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• Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE)

  ECLIPSE was a longitudinal observational study of 2164 COPD subjects and a smaller number of smoking controls (337) and nonsmoking controls (245) followed regularly for three years, with three chest CT scans (at baseline, one year, and three years) (Vestbo, European Respiratory Journal 2008; 31: 869). Inclusion criteria included age 40-75, at least 10 pack-years of smoking, and spirometry in GOLD grades 2-4 (COPD cases) or normal spirometry with post-bronchodilator FEV1 >85% predicted and FEV1/FVC>0.7 (controls). Study visits were performed at enrollment, three months, and every six months thereafter with spirometry, questionnaires, and other clinical evaluations. The ECLIPSE CT scans have been analyzed with the VIDA software for emphysema and airway phenotypes. ECLIPSE has provided key insights into the clinical epidemiology of COPD, including COPD exacerbations (Hurst, NEJM 2010; 363: 1128) and lung function decline in COPD (Vestbo, NEJM 2011; 365: 1184). ECLIPSE has been used in a number of genetic studies of COPD susceptibility and protein biomarkers(Faner, Thorax 2014; 69: 666). Genome-wide gene expression microarray data are available in 147 induced sputum samples from COPD subjects and 248 peripheral blood samples from COPD and control subjects.

  Study phs001252

• Non-small cell lung cancer molecular subtypes and vulnerability to immunotherapy treatment combinations

  The phase 3 IMpower150 trial in treatment-naïve patients with metastatic non-small-cell lung cancer (NSCLC) demonstrated significantly longer progression-free (PFS) and overall survival (OS) with first-line atezolizumab (anti-PD-L1)-bevacizumab (anti-VEGF)-carboplatin-paclitaxel (ABCP) than with bevacizumab-carboplatin-paclitaxel (BCP). We characterised four molecular NSCLC subtypes identified by unsupervised clustering of transcriptomes of 564 pre-treatment primary tumour samples from IMpower150 using non-negative matrix factorization (NMF1-4). Each subtype had distinct tumour PD-L1 expression levels, epithelial characteristics, immune composition, and treatment outcomes. Both NMF2 (enriched in tumour proliferation signal, macrophages, and monocytes) and NMF4 (enriched in B-cells and T cells) had elevated tumour PD-L1 expression. Of these two, only NMF4 demonstrated PFS and OS benefits with ABCP versus either BCP or atezolizumab-carboplatin-paclitaxel (ACP). Patients with NMF1 (enriched in basal and squamous-like cells) had improved outcomes on ABCP compared with ACP or BCP; those with NMF3 (enriched in adenocarcinoma signatures) showed similar outcomes among treatments. These insights could help inform individualised first-line treatment for metastatic NSCLC.

  Study EGAS50000001272

• Submitters and requesters Statistics

  EGA Statistics Bibliography Growth Community Archive Distribution Catalogue Here, we show the amount and global distribution of submitters and requesters Requester accounts created by country The below figure represents the number of requester accounts by country. In most of the cases cases, country was inferred from the requester email domain. Those requesters whose email domain could not be assigned to a country such as @gmail.com, are not included. Note that a requester is a user that has had a granted permission at some point in time. Requester Accounts Created by Country Download as PNG Download as JPG Download as WEBP Download as CSV map pie mapChart('requester-country', 'https://stats.ega-archive.org/requester/country') pieChart('requester-country-pie-chart', 'https://stats.ega-archive.org/requester/country','Requester accounts created by country') Requester accounts created by year The below figure represents the number of requester accounts by year. Note that a requester is a user that has had a granted permission at some point in time. Requester Accounts Created by Year Download as PNG Download as JPG Download as WEBP Download as CSV barChart('requester-year', 'https://stats.ega-archive.org/requester/year', ['Requester Accounts', 'Years'], true) Industry requester accounts The below figure represents the top 15 industry requesting companies. Industry Requester Accounts Download as PNG Download as JPG Download as WEBP Download as CSV pieChart('industry-requester-accounts', 'https://stats.ega-archive.org/industry/requester/accounts', 'Industry Requester Accounts') Submitter accounts created by country The below figure represents the number of submitter accounts by country. Location was infered from the requester email domain. Submitter Accounts Created by Country Download as PNG Download as JPG Download as WEBP Download as CSV map pie mapChart('submitter-accounts', 'https://stats.ega-archive.org/submitter/accounts/country') pieChart('submitter-accounts-pie-chart', 'https://stats.ega-archive.org/submitter/accounts/country','Submitter accounts created by country') Submitter accounts created by year The below figure represents the number of submitter accounts by year. Submitter Accounts Created by Year Download as PNG Download as JPG Download as WEBP Download as CSV barChart('submitter-users-year', 'https://stats.ega-archive.org/submitter/users/year', ['Submitter Accounts', 'Years'], true) DAC Members by Country The below figure represents the number of DAC members by country. DAC Members by Country Download as PNG Download as JPG Download as WEBP Download as CSV map pie mapChart('dac-members-by-country', 'https://stats.ega-archive.org/dac_member/country') pieChart('dac-members-by-country-pie-chart', 'https://stats.ega-archive.org/dac_member/country','DAC members by country')

