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• WES data

  WES FASTq files of 76 bulk pre-treatment tumors and 76 matched peripheral blood mononuclear cells from GO30140 group A

  Dataset EGAD00001008129

• Wilm's tumor sequencing data

  No. of samples: 80 (28 ULP-WGS, 26 WES, 26 RNA-SEQ) File types: FASTQ (28 ULP-WGS, 19 WES, 18 RNA) and BAM (7 WES, 8 RNA) Technology used: Sequencing - Illumina Novoseq 6000; Map/Align - Illumina DRAGEN v3.7.5; Genome assembly - GrCh38p13 Filename nomenclature: - SampleName_Passage_SampleType_TissueType_SequencingType - Passage of: PX = unknown; PZ = from patient; P0 = first passage from patient on plastic; P1 = first passage from plastic/PDX/organoid - SampleType: STN = normal; STT = tumor - SampleType STN: 00 = tissue unknown; 01 = adjacent normal; 02 = fibroblast; 03 = germline blood; 21 = cell line from patient tissue; 22 = cell line from PDX; 23 = cell line from patient fibroblast - SampleType STT: 00 = tissue unknown; 01 = primary tumor; 21 = cell line from patient; 22 = cell line from PDX - TissueType: WT = Wilm's tumor; 00 = kidney unknown; 01 = kidney left; 02 = kidney right - SequencingType: 00 = unknown; 02 = ultra-low pass whole-genome sequencing; 20 = whole-exome; 61 = bulk RNA-sequencing

  Dataset EGAD00001011111

• Gene expression QTL mapping in stimulated iPSC-derived macrophages

  Immune cells sense and respond to external stimuli, initiating an inflammatory response, with genetic variants potentially altering these responses. Traditional QTL mapping often uses naïve cells, missing condition-specific variants detectable post-stimulation. Our study uses a high-throughput platform to map eQTLs across 24 conditions using iPSC-derived macrophages, identifying that 76% of eQTLs in stimulated conditions were also present in naïve cells. We found response eQTLs (reQTLs) vary widely across conditions, with rare single-condition reQTLs being overrepresented among disease-colocalizing eQTLs. This study nominates 21.7% more disease effector genes at GWAS loci through reQTL colocalization, with 38.6% not found in the GTEx catalogue, highlighting the importance of condition-specific regulatory variation in understanding disease risk alleles. Our findings underscore the value of condition-specific studies in elucidating the genetic mechanisms underlying complex diseases. 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 EGAD00001015380

• Validation of a Haloplex platform for targeted re-sequencing of the exons of 25 genes

  We recently used the Agilent SureSelect platform to re-sequence a set of genes known to be mutated in human AML. The results from 10 AML DNA samples were very satisfactory, but the effort required was significant. Thus, we decided to re-sequence the same genes using the Haloplax system for target enrichment in 48 AML samples. We planned to do this using MiSeq and have data from a pilot of 3 samples. The data is promising but coverage appears pathcy so far. However, in order to get a better understanding of the data we will need deeper sequencing. We will need two lanes of HiSeq to get the same degree coverage as Sureselect. his 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 EGAD00001000603

• Inherited chromosomally-integrated human herpesvirus 6A/B (HHV-6A/B) genome sequences in the Japanese population

  The deposited sequences represent inherited chromosomally-integrated human herpesvirus 6 (iciHHV-6) genomes identified from 10 BioBank Japan (BBJ) subjects based on the analysis of the whole-genome sequencing (WGS) data. In brief, we re-aligned unmapped reads from the WGS to HHV-6A genome (Genbank accession number: KJ123690.1) using BWA-MEM algorithm. Ten out of 3,256 subjects were identified with high depth of coverage of HHV-6. We further distinguished subjects with integrated HHV-6A subtypes from those with integrated HHV-6B based on phylogenetic analysis of concatenated sequences of three viral genes (U27/U43/U83, which show high divergence between viral species). We reconstructed the HHV-6 viral genome of 10 subjects. First, reads that mapped to a reference HHV-6A genome (KJ123690.1) were further aligned against the integrated HHV-6A genome derived from a Japanese individual NA18999 (GenBank Accession number: KY316047.1) using BWA-MEM. Based on the alignment, variant calling was performed using freebayes (version: v1.2.0-2-g29c4002) with parameters ploidy = 1 and min-alternate-fraction = 0.8 {Garrison, 2012}. We generated subject-specific iciHHV-6 viral sequences by applying the resulting variants to the KY316047.1 reference genome using the FastaAlternateReferenceMaker function in the Genome Analysis Toolkit (GATK) v3.7. Please note that HHV-6B-specific variants are unlikely to be sensitively reconstructed using this method.

