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• RNA seq before and after cold pressor test

  The cold pressor test (CPT) is a widely used pain provocation test to investigate both pain tolerance and cardiovascular responses. Twenty-two females were phenotypically assessed before and after a CPT, and blood samples were taken for RNA-sequencing.

  Study EGAS00001006690

• DETECT-A NGS Data Batch 3

  This batch is a subset of the full DETECT-A dataset, containing 29294 fastq files generated from 3653 subjects. All sequencing was conducted using Illumina HiSeq 4000 and Illumina MiSeq platforms. Note that the division into batches follows no specific criteria and that the sequencing data for each subject has multiple files which may span multiple datasets. Thus, for a comprehensive analysis, it is recommended to request access to all datasets that comprise this study.

  Dataset EGAD00001008597

• DETECT-A NGS Data Batch 2

  This batch is a subset of the full DETECT-A dataset, containing 498 fastq files generated from 71 subjects. All sequencing was conducted using Illumina HiSeq 4000 and Illumina MiSeq platforms. Note that the division into batches follows no specific criteria and that the sequencing data for each subject has multiple files which may span multiple datasets. Thus, for a comprehensive analysis, it is recommended to request access to all datasets that comprise this study.

  Dataset EGAD00001008591

• DETECT-A NGS Data Batch 5

  This batch is a subset of the full DETECT-A dataset, containing 12740 fastq files generated from 3211 subjects. All sequencing was conducted using Illumina HiSeq 4000 and Illumina MiSeq platforms. Note that the division into batches follows no specific criteria and that the sequencing data for each subject has multiple files which may span multiple datasets. Thus, for a comprehensive analysis, it is recommended to request access to all datasets that comprise this study.

  Dataset EGAD00001015426

• DETECT-A NGS Data Batch 1

  This batch is a subset of the full DETECT-A dataset, containing 43963 fastq files generated from 3024 subjects. All sequencing was conducted using Illumina HiSeq 4000 and Illumina MiSeq platforms. Note that the division into batches follows no specific criteria and that the sequencing data for each subject has multiple files which may span multiple datasets. Thus, for a comprehensive analysis, it is recommended to request access to all datasets that comprise this study.

  Dataset EGAD00001008415

• DETECT-A NGS Data Batch 4

  This batch is a subset of the full DETECT-A dataset, containing 25210 fastq files generated from 3040 subjects. All sequencing was conducted using Illumina HiSeq 4000 and Illumina MiSeq platforms. Note that the division into batches follows no specific criteria and that the sequencing data for each subject has multiple files which may span multiple datasets. Thus, for a comprehensive analysis, it is recommended to request access to all datasets that comprise this study.

  Dataset EGAD00001015360

• DETECT-A NGS Data Batch 6

  This batch is a subset of the full DETECT-A dataset, containing 9 fastq files generated from 8 subjects. All sequencing was conducted using Illumina HiSeq 4000 and Illumina MiSeq platforms. Note that the division into batches follows no specific criteria and that the sequencing data for each subject has multiple files which may span multiple datasets. Thus, for a comprehensive analysis, it is recommended to request access to all datasets that comprise this study.

  Dataset EGAD00001015458

• Investigating Host Genetic Risk Factors for Tuberculosis in Highly Endemic South African Populations

  It is apparent from our recent population genetic and admixture mapping work 1–3 that a substantial part of the ancestral input into the South African Coloured (SAC) population is from the San or Khoe groups, which are not well represented in publicly available genetic databases. It is a reasonable assumption that the SAC population in the Western Cape may have derived more genetic input from the present KhoeSan population in the Northern Cape than the San residing in Namibia. It was concluded by our group that it is indeed the southern African KhoeSan group, the ≠Khomani, that best represent the KhoeSan contribution seen in the SAC 4. More recently, it has been shown that there are ancestry related increases in TB susceptibility, especially with increased Bantu-speaking African and KhoeSan ancestry 5. We aim to elucidate the epidemiological and human-host genetic risk factors for TB and the immunological pathways modulating TB infection. The proposed sub-study will enroll people evaluated for TB at Northern Cape community health clinics and their contacts from their households and/or community. We will conduct a demographic interview, collect saliva, which will be used for genetic analysis, and blood to determine latent TB infection status and capture immunological responses to mycobacterial infections at the cellular level and RNA sequencing.

  Study EGAS00001007850

• Genetic immune escape landscape in primary and metastatic cancer

  Immune surveillance escape is a hallmark of tumorigenesis1. Multiple studies have characterized the immune escape landscape across several untreated early-stage primary cancer types2–4. However, whether late-stage treated metastatic tumors present differences in genetic immune escape (GIE) prevalence and dynamics remains unclear. Here, we performed a pan-cancer characterization of GIE prevalence across six immune escape pathways in 6,457 uniformly processed Whole Genome Sequencing (WGS) tumor samples including 58 cancer types from 1,943 primary untreated patients and 4,514 metastatic patients. To effectively address the complexity of the Human Leukocyte Antigen (HLA-I) locus and to characterize its tumor status, we developed LILAC, an open-source integrative framework. We demonstrate that one in four tumors harbor GIE alterations, with high mechanistic and frequency variability across cancer types. GIE prevalence is highly consistent between primary and metastatic tumors for most cancer types with few exceptions such as prostate and thyroid carcinomas that have increased immune evasion frequencies in metastatic tumors. Positive selection analysis revealed that GIE alterations are frequently selected for in tumor evolution and that focal LOH of HLA-I, unlike non-focal LOH of HLA-I, tends to lose the HLA allele that presents the largest neoepitope repertoire. We also unraveled tumor genomic features contributing to immune escape incidence, including DNA repair deficiency, APOBEC activity, tobacco associated mutation load and viral DNA integration. Finally, there is a strong tendency for mid and high tumor mutation burden (TMB) tumors to preferentially select LOH of HLA-I for GIE whereas hypermutated samples favor global immune evasion strategies. Our results indicate that genetic immune escape is generally a pre-metastatic event during tumor evolution and that tumors adapt different strategies depending on their neoepitope burden.

  Study EGAS00001006123

• Liquid Biopsy Detection of Tumor-specific Structural Variants in High Grade Serous Ovarian Cancer

  WGS Liquid Biopsy. Recurrence is frequent for most patients with high grade serous ovarian cancer (HGSOC), even after effective chemotherapy induced remission. However, after achievement of complete clinical response, the minimal residual disease is often insufficient for genomic analysis. Therefore, methods to interrogate the clonal composition and molecular properties of minimal residual disease are needed to better understand the mechanisms of HGSOC relapse. To address this unmet need, we developed and validated a novel cfDNA-based approach for tracking disease burden using NGS-informed tumor specific structural variants (SVs). Methods: The optimization of the methodology was first performed using synthetic cfDNA generated by ultrasonication of gDNA from ovarian cancer cell lines. Following the optimized workflow, whole genome sequencing of multisite biopsies from pre-treatment HGSOC patients were performed and high confidence SVs were called by consensus of multiple published SV callers. Real-time PCR and digital droplet PCR (ddPCR) were used for assays development.

  Study EGAS50000001044