14989 results for "cancer studies using rna-seq"

in 24.78 milliseconds.

• Cross-species genomics identifies TAF12, NFYC and RAD54L as novel choroid plexus carcinoma oncogenes

  Choroid plexus carcinomas (CPC) are poorly understood and frequently lethal brain tumors with minimal treatment options. Using a new mouse model of the disease and a large cohort of human CPCs, we performed a cross-species, genome-wide search for novel oncogenes within syntenic regions of chromosome gain. TAF12, NFYC and RAD54L, co-located on human chromosome 1p32-35.3 and mouse chromosome 4qD1-D3, were identified as oncogenes that are gained in tumors in both species and required to initiate and progress the disease in mice. TAF12 and NFYC are transcription factors that regulate the epigenome, while RAD54L plays a central role in DNA repair. Our data identify a group of concurrently gained, novel oncogenes that cooperate in the formation of CPC and unmask potential new avenues for therapy.

  Study EGAS00001000961

• ICGC PedBrain: Deep-sequencing of childhood brain tumors.

  Brain tumors constitute the childhood tumors with the highest mortality rates and survival is often associated with severe long-term sequelae due to intensive multimodal treatment regimens. Thus, the PedBrainTumor network aims at the identification of robust biomarkers for clinical management and novel molecular targets for therapeutic interventions. Using massively parallel whole-genome sequencing, and transcriptome and methylome sequencing for subsets of cases, we aim to decipher the molecular causes of medulloblastoma as well as low-grade astrocytoma, and to identify markers to stratify patients for specialized treatment. As the PedBrain network is affiliated with clinical trials in medulloblastoma and pilocytic astrocytoma, validation cohorts for the translation of key findings into clinical settings are readily available.

  Study EGAS00001000215

• Relaxed selection during a recent human expansion

  To better understand and quantify the effect of a recent expansion process on the amount and pattern of mutation load, we screened the ascending genealogies of 3916 individuals from the CARTaGENE cohort (Awadalla et al. 2013) that were linked to the BALSAC genealogical database (http://balsac.uqac.ca/). Using stringent criteria on the quality of genealogical information, we selected (front) individuals whose ancestors were as close as possible to the front of the colonization of Quebec, and (core) individuals whose ancestors were as far as possible from the front. We then sequenced these 102 individuals at very high coverage (mean 89.5X, range 67X-128X) for 106.5 Mb of exomic and UTR regions and contrasted their genomic diversity to detect if sites with various degrees of conservation and deleteriousness had been differentially impacted by selection.

  Study EGAS00001001957

• Mullighan - PAX5-driven Subtypes

  Using integrated genomic analysis of 1.988 childhood and adult cases, we describe a revised taxonomy of B-cell acute lymphoblastic leukemia, which incorporates 23 subtypes defined by chromosomal rearrangements, sequence mutations, or heterogeneous genomic alterations. Two subtypes have frequent alterations of the B lymphoid transcription factor gene PAX5. One, PAX5alt, has diverse PAX5 alterations, and a second subtype is defined by a single mutation, PAX5 P80R. We show that P80R impairs B lymphoid development and promotes the development of B-ALL in vivo. These results demonstrate the utility of transcriptome sequencing to classify B-ALL and reinforce the central role of PAX5 as a checkpoint in B lymphoid maturation and leukemogenesis.

  Study EGAS00001003266

• Single cell whole genome sequencing of high hyperdiploid acute lymphoblastic leukemia

  This dataset was collected from viable bone marrow cells obtained at diagnosis from nine patients with high hyperdiploid ALL and one normal bone marrow sample. All samples were subjected to low pass single cell whole genome sequencing with the median sequencing coverage of 0.02x. Single nuclei in G0/G1 phase were isolated using a fluorescence-activated cell sorting (FACS) cytometer. DNA libraries were constructed and associated next-generation sequencing was carried out by European Research Institute for the Biology of Ageing (ERIBA), University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. Further details regarding the DNA libraries construction are available by Bos et. al., 2019 (https://link.springer.com/protocol/10.1007/978-1-4939-8931-7_15). The dataset has been used for copy number aberrations analysis.