  Study JGAS000240

• Target gene sequencing for human normal endometrial glands

  The raw fastq files target sequencing of 112 genes for 1,298 endometrial glands and matched blood samples. The paired-end sequencing data sets (R1 and R2) are deposited. ABCC1, ACRC, ANK3, ARHGAP35, ARID1A, ARID5B, ATCAY, ATM, ATR, BARD1, BCOR, BRCA1, BRCA2, BRD4, BRIP1, CAMTA1, CDC23, CDYL, CFAP54, CHD4, CHEK1, CHEK2, CTCF, CTNNB1, CUX1, DGKA, DISP2, DYNC2H1, EMSY, FAAP24, FAM135B, FAM175A, FAM65C, FANCA, FANCB, FANCC, FANCD2, FANCE, FANCF, FANCG, FANCI, FANCL, FANCM, FAT1, FAT3, FBN2, FBXW7, FGFR2, FRG1, GPR50, HEATR1, HIST1H4B, HNRNPCL1, HOOK3, KIAA1109, KIF26A, KMT2B, KMT2C, KRAS, LAMA2, LRP1B, MLH1, MON2, MRE11A, MSH2, MSH6, MTOR, NBN, PALB2, PHEX, PIK3CA, PIK3R1, PLXNB2, PLXND1, PMS2, POLE, POLR3B, PPP2R1A, PTEN, PTPN13, RAD50, RAD51, RAD51B, RAD51C, RAD51D, RAD52, RAD54B, RAD54L, RICTOR, SACS, SIGLEC9, SLC19A1, SLX4, SPEG, STT3A, TAF1, TAF2, TAS2R31, TFAP2C, TNC, TONSL, TP53, TTC6, UBA7, VNN1, WT1, XIRP2, ZBED6, ZC3H13, ZFHX3, ZFHX4, ZMYM4.

  Dataset EGAD00001008465

• HELIUS cohort

  The gut microbiota composition is unique to every individual but is shaped by common factors including diet, lifestyle, medication use, early-life determinants, living environment or genetics. Most of these factors may be influenced by ethnicity. This study explored variations in fecal microbiota composition in 6048 individuals with different ethnic backgrounds living in the same geographical area (Amsterdam, the Netherlands). The HELIUS data are owned by the Amsterdam University Medical Centers, location AMC in Amsterdam, The Netherlands. To allow sharing of microbiome data collected in HELIUS with (inter)national researchers, 16s rRNA sequence analysis has been stored at the European genome-phenome archive (EGA; accession code EGAD00001004106). This requires that access needs to be granted, also because the HELIUS data are stored with relevant phenotypical variables. Access is granted to all researchers affiliated with an internationally recognized research institution who request to use the HELIUS data within the EGA context, after having signed the data transfer agreement. Any researcher can request the data by submitting a proposal to the HELIUS Executive Board as outlined at http://www.heliusstudy.nl/en/researchers/collaboration, by email: heliuscoordinator at amsterdamumc dot nl. The HELIUS Executive Board will check proposals if they do not conflict with ethical approvals and informed consent forms of the HELIUS study.

  Study EGAS00001002969

• Genetic landscape of inherited retinal dystrophies

  In the context of research, this dataset contains 423 IRD samples; 411 of them analyzed with Clinical Exome Sequencing solutions, and 12 with Whole Exome Sequencing.

