11925 results for "cancer rna-seq"

in 21.95 milliseconds.

• Neoadjuvant_Breast_Cancer_Validations

  This study aims to re-sequence findings from whole genome studies using a bespoke pulldown method to validate mutations in those genomes sequenced.

  Study EGAS00001000428

• Targeted sequencing data of breast tumors with germline BRCA1/2 mutations

  This dataset contains targeted sequencing of breast tumors with germline BRCA1/2 mutations (n = 30) and those without. Breast cancer related genes (n = 115) have been captured and sequenced.

  Dataset EGAD00001005802

• Whole-exome sequencing (WES) data of papillary thyroid cancer and adjacent normal tissues

  High-coverage WES sequencing of DNA samples from 50 PTCs was performed on the Illumina HiSeq 2500 or 4000 System

  Dataset EGAD00001003262

• FFPE CPA Accreditation Study

  FFPE CPA accreditation of genome-scale sequencing in routinely collected formalin-fixed paraffin-embedded (FFPE) cancer specimens versus matched fresh-frozen samples using targeted pulldown capture prior to Illumina sequencing.

  Dataset EGAD00001000678

• Validation for human early embryonic substitutions (2017-05-11)

  PCR and MiSeq validation for early embryonic substitution candidates from 400 Breast cancer patients This dataset contains all the data available for this study on 2017-05-11.

  Dataset EGAD00001003332

• Dataset for synovial_sarcoma-WHOLE_GENOME

  Rare cancer sequencing data of 6 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008899

• 10x Genomics Single Cell Gene Expression for SA1035X8XB03425

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 8

  Dataset EGAD00001009148

• Single Cell Genome Sequence for DLP+ library A95632C

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA609 passage 6 on DLP+ library A95632C

  Dataset EGAD00001009322

• The University of Hong Kong Gastric Cancer XClone Study Single Cell CNV Data

  Single cell encapsulation and DNA libraries were prepared by Chromium™ Single Cell DNA Reagent Kits and Chromium™ Single Cell C and D Chip Kits.

  Dataset EGAD00001015383

• Exploring the extracellular transcriptome in seminal plasma for non-invasive prostate cancer diagnosis

  mRNA capture sequencing data of 57 seminal plasma samples.

  Dataset EGAD00001007688

• Single Cell Genome Sequence for DLP+ library A96141A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA604 passage 8 on DLP+ library A96141A

  Dataset EGAD00001009777

• 10x Genomics Single Cell Gene Expression for SA604X8XB02164

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA604 passage 8

  Dataset EGAD00001009118

• 10x Genomics Single Cell Gene Expression for SA1035X4XB02879

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 4

  Dataset EGAD00001009147

• Single Cell Genome Sequence for DLP+ library A95670A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA501 passage 5 on DLP+ library A95670A

  Dataset EGAD00001009448

• Mechanism of action and resistance to Trastuzumab Deruxtecan in patients with metastatic breast cancer: the DAISY trial

  198 exome sequencing samples

  Dataset EGAD00001009853

• High-resolution analysis for urinary DNA jagged ends

  consists 17 cases, 7 control cases and 10 cancer cases.

  Dataset EGAD00001008594

• Single Cell Genome Sequence for DLP+ library A95628A

  Single Cell Genome Sequence for triple negative breast cancer patient SA1162SB on DLP+ library A95628A

  Dataset EGAD00001009319

• Sequencing data for the manuscript "Early on-treatment changes in circulating tumor DNA fraction and response to enzalutamide or abiraterone in metastatic castration-resistant prostate cancer"

  This submission contains gzipped fastq files from paired-end targeted sequencing.

  Dataset EGAD00001010105

• Genome and transcriptome sequence data from a diffuse aarge B-cell lymphoma (relapse) tumor patient

  Genome and transcriptome sequence data from a diffuse large B-cell lymphoma (relapse) patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015308

• Genome and transcriptome sequence data from a relapsed blastic plasmacytoid dendritic cell neoplasm tumor patient

  Genome and transcriptome sequence data from a relapsed blastic plasmacytoid dendritic cell neoplasm patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015312

• Genome and transcriptome sequence data from a metastatic malignant peripheral nerve sheath tumor tumor patient

  Genome and transcriptome sequence data from a metastatic malignant peripheral nerve sheath tumor patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015322

• Genome and transcriptome sequence data from a CNS non-germinoma germ cell tumour tumor patient

  Genome and transcriptome sequence data from a CNS non-germinoma germ cell tumour patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015327

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 9 part 1)

  Whole genome sequencing data of 6 high-grade serous carcinoma (HGSC) patients (11 samples) sequenced with MGISEQ-2000

  Dataset EGAD00001011353

• sWGS for genome-wide copy number profiling

  Shallow whole-genome sequencing (sWGS) data for the identification of somatic copy number alterations (SCNA) and the estimation of tumor fractions in plasma DNA of metastatic colorectal cancer patients (mCRC).

