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• Coverage bias and sensitivity of variant calling for four whole-genome sequencing technologies

  Massively parallel sequencing has revolutionized research in cancer genetics and genomics and enhanced our understanding of natural human genetic variation. Recently, Lam et al. have performed a detailed comparison of two next-generation sequencing technologies with respect to their sensitivity to call single nucleotide variants (SNV) and indels. Here, we sequenced two tumor/normal pairs obtained from two paedriatic medulloblastoma patients with Life Technologies’ SOLiD 4 and 5500xl SOLiD, Illumina’s HiSeq2000, and Complete Genomics’ technology. We then compared their ability to call SNVs with high confidence. As gold standard for SNV calling, we used genotypes determined by an Affymetrix SNP array. Additionally, we performed a detailed analysis of how evenly each technology covers the genome and how the reads are distributed across functional genomic regions. Finally, we studied how a combination of data from different technologies might help to overcome the limitations in SNV calling by any of the four technologies alone.

  Study EGAS00001000274

• A comprehensive characterization of the cell-free transcriptome reveals tissue- and subtype-specific biomarkers for cancer detection

  Cell-free RNA (cfRNA) is a promising analyte for cancer detection. However, a comprehensive assessment of cfRNA in individuals with and without cancer has not been conducted. We performed the first transcriptome-wide characterization of cfRNA in cancer (stage III breast [n=46], lung [n=30]) and non-cancer (n=89) participants from the Circulating Cell-free Genome Atlas (NCT02889978). Of 57,820 annotated genes, 39,564 (68%) were not detected in cfRNA from non-cancer individuals. Within these low-noise regions, we identified tissue- and cancer-specific genes, defined as "dark channel biomarker" (DCB) genes, that were recurrently detected in individuals with cancer. DCB levels in plasma were correlated with tumor shedding rate and RNA expression in matched tissue, suggesting that DCBs with high expression in tumor tissue could enhance cancer detection in patients with low levels of circulating tumor DNA. Overall, cfRNA provides a unique opportunity to detect cancer, predict the tumor tissue of origin, and determine the cancer subtype.

  Study EGAS00001004704

• Diagnostic utility of whole genome sequencing in adults with B-other acute lymphoblastic leukemia

  Genomic profiling at diagnosis of B-cell precursor Acute Lymphoblastic Leukemia (BCP-ALL) in adults is used to guide disease classification, risk stratification and treatment decisions. Patients for which diagnostic screening fails to identify disease defining or risk stratifying lesions are classified as B-other ALL. We screened a cohort of 652 BCP-ALL cases enrolled in UKALL14 to identify and perform whole genome sequencing (WGS) on paired tumor-normal samples. For 52 B-other patients we compared WGS findings to data from clinical and research cytogenetics. WGS identifies a cancer associated event in 51/52 cases, this includes an established subtype defining genetic alteration in 5/52 that were previously missed by standard-of-care genetics. Of the 47 true B-other ALL we identified a recurrent driver in 87% (41).  Complex karyotype by cytogenetics emerges as a heterogeneous group, underlied by distinct genetic alterations associated with either favorable (DUX4-r) or poor outcomes (MEF2D-r, IGK::BCL2). For a subset of 31 cases, we integrate findings from RNA-sequencing (RNA-seq) analysis to include fusion gene detection, and classification by gene expression. Compared to RNA-seq, WGS was sufficient to detect and resolve recurrent genetic subtypes, however RNA-seq can provide orthogonal validation of findings. In conclusion, we demonstrate that WGS can identify clinically relevant genetic abnormalities missed by standard-of-care testing and identify leukemia driver events in virtually all cases of B-other ALL.

  Dataset EGAD00001009304

• Natural history of clonal haematopoiesis (2017-09-04)

  The incidence of acute myeloid leukemia (AML) increases with age and mortality exceeds 90% when diagnosed after age 60. Only 10-15% of cases evolve from a pre-existing myeloproliferative or myelodysplastic disorder; the remaining cases arise de novo without a detectable prodrome and are diagnosed upon development of bone marrow failure. Analysis of diagnostic blood samples has demonstrated that de novo AML is preceded by the accumulation of somatic mutations in pre-leukemic hematopoietic stem and progenitor cells (preL-HSPCs) that subsequently undergo clonal expansion. If individuals in this pre-leukemic phase could be identified, methods for determination of risk and monitoring for progression to overt AML could be developed. However recurrent AML mutations also accumulate during aging in healthy individuals who never develop AML, referred to as age related clonal hematopoiesis (ARCH). To distinguish individuals with preL-HSPCs at high risk of developing AML from those with ARCH, we undertook deep targeted sequencing of genes recurrently mutated in AML in blood samples from 133 individuals in the European Prospective Investigation into Cancer and Nutrition (EPIC) study taken on average 6 years before they developed AML (pre-AML group), together with 683 matched healthy individuals (Control group). Pre-AML cases displayed accelerated age-correlated accumulation of somatic mutations.The identity, number and variant allele frequency (VAF) of mutations differed between the two groups, and were incorporated into a computational model of AML risk prediction that accurately distinguished pre-AML cases from controls on average 7 years prior to AML development. Our findings provide proof of concept that early prediction of AML development is feasible in high-risk populations, paving the way for early disease detection, monitoring, and potentially prevention.