  Study EGAS00001006347

• Evolutionary landscape of clonal hematopoiesis in 3359 individuals from the general population

  This project contains longitudinal data for processed somatic variant calls and data on core phenotypic variables for 3359 community-based individuals ≥60 years, a sub-cohort of the population-based Lifelines cohort (167,729 participants). Cases with peripheral blood count abnormalities and population-based controls were included. Next-generation sequencing data were generated with a median time period of 43 months between baseline and follow-up visit. For 327 individuals a third visit sample was included. Error-corrected sequencing was performed using single-molecule tagged molecular inversion probes targeting 27 myeloid and lymphoid driver genes. The threshold for variant calling was set at ≥1% VAF and ≥10 consensus variant reads. Details on sample selection, sequencing technique, variant calling procedures and data curation are described (van Zeventer et al. 2023).

  Study EGAS00001007087

• Genomic Landscape and Clonal Architecture in Pediatric Myeloid Neoplasms with Chromosome 7 Deletions

  Full and partial loss of chromosome 7 (del7, 7q-) are prevalent cytogenetic abnormalities in pediatric myeloid neoplasms resulting in haploinsufficiency of key hematopoietic regulators on chromosome 7. While the genomic landscape of myeloid neoplasms in adults with del7 and 7q- has been described, pediatric patients with similar chromosome 7 losses have not been compiled into a single, comprehensive study utilizing modern sequencing strategies. To this end, we assembled a cohort of 108 pediatric and young adult patients representing a mixture of diagnoses. Using WGS, WES, and RNAseq, we compared the co-occurring mutations and gene expression levels in our cohort to those found in pediatric and young adult patients with two intact copies of chromosome 7. We also performed single-cell multi-omics on a subset of eight samples.

  Study EGAS00001008055

• Genome-wide associations of human gut microbiota variation and implications for causal inference analyses

  Here we use appropriate taxon-specific models along with support from independent cohorts to show association between human host genotype and gut microbiome variation. Using fecal derived 16S rRNA gene sequences and host genotype data from the Flemish Gut Flora Project (FGFP) we identify genetic associations involving multiple microbial traits. Mendelian randomization analysis was able to estimate associations between microbial traits and disease, however in the absence of clear microbiome driven effects, caution is needed in interpretation. This work marks a growing catalog of genetic associations which will provide insight into the contribution of host genotype to gut microbiome. Despite this, the uncertain origin of association signals will likely complicate future work looking to dissect function or use associations for causal inference analysis.