  Dataset EGAD00001006384

• Lipomatous tumors with 12q amplification

  The project concerns whole genome sequencing (short-read and long-read) and RNA-sequencing of lipomatous tumors with 12q-amplification. A subset of lipomatous tumors is driven by amplification of genes mapping to chromosome arm 12q, including the MDM2 gene. The goals of the study were to compare expression levels of genes mapping to 12q in tumors with amplification in rod-shaped or circularized chromosomes as well as to assess and compare the structural variants in those tumors. In total, 20 samples were analyzed, and the data were correlated with genomic data on bulk and single cell DNA from the same tumors. The fastq files from the tumors were uploaded to EGA.

  Dataset EGAD50000000087

• T cell and Antibody Responses in Rituximab-Treated Lymphoma Patients After SARS-CoV-2 Vaccination

  This dataset contains T cell receptor (TCR) sequencing data from 51 RNA samples, each processed into three independent libraries (tot 153 FASTQ files). Sequencing was performed on an Illumina NextSeq 500 platform using the NextSeq 500/550 Mid Output Kit v2.5 (300 Cycles), generating paired-end FASTQ files with dual 10 bp barcodes and 5% PhiX as internal control. Libraries were quantified with the Qubit HS dsDNA kit and assessed for fragment size distribution using the Agilent Tapestation D1000 system before isochoric pooling to 4 nM and sequencing in two independent runs. The resulting dataset enables analysis of TCR β-chain CDR3 sequences for clonal expansion and diversity studies.

  Dataset EGAD50000001714

• Determining off-target effects of splice-switching antisense oligonucleotides using short read RNAseq in neuronally differentiated human induced pluripotent stem cells

  Neuronal cells derived from female healthy control hiPSC lines LUMCi003-A, LUMCi003-B and LUMCi023-A were transfected with in total four different splice-switching AONs targeting three different human transcripts. Untransfected samples as well as samples transfected with a scrambled AON were included as controls. Three days after transfection, RNA was isolated for sequencing using Illumina Novaseq6000 in order to perform differential gene expression analysis and differential splicing analysis to determine off-target effects. Sequencing was performed in two batches: one containing the samples from cell line LUMCi003-A and the other containing cell lines LUMCi003-B and LUMCi023-A.

  Dataset EGAD50000001742

• T-VEC CBCL scRNA

  We are presenting raw and processed data of our study where we analyze fine-needle aspirate (FNA) samples of primary cutaneous B-cell lymphoma patients undergoing oncolytic virotherapy (https://clinicaltrials.gov/ct2/show/NCT03458117). We are uploading single cell RNA-sequencing and immune repertoire profiling data of 29 FNA samples from four pCBCL patients. The four patients have three different subtypes of primary cutaneous B-cell lymphoma: pCDLBCL-LT, pCFCL and pCMZL. The samples are taken at different time points following T-VEC injection (from baseline up to 91 days after injection). We are uploading the sequences in BAM format and the outputs of the cellranger pipeline (count matrices and filtered VDJ contigs) in CSV format.

  Dataset EGAD00001006829

• Massive parallel RNA sequencing of highly purified mesenchymal cells derived from bone marrow specimens of 3 Diamond-Blackfan anemia cases

  Highly purified mesenchymal cells (CD45-/7AAD-/CD235a-/CD31-/CD271+/CD105+) were prospectively FACS-isolated from bone marrow specimens of 3 Diamond-Blackfan anemia (DBA) cases. This data set, comprising 3 DBA cases, is used as complement to 45 low-risk myelodysplastic syndrome (LRMDS) and 4 Shwachman-Diamond syndrome (SDS) cases to demonstrate aberrant inflammatory signaling as a common mechanism in pre-leukemia syndromes to induce genotoxic stress in hematopoietic stem cells. In addition, this data set is used to determine different overlapping gene expression signatures in pre-leukemia syndromes compared to gene expression profiles of highly purified mesenchymal cells of healthy donors.