  Dataset EGAD00001003703

• Characterization and clinical relevance of the genomic alterations defining invasive lobular breast cancer

  Background: Invasive lobular breast cancer (ILBC) is the second most common histological subtype after ductal breast cancer (IDBC). In spite of significant clinical and pathological differences, ILBC is still treated as IDBC. Here, we aimed at identifying recurrent genomic alterations in ILBC with potential clinical implications.Methods: Starting from 630 ILBC primary tumors with a median follow up of 10 years, we interrogated oncogenic substitutions and indels of 360 cancer genes and genome-wide copy number alterations in 413 and 170 ILBC samples, respectively, and correlated those findings with clinical, pathological, and outcome features. The Cancer Genome Atlas database was used for comparison of frequency estimates.Results: Besides the high mutation frequency of CDH1 in 65% of the tumors, alterations in one of the three key genes of the PI3K pathway, PIK3CA, PTEN and AKT1, were present in more than half of the cases. ERBB2 and ERBB3 were mutated in 5.1 and 3.6% of the tumors. FOXA1 mutations and ESR1 copy number gains were detected in 9% and 25% of the samples. All these alterations were more frequent in ILBC than IDBC. The histological diversity of ILBC was associated with specific genomic alterations, such as enrichment for ERBB2 mutations in the mixed, non-classic subtype, and for ARID1A mutations and ESR1 gains in the solid subtype. Finally, ERBB2 and AKT1 mutations were associated with short-term risk of relapse, and chromosome 1q and 11p gain with increased and decreased breast cancer free survival, respectively.Conclusion: ERBB2, ERBB3 and AKT1 mutations represent high prevalence therapeutic targets in ILBC. FOXA1 mutations and ESR1 gains urgently deserve dedicated clinical investigation, especially in the context of endocrine treatment.

  Dataset EGAD00001001395

• Genome-Wide Association Study of Anorexia Nervosa (Price Foundation, Klarman Family Foundation, Center for Applied Genomics at the Children's Hospital of Philadelphia, Scripps Translational Sciences Institute Clinical Translational Science Award)

