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• Roche Alzheimer's dataset

  The Roche Alzheimer’s disease dataset (Roche_AD) consists of 80 samples from 40 unique individuals (one sample from the temporal cortex and one from deep white matter for each individual, 12 cases, 25 controls, 3 dementia). A total of 12,000 estimated cells from each sample were loaded on the 10x Single Cell Next GEM G Chip. cDNA libraries were prepared using the Chromium Single Cell 3’ Library and Gel Bead v3 kit according to the manufacturer’s instructions. cDNA libraries were sequenced using the Illumina NovaSeq 6000 System and NovaSeq 6000 S2 Reagent Kit v1.5 (100 cycles), aiming at a sequencing depth of minimum 30K reads/nucleus.

  Dataset EGAD00001009166

• Characterization of mutational signatures in human cancer cell lines reveals episodic APOBEC mutagenesis

  Multiple signatures of somatic mutations have been identified in human cancer genomes. To investigate whether mutational signatures continue to be generated, and if so their temporal patterns of activity, subsets of cell lines were cultured in vitro for extended periods and subjected to single cell cloning and whole genome or exome sequencing or directly to single cell whole genome sequencing. As expected, signatures of past exogenous exposures, such as tobacco smoke and ultraviolet light, were not generated in vitro. In contrast, signatures of normal and defective DNA repair and replication continued to be generated at essentially constant mutation rates. Signatures of APOBEC cytidine deaminase DNA-editing activity exhibited a distinctive pattern with substantial fluctuations in mutation rate over time and episodic bursts of mutations. The initiating factors for these bursts are unclear although retrotransposon mobilisation may play a role. This cell line set now constitutes a comprehensive resource of live experimental models of mutational processes of both known and unknown aetiologies potentially retaining the patterns of activity and regulatory influences operative in human cells in vivo.

  Dataset EGAD00001004202

• TRACERx100 metastatic samples

  Whole exome sequencing of 10 metastatic biopsies from four TRACERx100 patients (see EGA dataset EGAS00001002247), collected either after relapse or death. The data from these samples are initially published with Abbosh, C. et al. Phylogenetic ctDNA analysis depicts early stage lung cancer evolution. Nature, http://dx.doi.org/10.1038/nature22364 (2017). Abstract: Earlier detection of relapse following primary surgery for non-small cell lung cancer and the characterization of emerging subclones seeding metastatic sites might offer new therapeutic approaches to limit tumor recurrence. The potential to non-invasively track tumor evolutionary dynamics in ctDNA of early-stage lung cancer is not established. Here we conduct a patient-specific approach to ctDNA profiling in the first 100 lung TRACERx (TRAcking Cancer Evolution through therapy (Rx)) study participants, including one patient co-recruited to the PEACE (Posthumous Evaluation of Advanced Cancer Environment) post-mortem study. We identify independent predictors of ctDNA release in early-stage non-small cell lung cancer and perform tumor volume limit of detection analyses. Through blinded profiling of post-operative plasma, we observe evidence of adjuvant chemotherapy resistance and identify patients destined to experience recurrence of their lung cancer. Finally, we show that phylogenetic ctDNA profiling tracks the subclonal nature of lung cancer relapse and metastases, providing a new approach for ctDNA driven therapeutic studies.

  Dataset EGAD00001003301

• Ethiopia Genome Project (low coverage)

  The Ethiopian area stands among the most ancient ones ever occupied by human populations and their ancestors. Particularly, according to archaeological evidences, it is possible to trace back the presence of Hominids up to at least 3 million years ago. Furthermore, the present day human populations show a great cultural, linguistic and historic diversity which makes them essential candidate to investigate a considerable part of the African variability. Following the typing of 300 Ethiopian samples on Illumina Omni 1M (see Human Variability in Ethiopia project, previously approved by the Genotyping committee) we now have a clearer idea on which populations living in the area include the most of the diversity.This project therefore aims to sequence the whole genome of 300 individuals at low (4-8x) depth belonging to the six most representative populations of the Ethiopian area to produce a unique catalogue of variants peculiar of the North East Africa. Furthermore 6 samples (one from each population) will also be sequenced at high (30x) depth to ensure full coverage of the diversity spectrum.The retrieved variants will be of great help in evaluating the demographic dynamics of those populations as well as shedding light on the migrations out of Africa.