  Dataset EGAD00001007022

• CBD-RAW-SC-GEX: 10X Single-Cell Gene Expression

  Raw Illumina sequencing data and CellRanger BAM output files. For further information regarding this dataset, please contact Stephen Sansom at contact@combat.ox.ac.uk.

  Dataset EGAD00001008007

• TSCA-LI amplicon sequencing of called variants in WXS data of DSALL.

  Targeted resequencing of samples was done with TruSeq custom amplicon low input kit (TSCA-LI, Illumina). The oligo capture probes were designed to include a prefix of 8 random nucleotides at the 5 end of each probe. The assay is designed such that each targeted locus is annealed with two probes, resulting in amplicons tagged with unique molecular identifiers (UMI) (22) of 16 bases. Raw FASTQ sequencing files were processed as following: (a) The first 8 bases were trimmed from each read and recorded with the corresponding base quality scores (BQ) in the attribute field. (b) Reads were aligned with BWA. (c) First round of PCR duplicate cleaning was performed with picard tools markDuplicates using the parameters BARCODE_TAG=BC TAGGING_POLICY=All REMOVE_DUPLICATES=true (d) Since in the previous step only duplicate reads with identical UMIs were removed, a second pass of filtering was done. Reads with identical mapping were considered unique only if their corresponding UMIs were different in at least 3 positions (i.e., UMI edit distance > 2). (e) Paired-end read pairs overlapping genomic positions were clipped to avoid overestimation of the sequencing coverage using bamUtils clipOverlap.

  Dataset EGAD00001003275

• Bulk RNA sequencing of Singapore colorectal cancer patients (SG-BULK)

  RNA-seq libraries were prepared using the KAPA Stranded RNA-Seq Kit with RiboErase (Kapa Biosystems, Wilmington, MA) and sequenced to a target depth of 200-M reads on the Illumina HiSeq platform (Illumina, San Diego, CA).

  Dataset EGAD00001008512

• Neuroblastoma patient Total RNA Seq data

  Tumor Total RNA Seq data of primary neuroblastomas. This is an update of the „Berlin Neuroblastoma Dataset” (EGAS00001004022). This data was used for the analysis of circular RNA expression and regulation in neuroblastoma.

  Dataset EGAD00001008124

• Next Generation Children project

  Whole genome sequencing of sick children in neonatal and paediatric intensive care units, aligned to reference assembly GRCh37.

  Dataset EGAD00001007780

• Multiregional single cell RNA sequencing of human renal cell carcinoma

  The dataset comprises of 5' single cell RNA sequencing with TCR enrichment with 10x Genomics' Chromium technology of multiregional biopsies of human renal cell carcinomas. Biopsies from different tumour regions, the tumour-normal interface, normal kidney, normal adrenal, metastatic regions, peri-nephric fat, and peripheral blood were sequenced from 12 patients with kidney tumours.

  Dataset EGAD00001008030

• Phenotype Risk Scores Identify Patients with Unrecognized Mendelian Disease Patterns

  This study was designed to assess the phenotypic effects of rare variants. Rare variants are difficult to study in a high-throughput manner because most cohorts are underpowered to detect associations. In order to gain power to test rare variants, we use Phenotype Risk Scores (PheRS) based on features of Mendelian diseases. PheRS is calculated using claims data from an EHR that is mapped to clinical features from OMIM's clinical descriptions of Mendelian disease. We calculated PheRS for 1,204 Mendelians diseases in a cohort of 21,701 individuals genotyped on the HumanExome BeadChip. We then tested for association between these diseases and rare variants in causal genes. A phenotype risk score is calculated as the weighted sum of features for a given disease. The features are defined as a set of phecodes (consolidated ICD codes) associated with a particular Mendelian disease as described in OMIM. The weights for each phecode are calculated as the log inverse prevalence of the phecode in our cohort. For an individual, their score equals the sum of the weights for each phecode that is present in their medical record. Our study was based on a cohort of individuals with genotype data linked to de-identified electronic health records (EHR) from Vanderbilt's BioVU resource. We hope that this method will help generate phenotype-genotype correlation data on rare variants which in turn may inform rare variant interpretations use for diagnostics.