  Twin studies are consistent with substantial heritability in anorexia nervosa (AN), although detecting and confirming individual risk alleles has been difficult, due to small effects of single alleles and limited samples in prior studies. Methods: 1105 AN DNA samples obtained in a multisite study and 3733 pediatric patients of normal body weight were genotyped using the Illumina 610Q chip at The Center for Applied Genomics at The Children's Hospital of Philadelphia. Cases and controls were of European ancestry. Single nucleotide polymorphism (SNP) genotypes were subjected to quality control procedures, including elimination of SNPs with: call rates < 95%, minor allele frequency < 5%, and if Hardy-Weinberg equilibrium testing yielded p < 0.0001. Samples were removed if not of European ancestry or if showing cryptic relatedness. Eight AN DNA samples were deleted for low call rate, and 51 AN samples were deleted for cryptic relatedness. The statistical program, PLINK, was used to calculate a P value for each SNP passing quality control using the Cochran-Armitage trend test. The PennCNV program was used to define copy number variation (CNV). Results: We performed a genome-wide association study (GWAS) using with 1033 AN cases and 3733 controls (genomic inflation factor = 1.08). There were 11 SNPs with P<1X10-5 [(rsID, chromosome location, nearest gene, distance to nearest gene (base-pair), P value) rs6959888, 7q21.13, ZNF804B, 0, 1.63E-06; rs17725255, 20p11.23, CSRP2BP, 39396, 1.72E-06; rs10494067, 1p13.3, NTNG1, 0, 5.83E-06; rs2383378, 14q12, AKAP6, 0, 6.41E-06; rs410644, 5q14.1, SSBP2, 40462, 6.74E-06; rs4479806, 5p14.1, CDH9, 156926, 7.79E-06; rs957788, 13q33.3, FAM155A, 0, 8.11E-06; rs830998, 2q31.1, LRP2, 0, 8.68E-06; rs6782029, 3p25.3, VGLL4, 0, 9.04E-06; rs512089, 9p21.3, ELAVL2, 47984, 9.85E-06; rs3808986, 11q24.3, APLP2, 29217, 9.92E-6]. CNV analyses were performed on 1015 AN cases and 3532 controls. Overall frequencies of common or rare CNVs were similar between cases and controls. Specific rare and large (>500 kb, <1%) CNVs of interest included deletion of a large (~1.4Mbp) region of chr13q12 found in 2 AN samples and at a 10 fold lower frequency in a large sample (72,918) of subjects containing the genes SGCG, SACS, TNFRSF19, MIPEP, PCOTH, C1QTNF9B, SPATA13, MIR2276, and C1QTNF9, and an overlapping deletion and a duplication observed in 3 AN samples overlapping the CNTN6 and CNTN4 genes. Partially overlapping ~ 30 kb duplications were seen in 12 AN cases and in 1 control at the CDC5L gene on chromosome 6. Partially overlapping deletion of the 3' half of the PSTPIP1 gene was seen in 5 AN cases and no controls. Finally, a ~ 60 kb deletion of the PLEC1 gene was observed in 5 AN cases and in none of 3532 controls. Discussion: This is the first GWAS of AN. These preliminary results are consistent with absence of a major gene effect in AN. These results are consistent with genetic risk conveyed by multiple common alleles of small effect, as well as some uncommon CNVs of potentially larger effect. None of the implicated genes has a clear role in eating behavior. It must be emphasized that these results are preliminary and an additional ~ 400 AN cases will be analyzed as time and resources permit. These results require confirmation through study of independent populations of AN women.

  Study phs000679

• University of Bergen Rare Monogenic Autoimmune Syndrome (APS-1) Data Access Committee

  This is the DAC appointed by the University of Bergen for the datasets related to the study of APS-1 in the Department of Clinical Sciences . These data are from single cell transcriptomic analysis of expanded Tregs from patients with the rare monogenic autoimmune syndrome “APS-1” compared to healthy donors.

  Dac EGAC50000000081

• Sputum RNA-Seq from Asthmatic Patients for Microbes and Genes

  RNA-seq files and other data associated with an investigation of the relationship between microbes, genes and immune cells present in the sputum of humans with asthma.

  Study phs002224

• Norwegian Institute of Public Health – Cancer Registry of Norway Data Access Policy for JanusRNA transcriptomics datasets archived in Federated EGA Norway

  JanusRNA transcriptomics datasets are generated from biobank samples from the Janus Serum bank of the Cancer Registry of Norway/National Institute of Public Health. This Data Access Committee has been appointed to govern controlled access to these datasets archived in Federated EGA Norway.

  Dac EGAC50000000192

• Single-cell genotype-to-phenotype mapping via co-capture of DNA mutations and mRNA transcripts

  We developed single-cell Genotype-to-Phenotype sequencing (scG2P) for high-throughput, highly-multiplexed, single-cell joint capture of recurrently mutated genomic regions and mRNA phenotypic markers in cells or nuclei isolated from solid tissues. We applied scG2P to aged esophagus samples from five individuals with high alcohol and tobacco exposure.

  Dac EGAC50000000833

• RNAseq of 7 MPNSTs

  RNAseq of 7 MPNSTs for Magallon-Lorenz 2026. Contains 5 samples sequenced with DNBseq at BGI (four 2x100bp and one 2x150bp) and 2 samples sequenced with Illumina stranded mRNA-seq technology. BGI samples have been prefiltered with SOAPnuke. Two fastq files provided per sample with no additional filtering or QC.

  Dataset EGAD50000002493

• 909 bulk mRNA sequencing samples from the UPTIDER program

  Raw sequencing data for 909 bulk mRNA samples that correspond to 749 metastases, 64 primary tumours and 96 normal tissue. These samples were sequenced using NovaSeq6000. Library was prepared with Lexogen QuantSeq 3' FWD. Raw single-end fastq samples have been deposited as gzipped files.

  Dataset EGAD50000001910

• Ovarian Cancer Single Cell Whole Genome Sequencing

  Five primary, treatment-naive ovarian cancer specimens were subjected to single cell whole genome sequencing (10x Genomics workflow). Libraries were sequenced on an Illumina NovaSeq 6000 instrument. Sequencing data was processed with the Cell Ranger DNA pipelines. Archived here are BAM files for each sample.