  Documentation about/statistics/community

• Dataset for neuroendocrine_adrenal_tumor-RNA

  Rare cancer sequencing data of 145 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008862

• Characterisation of the genetic landscape of cutaneous leiomyoma and leiomyosarcoma - Leiomyoma WES

  Cutaneous leiomyoma (cLM) and leiomyosarcoma (cLMS) are rare benign and malignant soft tissue neoplasms showing smooth muscle differentiation, respectively, that arise from mesenchymal cells in the dermis and subcutis. Through whole exome sequencing of cLM and cLMS cases, we observed distinct differences between the somatic mutational profile of these tumour types. FH was identified as a driver gene in cLM with genetic alterations of FH occurring via somatic point mutation, somatic copy number loss, biallelic inactivation and germline point mutations. TP53 and RB1 were identified as driver genes in the cLMS cohort, with genetic alterations of TP53 occurring via somatic and germline point mutations, copy number loss and biallelic inactivation. Using RNA-sequencing, we identified recurrent gene fusions, including CRTC1/3-MAML2 in cLMS and a novel MYLK-MAP3K2 fusion. Analysis of the cell types present in the tumour microenvironment revealed a significantly increased presence of macrophages and decreased presence of myeloid dendritic cells in the cLMS cohort relative to the cLM cohort. Additionally, we identified common driver genes between cLMS and LMS from other sites. Thus, we provide the first in-depth profile of the genetic landscape of cLM and cLMS.

  Dataset EGAD00001014787

• Characterisation of the genetic landscape of cutaneous leiomyoma and leiomyosarcoma - Leiomyoma RNA

  Cutaneous leiomyoma (cLM) and leiomyosarcoma (cLMS) are rare benign and malignant soft tissue neoplasms showing smooth muscle differentiation, respectively, that arise from mesenchymal cells in the dermis and subcutis. Through whole exome sequencing of cLM and cLMS cases, we observed distinct differences between the somatic mutational profile of these tumour types. FH was identified as a driver gene in cLM with genetic alterations of FH occurring via somatic point mutation, somatic copy number loss, biallelic inactivation and germline point mutations. TP53 and RB1 were identified as driver genes in the cLMS cohort, with genetic alterations of TP53 occurring via somatic and germline point mutations, copy number loss and biallelic inactivation. Using RNA-sequencing, we identified recurrent gene fusions, including CRTC1/3-MAML2 in cLMS and a novel MYLK-MAP3K2 fusion. Analysis of the cell types present in the tumour microenvironment revealed a significantly increased presence of macrophages and decreased presence of myeloid dendritic cells in the cLMS cohort relative to the cLM cohort. Additionally, we identified common driver genes between cLMS and LMS from other sites. Thus, we provide the first in-depth profile of the genetic landscape of cLM and cLMS.

  Dataset EGAD00001014788

• Characterisation of the genetic landscape of cutaneous leiomyoma and leiomyosarcoma - Leiomyosarcoma WES

  Cutaneous leiomyoma (cLM) and leiomyosarcoma (cLMS) are rare benign and malignant soft tissue neoplasms showing smooth muscle differentiation, respectively, that arise from mesenchymal cells in the dermis and subcutis. Through whole exome sequencing of cLM and cLMS cases, we observed distinct differences between the somatic mutational profile of these tumour types. FH was identified as a driver gene in cLM with genetic alterations of FH occurring via somatic point mutation, somatic copy number loss, biallelic inactivation and germline point mutations. TP53 and RB1 were identified as driver genes in the cLMS cohort, with genetic alterations of TP53 occurring via somatic and germline point mutations, copy number loss and biallelic inactivation. Using RNA-sequencing, we identified recurrent gene fusions, including CRTC1/3-MAML2 in cLMS and a novel MYLK-MAP3K2 fusion. Analysis of the cell types present in the tumour microenvironment revealed a significantly increased presence of macrophages and decreased presence of myeloid dendritic cells in the cLMS cohort relative to the cLM cohort. Additionally, we identified common driver genes between cLMS and LMS from other sites. Thus, we provide the first in-depth profile of the genetic landscape of cLM and cLMS.