  Study EGAS00001004420

• Institut Curie Neuroblastoma Whole Genome Sequencing Diagnosis Relapse

  Neuroblastoma, a clinically heterogeneous pediatric cancer, is characterized by distinct genomic profiles but few recurrent mutations. As neuroblastoma is expected to have high degree of genetic heterogeneity, study of neuroblastoma's clonal evolution with deep coverage whole-genome sequencing of diagnosis and relapse samples will lead to a better understanding of the molecular events associated with relapse. Samples were included in this study if sufficient DNA from constitutional, diagnosis and relapse tumors was available for WGS. Whole genome sequencing was performed on trios (constitutional, diagnose and relapse DNA) from eight patients using Illumina Hi-seq2500 leading to paired-ends (PE) 90x90 for 6 of them and 100x100 for two. Expected coverage for sample NB0175 100x100bp was 30X for tumor and constitutional samples. For the seven other patients expected coverage was 80X for tumor samples with PE 100x100, 100X in the other tumor samples and 50X for all constitutional samples (see table 1). Following alignment with BWA (Li et al., Oxford J, 2009 Jul) allowing up to 4% of mismatches, bam files were cleaned up according to the Genome Analysis Toolkit (GATK) recommendations (Van der Auwera et al., Current Protocols in Bioinformatics, 2013, picard-1.45, GenomeAnalysisTK-2.2-16). Variant calling was performed in parallel using 3 variant callers: GenomeAnalysisTK-2.2-16, Samtools-0.1.18 and MuTect-1.1.4 (McKenna et al., Genome Res, 2010; Li et al., Oxford J, 2009 Aug; Cibulskis et al., Nature, 2013). Annovar-v2012-10-23 with cosmic-v64 and dbsnp-v137 were used for the annotation and RefSeq for the structural annotation. For GATK and Samtools, single nucleotide variants (SNVs) with a quality under 30, a depth of coverage under 6 or with less than 2 reads supporting the variant were filter out. MuTect with parameters following GATK and Samtools thresholds have been used to filter our irrelevant variants. .SNVs within and around exons of coding genes overlapping splice sites.. Then,variants reported in more than 1% of the population in the 1000 genomes (1000gAprl_2012) or Exome Sequencing Project (ESP6500) have been discarded in order to filter polymorphisms. Finally, synonymous variants were filtered out. MuTect focuses on somatic by filtering with constitutional sample. Mpileup comparison between constitutional and somatic DNAs allowed us to focus also on tumor specific SNVs with GATK and Samtools. Finally, every SNV called by our pipeline and also supported in any constitutional samples were filtered our in order to prevent putative constitutional DNA coverage deficiency. Then we analyzed CNVs (copy number variants) with HMMcopy-v0.1.1 (Gavin et al., Genome Res, 2012) and control-FREEC-v6.7 (Boeva et al., Bioinformatics 2011) with a respective window of 2000bp and 1000 bp, and auto-correction of normal contamination of tumor samples for Control-FREEC. Finally we explored Structural variants (SVs) including deletions, inversions, tandem duplications and translocations using DELLY-v0.5.5 with standard parameters (Rausch et al., Oxford J, 2012). In tumors, at least 10 supporting reads were required to make a call and 5 supporting reads for the sample NB0175 with a coverage of only 40X (see table 2). To predict SVs in constitutional samples for subsequent somatic filtering, only 2 supporting reads were required in order not to miss one. To identify somatic events, all the SVs in each normal sample were first flanked by 500 bp in both directions and any SVs called in a tumor sample which was in the combined flanked regions of respective normal sample was removed (see graph 1). Deletions with more than 5 genes impacted or larger than 1Mb and inversions or tandem duplications covering more than 4 genes, were removed. We focused on exonic and splicing events for deletions, inversions, and tandem duplications. For translocation, we keep all SVs that occurred in intronic, exonic, 5'UTR, upstream or splicing regions. Bioinformatics detection of variations with Deep sequencing approach Once PE reads merged and adaptors trimmed by SeqPrep with default parameters, merged reads were aligned via the BWA (Li H. and Durbin R. 2009 PMID 19451168) allowing up to 1 differences in the 22-base-long seeds and reporting only unique alignments. Only reads having a mapping quality 20 or more have been further analysed. Variant calling software was not used, since we aimed to predict variations at low frequencies, observed in less than 1% of reads. Such variants require a custom approach. Using DepthOfCoverage functions of the Genome Analysis Toolkit (GATK) v2.13.2 (McKenna A, et al., 2010 Genome Research PMID: 20644199), we focused on high quality coverage of bases A, C, G and T at the targeted variant position. Depth of coverage of each base following a mapping quality higher than 20 and a base quality higher than 10 have been taken into account in order to focus only on high quality data. Aiming to determine the background level of variability at the studied regions, 10 control samples were included in the analysis. The same approach and filtering criteria have been applied as introduced above over the entire amplicons. In order to highlight variants, for each sample the frequencies of each bases at each amplicon position were then compared to those observed in the set of controls. Statistical analyses were performed with the R statistical software (http://www.R-project.org). Fisher’s exact two-sided tests with a Bonferroni correction were performed to compare percentages of bases between the data sets, i.e. for a given base between a case and the controls. Finally, significant variations were filtered-in once (i) a significant increase in the percentage of avariant base and (ii) a significant decrease in the percentage of it's reference base following our p.values criteria was observed (p.val < 0.05).

  Dataset EGAD00001001356

• SCAT_Osteosarcoma_Validation

  This experiment is to validate putative somatic substitutions and indels identified in an exome screen of ~50 osteosarcoma tumour/normal pairs. It is the first stage in our ICGC commitment to study osteosarcoma. The validation process is an important component of our analysis to clarify the data prior to looking for evidence of new cancer genes, or subverted pathways important in the development of cancer. 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 EGAD00001000280

• Exploiting evolutionary steering in cancer therapy

  This dataset contains 9 bam files of exome sequencing for an experiment of evolved resistance. Here a barcoded cell line (HCC827 - POT) has been treated under high concentrations of gefitinib (GEF) and trametinib (TRM) until resistance has evolved, as well as under control conditions (DMSO). The dataset contains exome sequencing of confluent cells for three replicates for each anti-cancer drug as well as two replicates of growth under DMSO conditions. The original barcoded cell line (POT) was also exome sequenced and is included in the cohort. Sequencing was performed on the Illumina NovaSeq platform.