  Dataset EGAD00001002661

• Massive parallel RNA sequencing of highly purified mesenchymal cells derived from bone marrow specimens of 4 Shwachman-Diamond syndrome cases

  Highly purified mesenchymal cells (CD45-/7AAD-/CD235a-/CD31-/CD271+/CD105+) were prospectively FACS-isolated from bone marrow specimens of 4 Shwachman-Diamond syndrome (SDS) cases. This data set, comprising 4 SDS cases, is used as complement to 45 low-risk myelodysplastic syndrome (LRMDS) and 3 Diamond-Blackfan anemia (DBA) cases to demonstrate aberrant inflammatory signaling as a common mechanism in pre-leukemia syndromes to induce genotoxic stress in hematopoietic stem cells. In addition this data set is used to determine different overlapping gene expression signatures in pre-leukemia syndromes compared to gene expression profiles of highly purified mesenchymal cells of healthy donors.

  Dataset EGAD00001002660

• Target-capture sequencing of FFPE tumor samples from patients diagnosed with NKTL

  211 NKTL FFPE specimens were screened for somatic mutations using deep targeted capture sequencing. FFPE rolls or slides were extracted using QIAamp DNA FFPE Tissue kit (QIAGEN). The FFPE genomic DNA was treated with NEBNext FFPE DNA Repair Mix and assessed by Quant-it PicoGreen dsDNA Assay Kit (Invitrogen). The library was generated from 10-200 ng DNA with SureSelectXT Low Input Target Enrichment System for Illumina Paired-End Sequencing Library (Agilent Technologies) according to manufacturer’s instructions. RNA based probe was designed with SureDesign (Agilent Technologies) to target-capture 140 genes. Next, the captured libraries were pooled in equimolar concentration and sequenced on Illumina Novaseq 6000 platform with SP or S1 chip.

  Dataset EGAD00001005303

• MPM cell lines

  RNA-sequencing data for 12 MPM cell lines treated with 0.1% DMSO or 1 µM palbociclib for 9-10 days. Experiment was performed in duplicates for sensitive cells (MPM08, MPM21, MPM38, MPM57, MPM59, Meso11, Meso13, Meso34 and Meso56) and only once for resistant cells (MPM31, MPM34 and MPM36) except for Meso11 which was done in triplicates. For Meso11, Meso13, Meso34 and Meso56, a drug washout of 48 hours was also performed. 4 MPM cell lines (MPM31, MPM34, MPM59 and MPM66) were also analyzed in untreated condition. 2 FASTQ files for each sample (n=56) (paired)

  Dataset EGAD00001008741

• Genomic and immune signatures predict clinical outcome in newly diagnosed multiple myeloma treated with immunotherapy regimens

  In this study we performed whole genome sequencing on matched tumor-normal CD138+ bone marrow mononuclear cells from 60 patients with newly diagnosed multiple myeloma treated with daratumumab, carfilzomib, lenalidomide, and dexamethasone (NCT03290950-MANHATTAN trial). In addition, we performed 5’-single-cell RNA-sequencing (10X Genomics) coupled with V(D)J sequencing and capture of the surface protein markers (TotalSeq-C, Biolegend) of the CD138- bone marrow mononuclear cells to interrogate the composition of the immune microenvironment at baseline and after eight cycles of induction therapy in 22 patients with newly diagnosed multiple myeloma. Samples were multiplexed using hashtag oligo.

  Dataset EGAD00001011132

• Dataset for soft_tissue_tumor-RNA

  Rare cancer sequencing data of 243 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008859