  Dataset EGAD00001014789

• Characterisation of the genetic landscape of cutaneous leiomyoma and leiomyosarcoma - Leiomyosarcoma RNA

  Cutaneous leiomyoma (cLM) and leiomyosarcoma (cLMS) are rare benign and malignant soft tissue neoplasms showing smooth muscle differentiation, respectively, that arise from mesenchymal cells in the dermis and subcutis. Through whole exome sequencing of cLM and cLMS cases, we observed distinct differences between the somatic mutational profile of these tumour types. FH was identified as a driver gene in cLM with genetic alterations of FH occurring via somatic point mutation, somatic copy number loss, biallelic inactivation and germline point mutations. TP53 and RB1 were identified as driver genes in the cLMS cohort, with genetic alterations of TP53 occurring via somatic and germline point mutations, copy number loss and biallelic inactivation. Using RNA-sequencing, we identified recurrent gene fusions, including CRTC1/3-MAML2 in cLMS and a novel MYLK-MAP3K2 fusion. Analysis of the cell types present in the tumour microenvironment revealed a significantly increased presence of macrophages and decreased presence of myeloid dendritic cells in the cLMS cohort relative to the cLM cohort. Additionally, we identified common driver genes between cLMS and LMS from other sites. Thus, we provide the first in-depth profile of the genetic landscape of cLM and cLMS.

  Dataset EGAD00001014790

• Targeted sequencing of diffuse large B-cell lymphoma tumour samples from the UK's Haematological Malignancy Research Network

  Targeted sequencing was applied to an unselected population-based diffuse large B-cell lymphoma cohort (n=928) diagnosed in the UK's Haematological Malignancy Research Network catchment population of ~4 million (14 centres). DNA extracted from tumour samples was sequenced with a 293-gene panel using the Illumina HiSeq 2500. All data are provided in the CRAM format.

  Dataset EGAD00001008616

• Genetic drivers of epigenetic and transcriptional variation of human immune responses to infection (RNA-seq, ATAC-seq and ChIPmentation)

  RNA-seq, ATAC-seq and ChIPmentation data from monocyte-derived macrophages that were infected with Influenza A virus strain PR8WT, or a matching non-infected control.

  Dataset EGAD00001008422

• NHLBI TOPMed: Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE)

  ECLIPSE was a longitudinal observational study of 2164 COPD subjects and a smaller number of smoking controls (337) and nonsmoking controls (245) followed regularly for three years, with three chest CT scans (at baseline, one year, and three years) (Vestbo et al., 2008, PMID: 18216052). Subjects were enrolled at clinical centers in the US, Canada, Europe, and New Zealand. Inclusion criteria included subjects ages 40-75, at least 10 pack-years of smoking, and spirometry in GOLD grades 2-4 (COPD cases) or normal spirometry with post-bronchodilator FEV1 >85% (predicted) and FEV1/FVC>0.7 (controls). Study visits were performed at enrollment, three months, and every six months thereafter with spirometry, questionnaires, and other clinical evaluations. The ECLIPSE CT scans have been analyzed with the VIDA software for emphysema and airway phenotypes. ECLIPSE has provided key insights into the clinical epidemiology of COPD, including COPD exacerbations (Hurst, et. al., 2010, PMID: 20843247) and lung function decline in COPD (Vestbo, et. al., 2011, PMID: 21991892). ECLIPSE has been used in a number of genetic studies of COPD susceptibility and protein biomarkers (Faner, et. al., 2014, PMID: 24310110). Genome-wide gene expression microarray data are available in 147 induced sputum samples from COPD subjects and 248 peripheral blood samples from COPD and control subjects. Phenotype data for ECLIPSE subjects is available through dbGaP phs001252.