  Dataset EGAD00001005782

• Targeted sequencing (paired) of HR genes in primary and metastatic patient-derived xenografts (PDXs) of colorectal cancer (CRC)

  The dataset includes DNA targeted paired-wise (2 FASTQ per sample) sequencing of a manually curated panel of 44 genes with a documented role in homologous recombination (HR), a pathway of DNA damage response. Sequencing was conducted in 69 tumors from patients with metastatic colorectal cancer after serial passaging in mice (patient-derived xenografts, PDXs). For each PDX model profiled for HR gene mutations, therapeutic annotation of response to FOLFIRI (a chemotherapeutic regimen consisting of the combination of 5-fluorouracil and irinotecan) is available.

  Dataset EGAD50000000107

• Neversmoker lung adenocarcinoma

  Non-small cell lung cancer whole genome sequencing We performed whole genome sequencing of Korean never-smoker lung adenocarcinoma patients to discover novel pathway except EGFR and ALK patients. We identified estrogen signaling as a novel enriched signaling. Lastly we validated the elevated estrogen signaling through immunohistochemistry experiment in some patients which increased signaling.

  Study EGAS50000000232

• Analysis of Cell-Free DNA to Predict Outcome to Bevacizumab Combination Therapy in Metastatic Colorectal Cancer Patients

  This dataset includes FASTQ files of low coverage whole genome sequencing of normal tissue (n = 8), tumor tissue (n = 55) and cell free DNA from plasma samples (n=101) from patients with metastatic colorectal cancer treated with bevacizumab. A total of 164 samples are present from two different cohorts. The first batch of samples (n = 139, sample names sAPD302T until sAPD502_P0) were collected from the AC-Angiopredict Phase 2 trial (NCT01822444), the second batch of samples (n = 25m, sample names sAPD503_P0 until sAPD527_P0) were collected from the UMM cohort.

  Dataset EGAD50000000176

• Prevalence and association of microsatellite instability and Lynch syndrome Pan-Cancer and development of a personalized cancer risk prediction tool for Lynch syndrome carriers in India

  The study aimed to systematically study MSI/ MMRd status in tumour DNA and germline mutations in mismatch repair (MMR) genes across a unique, large and heterogeneous group of commonly observed non-colorectal gastrointestinal and genitourinary tumours in the Indian population.

  Study EGAS50000001449

• SCLC MeDIP

  Mimicry of neuronal features are emerging as malignant regulators of cancer growth and metastasis. Neuroendocrine (NE) cancers and small cell lung cancers (SCLC) in particular have been shown to share expression profiles marking various stages of neuronal differentiation. Here, methylation profile from SCLC patients' tumour and normal tissue has been investigated genome wise.

  Study EGAS50000000506

• AML_WES

  This 2014_AML_WES study includes 40 paired samples derived from Korean AML paitients. AML Bone Marrow samples were collected and paired with each normal(Saliva or BM derived) sequencing data. The results of this CN study were analyzed by Mutect and GATK for ranking germline variants and cancer variants to make mutational profile matrix.

  Study EGAS00001001559

• Screening_for_abnormal_CGI_methylation_in_primary_colorectal_tumours

  A common hallmark of neoplastic cells is abnormal acquisition of CpG island (CGI) methylation and the silencing of associated gene promoters. To determine the extent and distribution of CGI methylation in colorectal cancer, we solexa sequenced MBD affinity purified DNA prepared from five colorectal tumours and matched colon mucosa from the same individuals.

  Study EGAS00001000076

• 2017_AML_WGS

  This 2017_AML_WGS study includes 10 paired samples derived from Korean AML paitients. 10 AML Bone Marrow samples were collected and paired with each normal(Saliva or BM derived) sequencing data. The results of this WGS study were analyzed by Mutect and GATK for ranking germline variants and cancer variants to make mutational profile matrix.

  Study EGAS00001002388

• 2014_AML_WES_51 samples

  2014 AML WES study contains 51 paired WES samples which were collected from SNUH. The study was designed to examine the molecular abnormalities from leukemic patients at initial diagnosis in comparison with corresponding germ line control (saliva samples). The results of WXS were analyzed by Mutect for ranking cancer variants and creating mutational matrix.

