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• Out with the Java, in with the Python - new EGA data download client unveiled

  We will shortly be deprecating the Java-based download client also known as API V2. The Java client began its life at the back end of 2014, and during its time has seen many developments that have served our users well. During its tenure, the Java client enabled distribution of over 6.5 million files totalling nearly 15 petabytes of data to researchers around the globe. Recent increases in genomic and phenotypic data file sizes, the number of datasets archived in the EGA, the number of users downloading data, and the diversity of download locations has meant that at times the Java client struggled to distribute data efficiently. In response, our team of developers have built a new download client with more robust features and better functionality and reliability. Enter stage left our shiny new API V3.1! The new API V3.1 will replace both API V2 and API V3. The download client for the new API V3.1 is written in Python, and the code is openly available on Github. This Python client makes https calls to the EGA AAI (https://ega.ebi.ac.uk:8443/) and to the EGA Data API (https://ega.ebi.ac.uk:8052), both of which must be accessible from the client location. In addition to general updates to improve performance, the API V3.1 has three new features enhancing the EGA distributions services. First, requested data are now downloaded over secure https connections rather than http, meaning that data can be delivered unencrypted. Instead of separately requesting, downloading, and decrypting data using the Java client, data can now be requested and downloaded using a single command without the need for decrypting. The API V3.1 also automatically verifies each file’s unencrypted md5 after download to ensure the file has downloaded correctly. Second, the new API supports segmenting and automatic resuming. To enable quicker download speeds, the API breaks files into up to four segments and downloads them in parallel. With the new resume feature, downloads - both segmented and continuous stream - will automatically resume if they encounter any errors or the connection is interrupted. These features result in both a faster and more reliable download experience. Finally, the new API V3.1 implements the GA4GH-compliant htsget protocol for supporting requests over genomic ranges. This exciting new feature means that for data files with accompanying index files (e.g. .crai for CRAM files) users can download specific regions of interest rather than the entire file saving both time and storage space. The new features of the Python-based API V3.1 represent significant improvements in security, speed, reliability, and flexibility that are sure to provide a better data download experience. To take full advantage of these features, users must update to Python 3.X. Considering the changes in the data structures with the new API, the upgrade to a new version of the Python client is also mandatory. Updating the client to the latest version can be achieved by running the following command: pip3 install pyega3 -U We are excited for users to try out the new features and take advantage of the multifariously growing EGA distribution services for human biomedical omics data. If you have any questions or feedback, please email the EGA Helpdesk team. We'd love to hear from you!

  Blog new-ega-data-download-client

• A genome scan for genes underlying adult body size differences between Central African hunter-gatherers and farmers.

  The evolutionary and biological bases of the Central African pygmy phenotype, a characteristic of rainforest huntergatherers defined by reduced body size compared with neighboring farmers, remain largely unknown. Here, we perform a joint investigation in Central African hunter-gatherers and farmers of adult standing height, sitting height, leg length, and body mass index (BMI), considering 358 hunter-gatherers and 169 farmers with genotypes for 153,798 SNPs. In addition to reduced standing heights, hunter-gatherers have shorter sitting heights and leg lengths and higher sitting/standing height ratios than farmers and lower BMI for males. Standing height, sitting height, and leg length are strongly correlated with inferred levels of farmer genetic ancestry, whereas BMI is only weakly correlated, perhaps reflecting greater contributions of non-genetic factors to body weight than to height. Single- and multi-marker association tests identify one region and eight genes associated with hunter-gatherer/farmer status, and 24 genes associated with the height-related traits. Many of these genes have putative functions consistent with roles in determining their associated traits and the pygmy phenotype, and they include three associated with standing height in non-Africans (PRKG1, DSCAM, MAGI2). We find evidence that European height-associated SNPs or variants in linkage disequilibrium with them contribute to standing- and sitting-height determination in Central Africans, but not to the differential status of hunter-gatherers and farmers. These findings provide new insights into the biological basis of the pygmy phenotype, and they highlight the potential of cross-population studies for exploring the genetic basis of phenotypes that vary naturally across populations. Pemberton et al. Human Genetics 2018 https://doi.org/10.1007/s00439-018-1902-3

  Study EGAS00001002975

• A molecular cell atlas of the human lung from single cell RNA sequencing

  Although single cell RNA sequencing studies have begun providing compendia of cell expression profiles, it has proven more difficult to systematically identify and localize all molecular cell types in individual organs to create a full molecular cell atlas. Here we describe droplet- and plate-based single cell RNA sequencing applied to ~75,000 human lung and blood cells, combined with a multi-pronged cell annotation approach, which have allowed us to define the gene expression profiles and anatomical locations of 58 cell populations in the human lung, including 41 of 45 previously known cell types or subtypes and 14 new ones. This comprehensive molecular atlas elucidates the biochemical functions of lung cell types and the cell-selective transcription factors and optimal markers for making and monitoring them; defines the cell targets of circulating hormones and predicts local signaling interactions including sources and targets of chemokines in immune cell trafficking and expression changes on lung homing; and identifies the cell types directly affected by lung disease genes and respiratory viruses. Comparison to mouse identified 17 molecular types that appear to have been gained or lost during lung evolution and others whose expression profiles have been substantially altered, revealing extensive plasticity of cell types and cell-type-specific gene expression during organ evolution including expression switches between cell types. This atlas provides the molecular foundation for investigating how lung cell identities, functions, and interactions are achieved in development and tissue engineering and altered in disease and evolution.

