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• Transcriptomics for LUNG-NSCLC2 cohort

  The goal of IMMUcan is to understand how the immune system interacts with tumors and how therapeutic interventions influence this interaction. This cohort includes patients with non-small cell lung cancer who had surgical resection. This is a subcohort of the EORTC SPECTAlung study. This dataset contains transcriptomics data processed with the STAR pipeline. Two sequencing kits were employed: Roche KAPA for high-quality RNA samples and Takara SMART-Seq Stranded for samples with limited RNA quantities.

  Dataset EGAD50000002236

• WES of pleomorphic lung cancer

  Pulmonary pleomorphic carcinoma (PPC) is an aggressive and highly heterogeneous non-small-cell lung carcinoma whose underlying biology is still poorly understood. Forty-two tumor areas including 39 primary tumors and 3 metastases from 20 PPC patients were microdissected and the histologically distinct components were subjected to whole exome sequencing (WES) separately. Twist Human Core Exome + RefSeq + Mito-Panel kit (Twist Bioscience) was used for the whole exome capturing according to manufacturer’s guidelines. Paired-end 100-bp reads were generated on the Illumina NovaSeq 6000. After the sequencing, reads were aligned against the reference human genome GRCh38 using Burrows-Wheeler Aligner (BWA, v0.7.12)

  Dataset EGAD50000000453

• Gut metagenome/FR 2002

  The main goal of the project is the study the associations between the gut metagenome and human health. The dataset contains data for n=7211 FINRISK 2002 participants who underwent fecal sampling. Demultiplexed shallow shotgun metagenomic sequences were quality filtered and adapter trimmed using Atropos (Didion et al., 2017), and human filtered using Bowtie2 (Langmead and Salzberg, 2012).

  Study EGAS00001005038

• GenomeDenmark Phase 2 - MHC haplotypes

  The MHC vcf call set was generated using a modified AsmVar and BayesTyper pipeline. In contrast to the original pipeline, where variant calling is performed using alignment of collapsed assemblies to a reference genome, the MHC call set was produced using alignment of phased MHC haplotypes. Two iterations of BayesTyper was run, a first iteration for each haplotype seperately and a second iteration performing joint variant calling on all haplotypes. The sample IDs for the fathers and mothers are TrioID-01 and TrioID-02, respectively, and the IDs for the children are TrioID-0x, where x is a number between 3 and 7.

  Dataset EGAD00001003455

• RNA-seq of Liver Cancer

  The present series corresponds to 161 RNA-seq samples from tumors with matched WES or WGS. Hepatocellular carcinoma (HCC) accounts for more than 90% of liver cancers, and is a major health problem. It is the 3rd cause of cancer-related mortality. Advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. Thus, the development of next-generation sequencing technologies has made it possible to generate more comprehensive catalogues of somatic alteration events (single nucleotide substitutions, structural variations, and epigenetic changes) in liver cancer genome than ever before.

  Dataset EGAD00001003993

• Native American Ancient DNA sequencing

  The morphology of the first humans in the Americas (Paleoamericans) differs from that of Native Americans, and has raised the question of whether or not there are also differences in origin or genetics. A few populations who survived until relatively recently have been suggested to retain Paleoamerican morphology. One of these populations is from La Jolla. Here, we have generated genome sequence data from four La Jolla individuals in order to investigate these questions 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 EGAD00001002144

• Whole Exome Sequencing data of glioma from the Chinese Glioma Genome Atlas (CGGA) project

  Glioma is the most common and aggressive brain cancer in adults. While primary glioma has been widely studied, molecular characterization of recurrent glioma is still rare. The high-quality sequencing data that we generated provides a useful resource for the community. The CGGA project contains over 2,000 samples from Chinese cohorts. It totally includes the whole-exome sequencing (286), DNA methylation (159), mRNA sequencing (1,018), mRNA microarray (301) and microRNA microarray (198) and matched clinical data. CGGA removes the barriers to researchers, providing rapid and convenient access to high-quality functional genomic data resources for biological research and clinical applications.

  Dataset EGAD00001006445

• BRCA2, ATM, and CDK12 defects differentially shape prostate tumor driver genomics and clinical aggression

  This dataset contains all available targeted exon sequencing bam files from our study, "BRCA2, ATM, and CDK12 defects differentially shape prostate tumor driver genomics and clinical aggression". Patient identifiers are denoted by the first segment of the sample aliases (e.g. "P1"), and additional information is appended to reflect which sample is referenced. These include serial cfDNA samples ("-1", "-2", "-3", etc.), paired white blood cell or benign tissue control samples ("-Control"), or primary archival tissue samples derived from a diagnostic biopsy, prostatectomy, or transurethral resection of the prostate ("-Tissue"). All samples were sequenced using Illumina technology.

  Dataset EGAD00001006733

• Test dataset with ligh-weight files

  This is a test dataset derived from public data of the 1000 Genomes Project. Its purpose is not to allow for any inference about cohort data or results, but to aid bioinformaticians in the technical development and testing of tools, as well as data consumers in learning how to access information. This dataset consists of 3 pairs of light-weight (sliced) files: BAM + BAI, CRAM + CRAI and VCF + TBI. These files can be downloaded directly through the EGA-download-client PyEGA3 (https://github.com/EGA-archive/ega-download-client). For any further questions, please contact the DAC (Helpdesk - email: helpdesk [at] ega-archive [dot] org).

  Dataset EGAD00001009826

• 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