  Study phs001472

• RRBS data (cfSort study) from noncancer tissue DNA

  The RRBS libraries of the genomic DNA from the 521 tissue samples were constructed following the standard RRBS protocol. 100-200 ng of intact genomic DNA in the volume of 21.5 µl was used as input material. Restriction digestion was done with 2.5 µl 10xCutSmart buffer and 1 µl MspI (NEB) for 18 h at 37 oC and 20 min at 65 oC. 0.5 µl 10xCutSmart buffer, 0.3 µl dACGTP mixture (100 mM dATP, 10 mM dCTP, 10 mM dGTP), 1 µl Klenow (exo-, 5U/µl, NEB) and 2.6 µl RT-PCR water, 0.6 µl 50 mM DTT (ThermoFisher) was added to the mixture for end repair and A-overhang addition with the program 30 oC for 20 min, 37 oC for 1 h and 75 oC for 20 min. Adapter ligation was then performed with 1 µl 10xThermoFisher HC T4 ligase buffer, 0.4 µl 100 mM ATP (ThermoFisher), 0.2 µl 50 mM DTT, 1 µl ThermoFisher HC T4 DNA ligase (30 Weiss Unit/µl), 30 ng home-made duplex UMI adapter with all the cytosines methylated (protocol adopted from Kennedy et al.) at 16 oC for 20 h and 65 oC for 20 min. Bisulfite conversion of the adapter-ligated product was carried out with QIAGEN EpiTect plus DNA bisulfite kit following their protocol for two rounds of conversion. The converted product was purified with Qiagen MinElute spin column and eluted with 20 µl RT-PCR water. PCR amplification was done using the NEBNext Multiplex Oligos for Illumina (2.5 µl of universal and index primer each) and 25 µl KAPA HiFi HotStart Uracil+ ReadyMix (Roche) with the following cycling conditions: 98 oC for 45 s, 9 cycles of 98 oC for 15 s, 60 oC for 30 s and 72 oC for 30 s, followed by a final extension at 72 oC for 5 min. The PCR product was purified with 1x AmpureXP beads and eluted with 30 µl EB buffer. DNA concentration was measured by Qubit 1xdsDNA HS assay. 5% TBE-UREA PAGE and bioanalyzer assay was performed as quality control on each library before sequencing.

  Dataset EGAD00001010880

• A Tumour Organoid Biobank for Mapping Cancer Cell Vulnerabilities - WGS

  Whole genome sequencing data from cancer patient-derived organoids and their matched tumour tissue samples. Part of a study to include genomic and transcriptomic sequencing data, along with CRISPR screening data from cancer patient-derived organoids and matched tumour tissues. Some organoids were developed as part of the Human Cancer Models Initiative (HCMI) in collaboration with Cancer Research UK (CRUK). The study includes organoids derived from colorectal, oesophageal, ovarian, pancreatic, and stomach cancer samples.

  Dataset EGAD00001015469

• The Dutch Microbiome Project Batch 1

  The Dutch Microbiome Project (DMP) data includes shotgun metagenomic sequencing of faecal samples 8,208 Dutch individuals. Paired-end sequencing was performed using Illumina HiSeq 2000 platform. Data is archived in two batches to facilitate easier data access and upload to EGA. Batch 1 of DMP includes 4396 samples.

  Dataset EGAD00001007027

• cfMethyl-seq data (cfSort study) from serial plasma samples of NSCLC patients

  The cfMethyl-Seq libraries of the serial plasma cfDNA samples from the four NSCLC patients were constructed following the standard protocol. 10 ng of cfDNA in the volume of 25 µl was used as input material. 5’-end dephosphorylation was done with 3 µl 10xCutSmart buffer and 2 µl quick CIP from NEB (Ipswich, MA) at 37 oC for 30 min then heat-inactivated at 80 oC for 5 min. The 3’-end blocking was done with 0.5 µl 10xCutSmart buffer, 3 µl 2.5 mM CoCl2, 1 µl terminal transferase (all from NEB), and 0.5 µl 1 mM ddGTP at 37 oC for 2 h followed by 75 oC for 20 min. The mixture was then purified with 2x AmpureXP beads (Beckman Coulter, Indianapolis, IN) and eluted in 21.5 µl RT-PCR grade water (Thermo-Fisher, Waltham, MA). Restriction digestion was done with 2.5 µl 10xCutSmart buffer and 1 µl MspI (NEB) for 18 h at 37  oC and 20 min at 65 oC . 0.5 µl 10xCutSmart buffer, 0.3 µl dACGTP mixture (100 mM dATP, 10 mM dCTP, 10 mM dGTP), 1 µl Klenow (exo-, 5U/µl, NEB) and 2.6 µl RT-PCR water, 0.6 µl 50 mM DTT (ThermoFisher) was added to the mixture for end repair and A-overhang addition with the program 30  oC for 20 min, 37 oC for 1 h and 75 oC for 20 min. Adapter ligation was then performed with 1 µl 10xThermoFisher HC T4 ligase buffer, 0.4 µl 100 mM ATP (ThermoFisher), 0.2 µl 50 mM DTT, 1 µl ThermoFisher HC T4 DNA ligase (30 Weiss Unit/µl), 5 ng home-made duplex UMI adapter with all the cytosines methylated (protocol adopted from Kennedy et al.) at 16 oC for 20 h and 65 oC for 20 min. Bisulfite conversion of the adapter-ligated product was carried out with QIAGEN EpiTect plus DNA bisulfite kit following their protocol for two rounds of conversion. The converted product was purified with Qiagen MinElute spin column and eluted with 20 µl RT-PCR water. PCR amplification was done using the NEBNext Multiplex Oligos for Illumina (2.5 µl of universal and index primer each) and 25 µl KAPA HiFi HotStart Uracil+ ReadyMix (Roche) with the following cycling conditions: 98  oC for 45 s, 15 cycles of 98  oC for 15 s, 60  oC for 30 s and 72  oC for 30 s, followed by a final extension at 72  oC for 5 min. The PCR product was purified with 1x AmpureXP beads and eluted with 30 µl EB buffer. DNA concentration was measured by Qubit 1xdsDNA HS assay. 5% TBE-UREA PAGE and bioanalyzer assay was performed as quality control on each library before sequencing.