  Study EGAS00001004344

• Whole genome sequencing of tumor samples from advanced pre-treated NSCLC patients recruited in a phase I/II single-arm trial utilising CVA21, an oncolytic coxsackie virus, in combination with pembrolizumab.

  Acquired or de novo resistance to immune checkpoint inhibitors occurs in the majority of advanced non-small cell lung cancers (NSCLC). There is an unmet need to improve outcomes for patients with this condition. Oncolytic viruses represent an attractive treatment approach due to their dual activity in inducing tumor cell lysis directly and potentially augmenting anti-tumor immunity. Here, we present the safety, efficacy and translational findings from a phase I/II single-arm trial utilising CVA21, an oncolytic coxsackie virus, in combination with pembrolizumab in patients with advanced pre-treated NSCLC. We performed paired biopsies pre- and post-treatment in 10 patients who received intravenous CVA21 and pembrolizumab, 8 of whom had prior treatment with immune checkpoint inhibitor (ICI) therapy. Whole genome sequencing and spatial proteomics were performed to comprehensively characterise the response to CVA21. Combination CVA21/pembrolizumab (anti PD-1) therapy was well tolerated with no serious treatment-related adverse events. Partial responses were seen in two patients with prior acquired anti-PD-1 resistance and disease stabilisation in 6 patients, giving a clinical benefit rate of 80%. High baseline tumor mutational burden and PD-L1 expression were observed in patients with better response to treatment. Interestingly, an increase in antigen presentation and CD8+ T cell infiltration was observed on treatment compared with baseline in patients with better progression-free survival. This study demonstrates the potential of CVA21 to modulate the immunogenicity of tumor cells and remodelling the tumor microenvironment, providing novel insights for patient selection for trials involving novel immunotherapeutic approaches.

  Study EGAS00001008258

• Netherlands Cancer Institute (NKI-AVL) general DAC

  Data is available under reasonable request. All data requests will be reviewed by the NKI IRB and must be supported by the Principal Investigator of the study. The researcher will need to sign a data access agreement with the NKI after approval. Go to https://ega.nki.nl to fill out the form to request access.

  Dac EGAC50000000055

• WGS analysis of a glioma initiating cell line

  We here obtained whole-genome sequencing data to analyze transcription factor binding sequences and somatic mutations found in our RNA-seq analysis of glioma initiating cells.

  Study JGAS000096

• PRPH2-Related Retinal Dystrophies: Mutational Spectrum in 103 Families from a Spanish Cohort

  Various NGS experiments from patients affected by genomic variants at gene PRPH2, one of the most frequently inherited retinal dystrophy (IRD)-causing genes.

  Study EGAS50000000847

• The life-saving benefit of dexamethasone in severe COVID-19 is linked to a reversal of monocyte dysregulation

  Assessment of dexamethasone response in human lung through scRNA-seq analysis of bronchoalveolar lavage (BAL) samples from patients with severe COVID-19.

  Study EGAS50000000203

• ASPSCR1-TFE3 gene fusion panel deep amplicon sequencing data

  Dataset contains compressed, paired-end Fastq files of deep amplicon sequencing data from a custom ASPSCR1-TFE3 gene fusion panel for three alveolar soft part sarcoma cases described in "Development and first-in-human CAR T therapy targeting the pathognomonic MiT-fusion driven protein GPNMB".

  Dataset EGAD50000002438

• Exome dataset of ALK study

  Here we sequenced biopsies from a patient with ALK-positive NSCLC progressing on first-line lorlatinib. This dataset contains one Exome-seq (the tumor and its normal). This aims to investigate the impact of the K1150dup mutation on lorlatinib progression and to explore potential therapeutic strategies to overcome resistance.

  Dataset EGAD50000002554

• RNA-seq

  The RNA was extracted using the AS1390 PROMEGA kit according to the manufacturer’s instructions. The samples underwent sequencing using a Novaseq 6000 machine, equipped with an SP 200 cycles v1.5 cartridge. The sequencing process varied slightly across batches based on the input RNA and the library preparation kits used.

  Dataset EGAD50000002023

• WGS data for Pancreatic Cancer samples (misc.)

  WGS data for pancreatic cancer samples. These are miscellaneous samples which are part of a tandem duplicator phenotype paper (Farooq et al, NPJ Precision Oncology, 2025). The dataset includes tumour and normal BAM files sequenced on Illumina NovaSeq 6000 and aligned against GRCh38 (n=7 tumour/normal pairs).