  Study EGAS00001002819

• Orphan_Tumour_Study_NB

  The aim of this study is to investigate the transcriptional landscape of human cancer. 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/

  Study EGAS00001003445

• 2017_prospective_v2 Whole Exome Sequencing

  2017 AML prospective study contains 10 paired WES samples which were collected from SNUH.The study was designed to examine the molecular abnormalities from leukemic patients at initial diagnosis in comparison with corresponding germ line control (saliva samples). The results of WXS were analyzed by Mutect for ranking cancer variants and creating mutational matrix.

  Study EGAS00001002628

• Hi-C analysis of metastatic prostate tumors

  DNA strands have a complex and highly structured three-dimensional shape within the nucleus that has profound but poorly characterized impacts on transcriptional activity. Herein, we performed the first integrated deep Hi-C sequencing on 80 metastatic castration-resistant prostate cancer biopsy samples from the West Coast Dream Team consortium.

  Study EGAS00001006604

• Hi-C analysis of metastatic prostate tumors - Part 2

  DNA strands have a complex and highly structured three-dimensional shape within the nucleus that has profound but poorly characterized impacts on transcriptional activity. Herein, we performed the first integrated deep Hi-C sequencing on 80 metastatic castration-resistant prostate cancer biopsy samples from the West Coast Dream Team consortium.

  Study EGAS00001006612

• Genomic characterization of co-existing biliary tract intraepithelial neoplasia and carcinoma lesions reveals distinct evolutionary paths of gallbladder cancer

  Gallbladder carcinoma is the most common cancer of the biliary tract with dismal survival largely due to delayed diagnosis. Biliary tract intraepithelial neoplasia (BilIN) is the common benign tumor that is suspected to be precancerous lesions. However, the genetic and evolutionary relationships between BilIN and carcinoma remain unclear. Here we performed whole-exome sequencing of coexisting low-grade BilIN (adenoma), high-grade BilIN, and carcinoma lesions, and normal tissues from the same patients.

  Dataset EGAD00001007792

• Healthy control and lung cancer plasma cfDNA samples from various collection tubes

  The dataset contains 6 lung cancer and 60 healthy control plasma cfDNA samples collected in EDTA, PAXGene and Norgen blood collection tubes at various locations. Shallow WGS was performed on an Illumina Novaseq S4 PE150bp. Samples are provided as raw reads without any prior processing.

  Dataset EGAD00001008322

• MutWP5: CRUK Mutographs of Cancer: Breast: Reduction Mammoplasty (Exome)

  Sequencing of LCM-derived microbiopsies from 10 women who underwent reduction mammoplasty. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequently be sent for whole-genome sequencing. Results from this portion of the study will be compared to women who are BRCA1/2 germline carriers and those with cancer. . This dataset contains all the data available for this study on 2023-03-08.

  Dataset EGAD00001010110

• MutWP5: CRUK Mutographs of Cancer: BRCA Carriers (WG)(Novaseq)

  Sequencing of LCM-derived microbiopsies from 20 women who underwent risk-reducing reduction mastecomies due to germline BRCA1/2. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequenctly be sent for whole-genome sequencing. Results from this poriton of the study will be compared to women who had cosmetic breast reduction surgeries and those with cancer. . This dataset contains all the data available for this study on 2023-03-08.

  Dataset EGAD00001010112

• MutWP5: CRUK Mutographs of Cancer: BRCA Carriers (Exome)(Novaseq)

  Sequencing of LCM-derived microbiopsies from 20 women who underwent risk-reducing reduction mastecomies due to germline BRCA1/2. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequenctly be sent for whole-genome sequencing. Results from this poriton of the study will be compared to women who had cosmetic breast reduction surgeries and those with cancer. . This dataset contains all the data available for this study on 2023-03-08.

  Dataset EGAD00001010115

• Longitudinal profiling of circulating tumour DNA for tracking tumour dynamics in pancreatic cancer

  Whole genome sequencing from two resectable patients with pancreatic cancer for both normal and tumour tissue samples; whole exome sequencing from the two resectable patients and five unresectable patients of peripheral blood mononuclear cells and blood plasma (1-5 time points per patient), and whole exome sequencing of plasma samples from three chronic pancreatitis patients.