• Genome-Wide Predictors of Treatment-Related Toxicities in SWOG S0221 Trial

  When undergoing treatment for breast cancer, many women experience severe side effects, some of which result in treatment-related death and some that can persist for years. Little is understood regarding factors that may predict drug toxicities. Pharmacogenetics, the investigation of variants in candidate genes in drug metabolism pathways, has been used to determine susceptibility to treatment-related toxicities, as well as to cancer recurrence. Although there have been some strong and important findings using this approach, such as identification of single nucleotide polymorphisms (SNPs) that predispose to side effects associated with thiopurines and irinotecan, there has been less progress in assessment of genetic variants that predispose to toxicities resulting from the multi-drug regimen commonly used to treat breast cancer, anthracyclines (A), cyclophosphamide (C), and taxanes (T). These difficulties in identification of key gene variants may be due to the complex metabolic pathways of these drugs, the lack of rate limiting enzymes in the processes, or the limitations of single SNP analysis, rather than capturing all of the variability across the genes. In addition to drug metabolism pathways, however, there may be a number of constitutional factors or other processes that affect damage to normal tissues in the course of chemotherapy, some known or hypothesized, such as DNA repair and oxidative stress pathways, and others not yet discovered. However, there have been no clear candidate genes that account for a large part of the variation in drug or treatment response, and there are likely important genes that influence sensitivity of cells to chemotherapy through unknown pathways which have not yet been identified or hypothesized. The present technological capabilities to screen the entire genome for variants that discriminate populations allows the opportunity to identify these as yet unknown pathways, and open the doors to exciting new avenues of research into mechanisms that had not been previously considered. We conducted a genome-wide scan (GWAS) in a clinical trial (S0221), in which women with high risk breast cancer were treated with different dosing schedules of C, A and T. Blood specimens were collected and banked, and DNA extracted for genotyping on the Illumina OMNI 1M platform. The GWAS data were used to examine genetic variants significantly associated with grades 3 and 4 toxicities, including peripheral neuropathy recorded during the T segment. In S0221, toxicities were graded according to the NCI Common Toxicity Criteria for Adverse Events (CTCAE). The neurotoxicity is predominantly a distal sensory neuropathy, which is characterized by pain, numbness, tingling, and reduced functional capacity in the extremities. Other symptoms include parasthesias, ataxia, impaired vibration and joint position sense, and loss of tendon reflexes. By using a GWAS approach, it is likely that important pathways not previously considered can be revealed as important in susceptibility to treatment-related toxicities, identifying those at greatest risk for alternate drugs or dose reduction, and opening new areas of research for prevention of taxanes-related neuropathy among patients receiving chemotherapy for breast cancer.

  Study phs001428

• National Cancer Institute (NCI) Genome-Wide Association Study (GWAS) of Renal Cell Carcinoma in African Americans

  The NCI GWAS of renal cell carcinoma (RCC) in African Americans was undertaken to provide insight into genetic loci affecting susceptibility to this malignancy in a racial group known to be at elevated risk. We genotyped 1,136,723 single-nucleotide polymorphisms (SNPs) among 255 cases and 375 controls of African ancestry from the NCI Kidney Cancer Study, and further investigated 16 SNPs in a replication set consisting of 140 cases and 543 controls from a case-control study conducted at the University of Texas MD Anderson Cancer Center. The variant rs10771279 located on 12p11, 77kb from a European-ancestry RCC risk marker, was associated with RCC risk in the GWAS (P=1.2 x 10-7) but did not replicate (P=0.99). The variant 7105934 on 11q13.3, previously associated with RCC in a GWAS using European-ancestry samples, was associated with risk in both studies [meta-analysis odds ratio (OR)=0.76, 95% confidence interval (CI)=0.64-0.91; P=0.0022]. The frequency of this allele was higher than that observed in the European-ancestry GWAS (0.56 and 0.07 respectively among controls). The rs7105934 association was stronger for clear cell RCC (ccRCC: OR=0.56; P=7.4 x 10-7) and absent for cases of other or unknown histology (OR=1.02; P=0.86). In conclusion, this study provides evidence that rs7105934 is a susceptibility locus for RCC, and clear-cell RCC in particular, among African Americans.

  Study phs000863

• Systematic Growth Factor Profiling Platform for 3D Tumor Models Reveals EstradiolResponsive Cellular Mechanisms of Immunotherapy Resistance

  Epithelial ovarian cancer (EOC) exhibits significant molecular heterogeneity, which is thought to be influenced by the tumor microenvironment (TME). However, the specific factors driving this heterogeneity remain poorly understood. In this study, we integrated growth factoromics and genomic data to identify TME factors contributing to EOC heterogeneity and immunosuppression. Our analysis revealed distinct subgroups of EOC samples with differential responsiveness to specific growth factors, particularly estradiol and R-spondin. Notably, samples with high responsiveness to estradiol and Wnt (C1 cluster) were enriched in the Mesenchymal (MES) molecular subtype, while samples with high responsiveness to R-spondin (C2 cluster) were associated with the Differentiated (DIF) and Immunoreactive (IMR) subtypes. We discovered that the G protein-coupled estrogen receptor (GPER), rather than the classical estrogen receptor alpha (ERα), was the key mediator of estrogen responsiveness and a determinant of molecular subtype classification. Single-cell sequencing analysis identified subsets of estrogen-responsive malignant cell (MAL.PDCD5) and cancer-associated fibroblast (FB.TNFSF10), which were associated with immunosuppressive patterns in the TCGA cohort. Importantly, the interaction between these cell populations significantly increased upon estrogen treatment, suggesting a potential mechanism by which estrogen signaling may contribute to the development of an immunosuppressive TME. Our findings highlight the critical role of estrogen signaling in shaping the molecular heterogeneity and immunosuppressive TME of EOC and provide novel insights into potential therapeutic targets for overcoming immunosuppression in this malignancy.