  Study phs001516

• August 2021 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  August 2021 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001008101

• Genetic-epigenetic tissue mapping for plasma DNA: applications in prenatal testing, transplantation and oncology

  We developed Genetic-Epigenetic Tissue Mapping (GETMap) to determine the tissue composition of plasma DNA carrying genetic variants not present in the constitutional genome through comparing their methylation profiles with relevant tissues.

  Dataset EGAD00001007041

• Investigation of the Causal Etiology in a Patient with T-B+NK+ Immunodeficiency

  We describe a male proband with normal B lymphocyte and natural killer (NK) cell numbers, but who had T lymphopenia beginning at 1 week of age. His peripheral blood contained very few T cell receptor excision circles (TREC), suggesting impaired thymic T cell development. He received an allogeneic hematopoietic stem cell marrow transplant, but despite engraftment, it did not fully correct the T lymphopenia. Sequencing excluded known immunodeficiency genes; however, whole exome sequencing revealed X-linked inheritance by the male proband of a missense mutation in MED14 (MED14V763A), a component of the mediator complex. Functional screening of the MED14V763A variant in zebrafish suggested that MED14 is essential for normal development, since morpholino (MO)-mediated loss of MED14 function attenuated T cell development, but it was rescued by ectopic expression of the wild type human MED14 but not by the MED14V763A variant. This defect in T cell repopulation is consistent with the incomplete T cell reconstitution observed upon transplantation of the proband with bone marrow from his healthy male sibling, who was found to have the same MED14V763A variant. However, the brother was normal, indicating that the altered MED14 could not by itself explain the disease. WES also revealed a mutation in the L1 cell adhesion molecule (L1CAMQ498H); however, introducing that mutation in vivo in mice did not disrupt T cell development. Consequently, the immunodeficiency in the patient is not fully elucidated. It is possible that MED14 contributes, but it is also possible that another gene is fully responsible for the disease.

  Study phs002990

• KiCS WGS data for academic and for-profit use

  Data from samples that are marked for both academic and for-profit use.

  Dataset EGAD00001009699

• Efficacy of two different FGFR-inhibitors in a patient with extrahepatic cholangiocarcinoma harboring an FGFR2 mutation

  Cholangiocarcinomas (CCAs) is a type of cancer with few effective systemic therapies. Elucidation of the molecular landscape of the disease from genomic studies based on next generation sequencing (NGS) has contributed to the introduction of new targeted therapies. One of these treatments consists of a class of small molecules that target members of the FGFR family of receptor tyrosine kinases. These drugs are effective and have been approved for cholangiocarcinomas with fusions or rearrangements of FGFR genes. In contrast, the role of these inhibitors in cholangiocarcinomas with mutations in FGFR genes is less well defined. We report here a patient with a cholangiocarcinoma bearing a FGFR2 p.Ser252Trp mutation. The patient was treated with two different FGFR inhibitors, as the first caused ocular toxicity. She obtained clinical benefit from both. This case illustrates the efficacy of FGFR inhibitors on cholangiocarcinoma with specific point mutations. This is the first case to report the clinical benefit of these drugs in FGFR2 p.Ser252Trp mutation. Clinical benefit can be sustained, as seen in our patient. Our case also shows that FGFR inhibitors-induced adverse effects, such as ocular toxicities, may not recur after re-challenge with an alternative drug of the same class.

  Dataset EGAD50000000021

• STREP GENE: Genetics and Severe Streptococcal Infections

  This study investigated host genetic susceptibility to invasive group A streptococcal disease in the UK. Cases were either survivors recruited retrospectively through a patient group or identified from the a tissue bank at Imperial College London. Those recruited through the patient group had survived an episode of invasive GAS disease at a UK hospital since 1980 with microbiological confirmation obtained either through Public Health England or from the treating hospital. Those identified from the tissue bank had been diagnosed with invasive GAS disease at the Hammersmith Hospital, London, UK, since 2006. All cases aged less than 65 years without long-term medical conditions genome-wide genotyped using either the Illumina HumanCore or the Global Screening Array platform.