  Dataset EGAD50000002102

• Mechanism of Decitabine response in MDS/AML patients

  The dataset includes single cell RNA sequencing data from 17 AML/MDS patients undergoing a decitabine clinical trial. In total 47 samples were interrogated using 10X genomics ChromiumTM 140 Single Cell 5' Reagent Kit. The dataset includes bam files for each sample generated using CellRanger with default parameters.

  Dataset EGAD50000001354

• CosMX spatial transcriptomics

  This study consists of the spatial transcriptomics analyis data generated by : CosMxTM Human Universal Cell Characterization RNA Panel (1000-plex); NanoString, USA for n=4 SLD-HCC and n=4 non-SLD-HCC. The goal of this data is to compare SLD-HCC vs non-SLD-HCC as well as response to immunotherapy

  Dataset EGAD50000001507

• Targeted deep sequencing data of 386 T-ALL patients

  Targeted deep sequencing data of 386 T-ALL patients in several high-risk T-ALL genes. Samples were prepared according to Agilent's HaloPlex HS Target Enrichment Protocol and sequenced as 75bp paired-end reads. Data is available as paired-end FASTQ files for each sample.

  Dataset EGAD50000001168

• D1D2 trial Whole Exome Sequencing (WES)

  Surgical treatment of gastric cancer: 15-year follow-up results of the randomised nationwide Dutch D1D2 trial. Molecular characterisation of N=80 resectable gastric adenocarcinomas from D1D2 trial, describing mutations obtained by matched (Tumor-Normal) whole exome sequencing (WES). Samples are annotated for TCGA’s molecular classification (MSI, GS and CIN).

  Dataset EGAD50000001144

• Dataset for Multiple Myeloma WGS data, part 2

  This dataset contains 518 case and control WGS sequencing samples of patients with multiple myeloma. Sequencing was performed on Illumina NovaSeq 6000 and HiSeq X using TruSeq Nano DNA Kits. The sequencing was always paired.

  Dataset EGAD50000000681

• Dataset for Multiple Myeloma WGS samples

  This dataset contains 221 case and control WGS sequencing samples of patients with multiple myeloma. Sequencing was performed on Illumina NovaSeq 6000 and HiSeq X using TruSeq Nano DNA Kits. The sequencing was always paired.

  Dataset EGAD50000000682

• Altered Blood and Keratinocyte microRNA/transfer RNA Fragment Profiles Related to Fibromyalgia Syndrome and its Severity

  We show dysregulated microRNA and tRNA fragment profiles related to FMS pathopyhsiology and opening new perspectives for FMS diagnostics and symptom monitoring. This dataset includes all sequencing raw files from whole blood (tempus tube) and keratinocyte sequencing.

  Dataset EGAD50000000900

• Single-cell/single-nucleus RNA-seq of diffuse hemispheric gliomas, H3G34-mutant.

  9 DHG-H3G34 patient samples were sequenced by paired-end scRNA-sequencing using the Smart-Seq2 protocol on a NextSeq 500 sequencer (Illumina). Illumina bcl2fastq 1.5 was used for demultiplexing. This dataset contains the resulting 9,408 fastq files of 4,704 single cells/nuclei sequenced.

  Dataset EGAD50000000760

• BAM files from capture-based targeted sequencing of 12 agressive B-cell lymphoma tumour samples (IG-MCL-panel)

  This dataset contains BAM files from capture-based targeted sequencing of 12 agressive B-cell lymphoma tumour samples for cases 1 to 6 and 8 to 13. The sequencing panel used is a MCL-oriented panel containing 159 genes.

  Dataset EGAD50000000801

• Sample metadata

  Sample metadata for this experiment. Includes treatment and donor derivation information.

  Dataset EGAD50000000827

• ctDNA diva aggregate data

  ctDNA biomarker and relevant clinical data for divarasib phase I GO42144 study, including tumor type, KRAS G12C mutation detectability in plasma at baseline, baseline SLD, sites of metastasis, lines of therapy, best response, confirmed best response, PFS, ctDNA tumor fraction and KRAS G12C VAF at baseline/C1D15/C3D1.

  Dataset EGAD50000000454

• Exome sequencing for heterogeneity and evolution of DNA mutation rates

  Dataset comprising 27 pairs of high-depth (300x) WES results obtained from 54 PDXs derived from primary CRCs resected synchronously with their corresponding metastases. These exoms sequences are part of a larger study on the heterogeneity and evolution of DNA mutation rates in microsatellite-stable colorectal cancer.

  Dataset EGAD50000000208