  Dataset EGAD00001010881

• 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

• RNAseq data for Failure of Differentiation of the Rhombic Lip Constitutes Medulloblastoma

  We used single-cell transcriptomics to study cells from the developing human cerebellum, and show that different molecular subgroups of medulloblastoma resemble distinct glutamatergic progenitors.

  Dataset EGAD00001008458

• ICGC Data Access Compliance Office

  To access Controlled Access ICGC data at the EGA you must first apply for access on the DACO form. Instructions on this process is available from this web site: http://docs.icgc.org/portal/access/

  Dac EGAC00001000010

• Next Generation Children project

  Whole genome sequencing of sick children in neonatal and paediatric intensive care units, aligned to reference assembly GRCh38.

  Dataset EGAD00001007868

• Solve-RD_RND_cohort-1_DF1+2_V1

  Solve-RD data submitted to the ERN-RND cohort for re-analysis (Data freeze 1+2) v1

  Dataset EGAD00001009769

• Dataset for Sarcoma RNA sequencing linked from study EGAS00001004813

  Sequencing data of 410 sarcoma tumor runs, which were uploaded to EGAS00001004813. The sequencing was always paired.

  Dataset EGAD00001010276

• Small RNA sequencing of endometrial cancer patients with samples collected prior to diagnosis and controls

  This dataset contains unpaired FASTQ files of 316 endometrial cancer cases and 316 matched controls representing circulating RNAs. RNA count files are provided as the output of sncRNA pipeline and represent 12 RNA types (isomiR, lncRNA, precursor miRNA, miRNA, miscRNA, mRNA, piRNA, scaRNA, snoRNA, snRNA, tRF, and tRNA). We also provide metadata of the samples.

  Dataset EGAD50000000391

• Whole Genome Sequencing and Variant Calling for Autism Families

  We extracted DNA from whole blood or lymphoblast-derived cell lines and assessed the DNA quality with PicoGreenTM and gel electrophoresis. Whole genome sequencing was performed (Illumina HiSeq2000 and Illumina HiSeq X). WGS reads were mapped to the human reference genome assembly hg19 (GRCh37) using Burrows-Wheeler Aligner v.0.7.12 (TCAG) or Isaac v.2.0.13 (Macrogen). For each genome, we performed local realignment and quality recalibration and detected SNVs and small indels using GATK Haplotype Caller v.3.4.6 without genotype refinement. We detected CNVs using ERDS (estimation by read depth with single nucleotide variants) and CNVnator. We detected structural variants using Manta v.0.29.6. When available by the variant caller (i.e. GATK and Manta), trio-based joint variant calling was conducted for each family.

  Dataset EGAD00001008452

• Solve-RD_ITHACA_cohort-1_DF1+2_V1

  Solve-RD data submitted to the ERN-ITHACA cohort for re-analysis (Data freeze 1+2) v1

  Dataset EGAD00001009770

• BC Cancer, part of the Provincial Health Services Authority, Technology Development Office, Data Access Committee (PHSA TDO DAC)

  Access to data generated by BCCA is made available by completing the data access agreement for review by the data access committee and will be granted to qualified investigators for appropriate use.

  Dac EGAC00000000011