  Dataset EGAD00001008593

• MutWP5: CRUK Mutographs of Cancer: Breast: Reduction Mammoplasty (WG)(Novaseq)

  Sequencing of LCM-derived microbiopsies from 10 women who underwent reduction mammoplasty. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequenctly be sent for whole-genome sequencing. Results from this poriton of the study will be compared to women who are BRCA1/2 germline carriers and those with cancer. . This dataset contains all the data available for this study on 2023-03-08.

  Dataset EGAD00001010113

• Anaplastic Meningioma WGS-X10

  Anaplastic meningiomas are a rare, malignant variant of meningioma. At present there is no effective treatment for this cancer. The aim of the study is to identify somatic mutations in anaplastic meningiomas. We plan to sequence a set of 500 known cancer genes in 50 anaplastic meningioma and corresponding peripheral blood DNA samples. Bioinformatics will be used to analyse the results to assess the probability of these mutations being causal and so likely of critical importance for the tumour growth. Identification of these mutations will guide selection of appropriate compounds to effectively treat the disease.

  Dataset EGAD00001001267

• MutWP5: CRUK Mutographs of Cancer: Breast: Reduction Mammoplasty (Exome)(Novaseq)

  Sequencing of LCM-derived microbiopsies from 10 women who underwent reduction mammoplasty. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequenctly be sent for whole-genome sequencing. Results from this poriton of the study will be compared to women who are BRCA1/2 germline carriers and those with cancer. . This dataset contains all the data available for this study on 2023-03-08.

  Dataset EGAD00001010116

• SNP data

  SNP data from 49 paired samples (tumor/germline) with muscle invasive bladder cancer.

  Dataset EGAD00010001943

• TOTHER3

  Patritumab deruxtecan in HER2-negative breast cancer: part B results of the window-of-opportunity SOLTI TOT-HER3 trial and biological determinants of early-response

  Dac EGAC50000000255

• Finding structural variation and functional consequences from primary acute myeloid leukemia cells with complex karyotype (CK-AML) at the single-cell level

  Study EGAS00001007436

• EuCanImage_DEMO_UC1

  This dataset contains the standardized clinical information related to the Use case 1 - Liver Cancer (HCC) from EuCanImage. The Data is Synthetic.

  Dataset EGAD50000002083

• Osteosarcoma_X10

  This is a continuation of the osteosarcoma work we have undertaken.

  Study EGAS00001002167

• Somatic_mutation_in_edited_cholangiocyte_organoids_NanoSeq

  Characterisation of mutation rates and patterns in edited human cholangiocyte organoids (NanoSeq)

  Study EGAS00001006405

• Raw count table

  Raw count matrix of the 124 bulk tumor RNAseq samples from patients with hormone sensitive or castration resistant prostate cancer.

  Dataset EGAD00001008762

• Heterogeneous Genomic Evolution and Immune Microenvironments in Metastatic Lung Cancer

  WES data of paired primary and metastatic tumors

  Dataset EGAD00001006213

• CINECA_synthetic_cohort_EUROPE_UK1 referencing fake samples

  Please note: This synthetic data set (with cohort “participants” / ”subjects” marked with FAKE) has no identifiable data and cannot be used to make any inference about cohort data or results. The purpose of this dataset is to aid development of technical implementations for cohort data discovery, harmonization, access, and federated analysis. In support of FAIRness in data sharing, this dataset is made freely available under the Creative Commons Licence (CC-BY). Please ensure this preamble is included with this dataset and that the CINECA project (funding: EC H2020 grant 825775) is acknowledged. For any questions please contact isuru@ebi.ac.uk or cthomas@ebi.ac.uk This dataset (CINECA_synthetic_cohort_EUROPE_UK1) consists of 2521 samples which have genetic data based on 1000 Genomes data (https://www.nature.com/articles/nature15393), and synthetic subject attributes and phenotypic data derived from UKBiobank (https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001779). These data were initially derived using the TOFU tool (https://github.com/spiros/tofu), which generates randomly generated values based on the UKBiobank data dictionary. Categorical values were randomly generated based on the data dictionary, continuous variables generated based on the distribution of values reported by the UK Biobank showcase, and date / time values were random. Additionally we split the phenotypes and attributes into 4 main classes - general, cancer, diabetes mellitus, and cardiac. We assigned the general attributes to all the samples, and the cardiac / diabetes mellitus / cancer attributes to a proportion of the total samples. Once the initial set of phenotypes and attributes were generated, the data data was checked for consistency and where possible dependent attributes were calculated from the independent variables generated by TOFU. For example, BMI was calculated from height and weight data, and age at death generated by date of death and date of birth. These data were then loaded to the development instance of Biosamples (https://www.ebi.ac.uk/biosamples/) which accessioned each of the samples. The genetic data are derived from the 1000 Genomes Phase 3 release (https://www.internationalgenome.org/category/phase-3/). The genotype data consists of a single joint call vcf files with call genotypes for all 2504 samples, plus bed, bim, fam, and nosex files generated via plink for these samples and genotypes. The genotype data has had a variety of errors introduced to mimic real data and as a test for quality control pipelines. These include gender mismatches, ethnic background mislabelling and low call rates for a randomly chosen subset of sample data as well as deviations from Hardy Weinberg equilibrium and low call rates for a random selection of variants. Additionally 40 samples have raw genetic data available in the form of both bam and cram files, including unmapped data. The gender of the samples in the 1000 genomes data has been matched to the synthetic phenotypic data generated for these samples. The genetic data was then linked to the synthetic data in BioSamples, and submitted to EGA.