  Dataset EGAD00001000598

• Cross-site Concordance Evaluation of Tumor DNA and RNA Sequencing Platforms of CIMAC-CIDC Network

  The Cancer Immune Monitoring and Analysis Centers (CIMACs) and the Cancer Immunologic Data Commons (CIDC)  has engaged in efforts to harmonize Whole-exome (WES) and RNA-sequencing (RNA-seq) data from three different experimental platforms (MD Anderson, NCI MoCha lab, and Broad Institute) and are using a series of developed pipelines to process the early trial samples. To evaluate the consistency of tumor WES and RNA-seq profiling platforms across different centers, the CIMACs-CIDC conducted a systematic harmonization study. DNA and RNA were centrally extracted from fresh frozen (FF) and formalin-fixed paraffin-embedded (FFPE) non-small cell lung carcinoma (NSCLC) tumors and distributed to three centers for WES and RNA-seq profiling

  Study phs002295

• Kids First and INCLUDE: Down Syndrome, Heart Defects, and Acute Lymphoblastic Leukemia

  This project is a collaboration with the trans-NIH INvestigation of Co-occurring conditions across the Lifespan to Understand Down syndromE (INCLUDE) Project, which seeks to improve health and quality-of-life for individuals with Down syndrome, and NHLBI's TransOmics for Precision Medicine (TOPMed) program, which seeks to apply omics technologies to improve scientific understanding of the fundamental biological processes that underlie heart, lung, blood, and sleep (HLBS) disorders. The data is also available at the INCLUDE Data Hub. Down syndrome (DS), which occurs due to trisomy 21, is one of the strongest risk factors for both congenital heart disease (CHD) and acute leukemia. For instance, children with DS have a 2000-fold increased risk of atrioventricular septal defects (AVSD) and a 20-fold increased risk of acute lymphoblastic leukemia (ALL). An important and innovative aspect of the Kids First program is understanding the overlap between structural birth defects and childhood cancer. Notably, the background of DS predisposes children to both of these phenotypes, however, the genomic architecture of risk remains largely undiscovered. In this joint Kids First/TOPMed/INCLUDE project, we are currently including >2,000 samples for whole-genome sequencing, including: 1) paired germline-tumor samples from children with DS-ALL; and 2) samples from families with DS-CHD. This work will advance our understanding of the developmental pathways that may lead to both structural birth defects and childhood cancer. The objectives of this study are to determine the genetic variants underlying AVSD and ALL risk in children with DS. Therefore, the aims of our study are: 1) compare whole-genome sequencing (WGS) data between children with documented DS-AVSD and children with DS who have structurally normal hearts to identify genetic variants that perturb heart development; and 2) compare WGS data between children with documented DS-ALL and children (from Aim 1) with DS who do not have a known history of ALL. We will also examine associations between germline mutations and somatic genomic features. This study will address the fundamental question of why children with DS have an elevated risk of AVSD and ALL. Insights into the genes that drive DS-AVSD and DS-ALL may have implications for improved genetic counseling, surveillance, clinical management, and treatment strategies for these children. Additionally, our findings may inform targeted therapies or interventions for children without DS who are at risk for structural birth defects and cancer. Additional Pediatric Cardiac Genetics Consortium (PCGC) data from children affected with Down syndrome and congenital heart disease are accessible through two separate dbGaP studies: phs001138 (Kids First) and phs001194 (TOPMed).

  Study phs002330

• SPECIAL (scATACseq): Dissecting the melanoma ecosystem one cell at the time during immunotherapy

  Characterising epigenome profiles of stage III/IV melanoma samples treated with ICB before and on treatment by single cell ATAC sequencing.

  Study EGAS50000001014

• Ovarian cancer/normal cell lines

  We performed whole genome sequencing of nine OC patient-derived cell lines and one normal cell line (HOSEpiC) to analyze if the cell lines harbor OC-typical genomic aberrations absent in normal cells and to relate genomic features to drug sensitivities.

  Dataset EGAD00001003146

• whole genome sequencing data of genomic heterogeneity of multiple synchronous lung cancer.

  Fastq data of genomics heterogeneity of multiple synchronous lung cancer. Whole-genome sequencing (WGS) were performed in 3 tumour samples, one regional lymph node metastasis sample and peripheral blood sample from the same patient with MSLCs.

  Dataset EGAD00001003458

• BLUEPRINT: WGBS-seq of multiple myeloma and plasma cells

  Whole-genome Bisulfite sequencing of two multiple myeloma samples and one pooled sample of plasma cells.

  Dataset EGAD00001000672