  Study EGAS50000000422

• The evolutionary history of human colitis-associated colorectal cancer

  Inflammatory bowel disease confers an increased lifetime risk of developing colorectal cancer (CRC), and colitis-associated CRC (CA-CRC) is molecularly distinct from sporadic CRC (S-CRC). Here we have dissected the evolutionary history of CA-CRC using multi-region sequencing. Exome sequencing was performed on fresh-frozen multiple regions of carcinoma, adjacent non-cancerous mucosa and blood from 12 CA-CRC patients (n=55 exomes), and key variants were validated with orthogonal methods. Genome-wide copy number profiling was performed using SNP arrays and low-pass whole genome sequencing on archival non-dysplastic mucosa (n=9), low-grade dysplasia (LGD, n=30), high-grade dysplasia (HGD, n=13), mixed LGD/HGD (n=7) and CA-CRC (n=19). Phylogenetic trees were reconstructed, and evolutionary analysis used to reveal the temporal sequence of events leading to CA-CRC. 10/12 tumors were microsatellite stable with a median mutation burden of 3.0 single nucleotide alterations (SNAs) per Mb, around 20% higher than S-CRC (2.5 SNAs/Mb), and consistent with elevated aging-associated mutational processes. Non-dysplastic mucosa had considerable mutation burden (median 47 SNAs), including mutations shared with the neighboring CA-CRC, indicating a pre-cancer mutational field. CA-CRCs were often near-triploid (42%) or near-tetraploid (21%) and phylogenetic analysis revealed that copy number alterations (CNAs) began to accrue in non-dysplastic bowel, but the LGD/HGD transition often involved a punctuated catastrophic CNA increase.

  Study EGAS00001003028

• Bioinformatic Methods and Bridging of Assay Results for Reliable Tumor Mutational Burden Assessment in Non-Small Cell Lung Cancer

  Tumor mutational burden (TMB) has emerged as a predictive biomarker of response to immune checkpoint inhibitors. Standardization of TMB measurement is essential for implementing diagnostic tools to guide treatment. Here we evaluate bioinformatic TMB analysis by whole exome sequencing (WES) in formalin-fixed, paraffin-embedded samples. In CheckMate 026, TMB was retrospectively assessed in 312 patients with non-small cell lung cancer (58% of the intent-to-treat population) who received first-line nivolumab treatment or chemotherapy. We examined the sensitivity of TMB assessment to bioinformatic filtering methods and assessed concordance between TMB data derived by WES and the FoundationOne CDx™ assay. TMB scores comprising synonymous, indel, frameshift, and nonsense mutations (all mutations) were 3.1-fold higher than data including missense mutations only, but values were highly correlated (Spearman’s r = 0.99). Scores from CheckMate 026 samples including missense mutations only were similar to those generated from data in The Cancer Genome Atlas, but those including all mutations were generally higher. Using databases for germline subtraction (instead of matched controls) showed a trend for race-dependent increases in TMB scores. Parameter variation can therefore impact TMB calculations, highlighting the need for standardization. Encouragingly, WES and FoundationOne CDx outputs were highly correlated (Spearman’s r = 0.90) and differences could be accounted for by empirical calibration, suggesting that reliable TMB assessment across assays, platforms and centers is achievable.

  Study EGAS00001003661

• Conserved features of TERT promoter duplications reveal an activation mechanism that mimics hotspot mutations in cancer

