library. Sequencing data are paired end.

  Dataset EGAD50000001556

• Genomic analyses (WES, RNAseq, scRNAseq and scTCRseq) of triple negative breast cancer evolution

  This study explores the evolution of tumor and blood immune microenvironment and related mechanisms that shape breast cancer progression.

  Dataset EGAD50000000117

• Single-cell TCR sequencing data of patients with T follicular helper cell lymphomas

  This dataset contains single-cell TCR sequencing data generated by the Cellranger pipeline (v3.1.0, 10X Genomics) from 9 LN and 16 PB samples of 14 patients with T follicular helper cell lymphomas (TFHLs) as well as 7 homeostatic LN (HLN) samples.

  Dataset EGAD50000000403

• Single-cell RNA sequencing data of patients with T follicular helper cell lymphomas

  This dataset contains single-cell count data generated by the Cellranger pipeline (v3.1.0, 10X Genomics) from 9 LN and 16 PB samples of 14 patients with T follicular helper cell lymphomas (TFHLs) as well as 7 homeostatic LN (HLN) samples.

  Dataset EGAD50000000402

• Single-cell BCR sequencing data of patients with T follicular helper cell lymphomas

  This dataset contains single-cell BCR sequencing data generated by the Cellranger pipeline (v3.1.0, 10X Genomics) from 5 LN and 1 PB samples of 5 patients with T follicular helper cell lymphomas (TFHLs) as well as 7 homeostatic LN (HLN) samples.

  Dataset EGAD50000000400

• WES and RNA-Seq of HCC biopsies and HCC derived Organoids

  We aimed to identify somatic mutations and transcriptional differences that could explain the resistance to Doxorubicin. This dataset includes RNA-Seq of HCC biopsies and Organoids and WES of Organoids.

  Dataset EGAD50000000060

• Illumina Infinium MethylationEPIC Array IDAT files generated from 11 glioma patient samples

  This dataset includes IDAT files from 6 IDH-mutant, 5 IDH-wild-type glioma patient samples of unmatched initial and recurrent timepoints profiled using the Illumina Infinium MethylationEPIC Array.

  Dataset EGAD00010002157

• A molecular atlas of the human postmenopausal fallopian tube and ovary from single-cell ATAC sequencing

  This datasets contains raw sequencing fastq data of14 samples from 5 donors of single cell ATAC using10x genome technology of human postmenopausal fallopian tube and ovary tissues.

  Dataset EGAD00001010077

• miRNA and mRNA transcriptome data

  This dataset contains 278 miRNA and 20 mRNA transcriptomes generated as part of the study "miR-374a-5p regulates inflammatory genes and monocyte function in inflammatory bowel disease."

  Dataset EGAD00001008683

• ChIPseq of neuroblastoma

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

  Dataset EGAD00001006557

• Whole genome sequence data from Illumina HiSeqX instruments

  This dataset includes bam files from 120 samples. These samples were sequenced using 2x150bp reads on an Illumina HiSeqX sequencer and aligned using the Isaac aligner. All samples were processed with TruSeq DNA PCR-free sample preparation.

  Dataset EGAD00001003562