  Dataset EGAD00001006673

• scRNAseq data of human innate lymphoid cells (ILCs) and natural killer (NK) cells from fresh umbilical cord blood

  scRNA-seq was performed on the BD Rhapsody platform. ILCs (ILC1, ILC2, ILC3) and NK cells were bulk sorted from fresh cord bloods of 3 donors. The 4 samples containing ILCs and NK cells from each donor were stained with Sampletag antibodies (12 samples in total) before Abseq staining with the BD Immune Discovery panel and 6 additional antibodies was performed to better classify immune cell subsets. The sorted population were pooled before loading onto the BD Rhapsody cartridge. The manufacturer's protocol was followed for library construction and samples were sequenced on a Illumina NovaSeq 6000.

  Dataset EGAD50000001713

• McGill EMC Community projects Release 7 for cell line "hTERT RPE1"

  Complete reference epigenome (as defined by IHEC) of normal hTERT RPE1 cell line as well as hTERT RPE1 cell lines engineered to express EPC1-PHF1 and JAZF1-SUZ12 fusion proteins, found in Endometrial Stromal Sarcoma.

  Dataset EGAD00001007680

• Single-cell B-cell receptor sequencing data of peripheral blood mononuclear cells obtained from 30 ATL patients, 11 HTLV-1-infected asymptomatic carriers, and 4 healthy donors.

  Single-cell B-cell receptor sequencing (scBCR-seq) data of peripheral blood mononuclear cells (PBMCs) obtained from 30 ATL patients (34 samples including 4 sequential ones), 11 HTLV-1-infected asymptomatic carriers, and 4 healthy donors.

  Dataset EGAD00001007013

• LLDeep DAG2+: scRNA-seq in PBMCs

  Single cell transcriptomics of PBMCs of 47 donors from the Lifelines Deep cohort (general population, Northern part of the Netherlands). Cells of five or six different donors were pooled together in one sample pool, resulting in eight different sample pools. In total, 28.855 cells were captured and their transcriptomes were sequenced to an average depth of 74k. Genotype data was available for each donor, which allowed us to use the Demuxlet method that uses variable SNPs between the pooled individuals to determine which cell belongs to which individual. Since genotype information is lacking of 2 individuals, the transcriptome of only 45 individuals could be retrieved.

  Dataset EGAD00001003459

• DAC for Combined MEK and BCL-2/XL inhibition is effective in high-grade serous ovarian cancer patient-derived xenograft models and BIM levels are predictive of responsiveness

  Dac EGAC00001001250

• Noninvasive detection of cancer-associated genome-wide hypomethylation and copy number aberrations by plasma DNA bisulfite sequencing

  Dataset EGAD00001000856

• ega_SJLIFE_BMD_nonALL

  A replication cohort consisting of 1428 adult survivors of any non-ALL pediatric cancer

  Dataset EGAD00010001395

• DNA Methylation profiles of colorectal cancer samples

  Illumina 450K DNA methylation profiles of 314 fresh-frozen colorectal mucosa, adenoma or adenocarcinoma samples.

  Dataset EGAD00010001888