  Study EGAS00001003421

• Whole exome sequencing of a representative cohort of AML

  The Genomic DNA Clean & Concentrator kit (ZYMO Research) was used to remove EDTA from the DNA samples. Sample libraries were prepared using 100 ng of input according to the KAPA HyperPlus Kit (Roche) using Unique Dual Index adapters (Integrated DNA Technologies, Inc.). Exomes were captured using the SeqCap EZ MedExome (Roche Nimblegen) according to SeqCap EZ HyperCap Library v1.0 Guide (Roche) with the xGen Universal blockers – TS Mix (Integrated DNA Technologies, Inc.). The amplified captured sample libraries were paired-end sequenced (2x100 bp) on the Novaseq 6000 platform (Illumina) and aligned to the hg19 reference genome using the Burrows-Wheeler Aligner (BWA)3, v0.7.15-r1140.

  Dataset EGAD00001007580

• Whole-exome sequencing of hepatocellular carcinoma biopsies

  All 122 HCC biopsies and 115 non-tumoral tissues from 114 patients were subjected to whole-exome sequencing. Whole-exome capture was performed using the SureSelectXT Clinical Research Exome (Agilent Technologies) or SureSelect Human All Exon V6+COSMIC (Agilent Technologies) platforms according to the manufacturer’s guidelines. Sequencing was performed on an Illumina HiSeq 2500 at the Genomics Facility Basel according to the manufacturer’s guidelines. Paired-end 101-bp reads were generated.

  Dataset EGAD00001008182

• HELIUS cohort gut microbiome

  The gut microbiota composition is unique to every individual but is shaped by common factors including diet, lifestyle, medication use, early-life determinants, living environment or genetics. Most of these factors may be influenced by ethnicity. This study explored variations in fecal microbiota composition in 6048 individuals with different ethnic backgrounds living in the same geographical area (Amsterdam, the Netherlands). The HELIUS data are owned by the Amsterdam University Medical Centers, location AMC in Amsterdam, The Netherlands. To allow sharing of microbiome data collected in HELIUS with (inter)national researchers, 16s rRNA sequence analysis has been stored at the European genome-phenome archive (EGA; accession code EGAD00001004106). This requires that access needs to be granted, also because the HELIUS data are stored with relevant phenotypical variables. Access is granted to all researchers affiliated with an internationally recognized research institution who request to use the HELIUS data within the EGA context, after having signed the data transfer agreement. Any researcher can request the data by submitting a proposal to the HELIUS Executive Board as outlined at http://www.heliusstudy.nl/en/researchers/collaboration, by email: heliuscoordinator at amsterdamumc dot nl. The HELIUS Executive Board will check proposals if they do not conflict with ethical approvals and informed consent forms of the HELIUS study.

  Dataset EGAD00001004106

• HELIUS cohort gut microbiome batch2

  The gut microbiota composition is unique to every individual but is shaped by common factors including diet, lifestyle, medication use, early-life determinants, living environment or genetics. Most of these factors may be influenced by ethnicity. This study explored variations in fecal microbiota composition in 6048 individuals with different ethnic backgrounds living in the same geographical area (Amsterdam, the Netherlands). The HELIUS data are owned by the Amsterdam University Medical Centers, location AMC in Amsterdam, The Netherlands. To allow sharing of microbiome data collected in HELIUS with (inter)national researchers, 16s rRNA sequence analysis has been stored at the European genome-phenome archive (EGA; accession code EGAD00001004106). This requires that access needs to be granted, also because the HELIUS data are stored with relevant phenotypical variables. Access is granted to all researchers affiliated with an internationally recognized research institution who request to use the HELIUS data within the EGA context, after having signed the data transfer agreement. Any researcher can request the data by submitting a proposal to the HELIUS Executive Board as outlined at http://www.heliusstudy.nl/en/researchers/collaboration, by email: heliuscoordinator at amsterdamumc dot nl. The HELIUS Executive Board will check proposals if they do not conflict with ethical approvals and informed consent forms of the HELIUS study.

  Dataset EGAD00001009732