  Dataset EGAD50000001833

• Exome Sequencing data from infertility cases.

  This dataset includes exome sequencing (ES) from a cohort of patients with infertility. Sequencing was performed on genomic DNA extracted from blood, using Agilent SureSelect XT Low Input exome capture and Illumina NovaSeq 6000 paired-end sequencing and is intended to facilitate research into novel genetic causes of infertility.

  Dataset EGAD50000001881

• HIV-phyloTSI: BEEHIVE

  This dataset includes sample numbers TSI_0203 to TSI_0315 for the BEEHIVE cohort of the study. Samples were sequenced using the Illumina NovaSeq system and the veSEQ-HIV method (see Bonsall, Golubchik et al 2020, DOI: 10.1128/JCM.00382-20). Each sample has a BAM file, and its associated reference file.

  Dataset EGAD50000001310

• Melanoma transcriptomic data from patients undergoing immunotherapy

  This dataset contains raw RNA sequencing data from melanoma patient tumor samples collected before and during immunotherapy. The data support investigation of treatment-related changes in tumor cell populations. Samples were analyzed as part of a study exploring cellular responses to immune-based therapies.

  Dataset EGAD50000001569

• Shallow Whole Genome Sequencing (sWGS) from REPEAT trial

  Samples associated to: "A phase Ib/II study of regorafenib and paclitaxel in patients with beyond first-line advanced esophagogastric carcinoma (REPEAT)". sWGS from 97 Esophagogastric Carcinoma samples. sWGS was done to carry out Copy Number Analysis. Dataset includes: .fastq, .bam and .bai files.

  Dataset EGAD50000001161

• SMPaeds PanelSeq of tumour tissue

  Deep sequencing of a targeted panel of 92 paediatric cancer related genes or 233 pan-cancer related genes for both relapse/archival disgnostic tumour tissue and germline DNA from whole blood cell pellet. Tumour tissue was sequenced to approximately 400X coverage and germline DNA was sequences to aproximately 100X coverage.

  Dataset EGAD50000000783

• Pregnancy-associated melanoma

  The aim of this project is to assess differences in intratumoral immune composition in pregnant melanoma patients versus non pregnant melanoma controls. Samples (N=25) were obtained from a local patient database. From archived FFPE we isolated RNA and performed NGS and bio-informatica data-analysis.

  Dataset EGAD50000000706

• Exome sequencing analysis of BCP-LBL patients samples

  In order to perform comprehensive SNV and CNA analyses of a cohort of BCP-LBL patients, we performed whole exome sequencing of 41 tissue samples from BCP-LBL patients. Because the material was available as FFPE, the target coverage of the samples was >200x.

  Dataset EGAD50000000418

• ImmuNEO CD8 cell lines

  Paired RNA-Seq data from 16 samples of different tumors CD8+ T cells added to the study "Proteogenomic analysis reveals RNA as a source for tumor-agnostic neoantigen identification (H021)". Sequencing was performed on Illumina NextSeq 500. The sequencing was always paired

  Dataset EGAD50000000193

• Clones derived from early passage tumoroids of colorectal cancer

  We obtained different clones from early passage CRC tumoroids to study mutational signatures specific for truncal or private somatic alterations. These whole genome sequences are part of a larger study on the heterogeneity and evolution of DNA mutation rates in microsatellite-stable colorectal cancer.

  Dataset EGAD50000000152

• A novel orthotopic patient-derived xenograft model of radiation-induced glioma following medulloblastoma

  DNA methylation arrays were performed to molecularly subtype these samples based on Capper D, Jones DTW, Sill M, et al. DNA methylation-based classification of central nervous system tumours. Nature. 2018;555(7697):469-474. doi:10.1038/nature26000

  Dataset EGAD00010002017

• Tel Aviv RNA-seq dataset of of BiPSCs and FiPSCs derived cells

  RNA-seq data obtained from directed differentiation of a subset of FiPSCs and BiPSCs cell lines towards islet-like cells. RNA was collected at two key developmental stages: definitive endoderm (DE) and pancreatic progenitors (PP).

  Dataset EGAD00001003780

• Genome-wide data of Erasmus Rucphen Family (ERF) Study

  The data consists of 678189 genome-wide polymorphic variants of 3658 individuals from ERF/GRIP region in a variant call format (vcf) file. ERF has been genotyped with different genotyping platform: Illumina 318 k, 350 k, 610 k and Affymetrics 200 k.

  Dataset EGAD00001003571

• RNA sequencing data to study therapeutic targeting of ependymoma

  This dataset conatains RNA sequencing data from 24 patients. Up to two lanes per tumour sample have been seqeunced on a Illumina HiSeq2000 instrument in paired-end mode resulting in 58 Fastq files.

  Dataset EGAD00001003966