  Mutations in the TERT promoter are the single most common non-coding mutation in cancer and represent the genetic underpinnings of tumor cell immortality. Beyond the two most common point mutations, G228A and G250A, which selectively recruit the ETS factor GABP to activate TERT, the significance of other variants in the TERT promoter are unknown. We identified duplications of wildtype sequence within the core promoter region of TERT in 7 different cancer types that have strikingly similar features including size, insertion position, and inclusion of one of the native ETS motifs. Each duplication activates the TERT promoter to a similar level as G228A and G250A and is critically dependent on the insertion site. The GABP tetramer binds to the TERT duplicated promoter sequence by virtue of the native ETS motif and its duplicated version with precise spacing, and it is necessary for the transcriptional activation by all duplications tested. Spatiotemporal analysis in a multifocal glioblastoma shows the duplication is clonal and its activation of TERT is readily detectable at the single cell level and in bulk tumor tissue. We conclude that recurrent TERT promoter duplications of the native ETS sequence are functionally and mechanistically equivalent to the hotspot mutations that confer tumor cell immortality. The shared mechanism of these divergent somatic genetic alterations suggests a strong selective pressure for recruitment of the GABP tetramer to activate TERT.

  Study EGAS00001006118

• Genome-wide association study identifies common variants associated with breast cancer in South African Black women

  Genome-wide association studies (GWAS) have characterized the contribution of common variants to the development of breast cancer (BC) in populations of European descent, however no GWAS have been reported in resident African populations. This GWAS included 2,485 resident African BC cases and 1,101 population matched controls. Two risk loci were identified, one on chromosome 15, located between UNC13C and RAB27A (rs7181788, p = 1.01x10-08) and a second in an intron of USP22 on chromosome 17 (rs899342, p = 4.62x10-08). RAB27A is a member of the RAS oncogene family associated with invasive growth and metastasis, and UNC13C is involved in tumor progression. The rs899342 SNP is an eQTL for expression of USP22 in a wide range of tissues. Several genome-wide significant signals were detected in a hormone receptor subtype analysis. Comparison of a meta-analysis of other African ancestry BC GWAS datasets predominantly of West African ancestry with our South African data showed limited evidence of shared risk loci, suggesting potential heterogeneity in genetic risk factors for breast cancer in different African populations. A European ancestry derived polygenic risk model for BC was applied to our data, explaining only 0.79% of variance, with an area under the curve of 0.56. This study identified genetic risk factors for BC in a resident African population, but larger studies in this and other African populations are needed to further define the contribution of common variants to BC risk.

  Study EGAS00001008032

• COIN_CRC_GWAS

  Genotype data of 1,950 individuals from the COIN and COIN-B trials of advanced/metastatic colorectal cancer. Data provided in plink format, and has been quality controlled. Control data used was from the WTCCC2 project National Blood Donors (NBS) Cohort (EGAD00000000024).

  Dataset EGAD00010002186

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 10)

  Whole genome sequencing data of 56 high-grade serous carcinoma (HGSC) patients (208 samples) sequenced with Novoseq 6000

  Dataset EGAD50000000275

• Multiple Myeloma GWAS Meta-analysis

  Meta-analysis of Multiple Myeloma genome-wide association study datasets. Included are meta-analyses with and without the UK Biobank dataset.

  Study EGAS50000000292

• Nanopore whole-genome sequencing of human sarcomas

  We performed single and multi-region nanopore whole-genome sequencing on human sarcoma samples from adult and paediatric patients.

  Study EGAS50000000651

• Shallow dataset

  Associated with Molecular biomarkers in progression from refractory celiac disease to the lethal cancer variety enteropathy associated T cell lymphoma (EATL) Study. shallow Whole Genome Sequencing (sWGS) of 63 samples. sWGS was done to analyze copy number aberration.

  Dataset EGAD50000001165

• DNA sequencing of sgRNAs enriched from the CRISPR-Cas9 screened HCC organoids

  Project aims to find enriched or depleted sgRNAs to identify functional genes in HCC progression and lenvatinib resistance

  Study EGAS50000000848

• Single-cell Transcriptome Profiling of Treatment-naïve and Post-treatment Colorectal Cancer: Insights into Putative Mechanisms of Chemoresistance

  These terms and conditions govern access to the managed access datasets to which the User Institution has requested access. The User Institution agrees to be bound by these terms and conditions.

  Dac EGAC50000000482

• Whole genome sequencing of osteosarcoma from patients seen at UT MD Anderson Cancer Center.

  Whole genome sequencing of 35 osteosarcoma patients (primary, relapsed, and metastatic) with matched normals. Tumors were sequenced at target 60X and matched normals at target 30X.

  Dataset EGAD00001005389

• Lowpass whole genome sequencing of single circulating tumor cells (CTCs) in ALK-rearranged non-small-cell lung cancer resistant to ALK inhibitors

  Lowpass whole genome sequencing of 43 single CTCs and one tumor biopsy

  Dataset EGAD00001007700