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• Feasibility of targeted capture sequencing in routinely collected FFPE cancer specimens

  Testing the feasibility of genome-scale sequencing in routinely collected formalin-fixed paraffin-embedded (FFPE) cancer specimens versus matched fresh-frozen samples using targeted pulldown capture prior to Illumina sequencing.

  Dataset EGAD00001000354

• Exome sequence of probands in Barrett's oesophagus families

  Barrett?s oesophagus is common in the UK affecting 2 % of the population. Family history has been recorded among the 4000 Barrett's cases collected so far and have 241 families. Among them we have assessed 6 multiplex families with proven Barrett?s and defined as having 1 pro band and at least 3 affected first degree members. We propose to exome sequence the probands of these six families to assess the presence of pathogenic rare coding variants.

  Dataset EGAD00001002181

• Single-cell RNA sequencing of cytokine-induced T cell responses

  Cytokines affect T cell responses by polarising them to different phenotypes. We isolated T cells from healthy platelet donors and cultured them in resting and stimulated condition, as well as in the presence of Th2, iTreg and Th17 polarizing cocktail. To characterize the efficacy of cytokine induced porization and subpopulation specific response, we profiled single cell transcriptome five days following polarization using 10x platform (3' v2).

  Dataset EGAD00001005290

• Human Biofluid RNA Atlas

  This dataset contains small RNA sequencing data and mRNA capture sequencing data from 20 different human biofluids (amniotic fluid, aqueous humor, ascites, bile, bronchial lavage fluid, breast milk, cerebrospinal fluid, colostrum, gastric fluid, pancreatic cyst fluid, plasma, saliva, seminal fluid, serum, sputum, stool, synovial fluid, sweat, tear fluid and urine). In total, 180 samples were sequenced. Files are provided in fastQ format. Samples were sequenced on a NextSeq 500.

  Dataset EGAD00001005439

• Whole genome sequencing of HSPCs and pAML

  Whole genome sequencing data (Illumina HiSeq and NovaSeq) of clonal cultures derived from pediatric human bone marrow-derived hematopoietic stem and multipotent progenitor cells (in total 44 samples from 10 donors) and bulk pediatric acute myeloid leukemia blasts (in total 6 samples from 6 patients) to study the mutation accumulation.

  Dataset EGAD00001006338

• SG Peranakan Project dataset

  This dataset contains the genotypes jointly-called from whole genome sequencing data of 177 self-reported Peranakans in Singapore. Reads were aligned to GRCh37 reference genome and jointly-called with other WGS samples. Basic quality control measures and population phasing without reference were performed on the called genotypes. The data are stored in VCF v 4.3 format, and one .vcf.gz file stored the genotypes from one of the 23 chromosomes (22 autosomes+X chromosome).

  Dataset EGAD00001007786

• RNA-Seq of response to Tozinameran vaccination in individuals with KTx/dialysis or healthy controls.

  Low-input RNA-Seq (~200 cells per sample) of CD4+ T cells in patients with kidney transplants, dialysis, or healthy controls after the second dose of Tozinameran COVID-19 vaccine. RNA-Seq was performed using the Smart-Seq v4 ultra-low input protocol. The dataset includes 4 healthy control samples, 3 kidney transplant recipients, and 4 patients undergoing dialysis.

  Dataset EGAD00001007689

• CM214 - Biomarker Analysis From the Phase 3 CheckMate 214 Trial of Nivolumab Plus Ipilimumab (N+I) or Sunitinib (S) in Advanced Renal Cell Carcinoma (aRCC)

  CM214 - Biomarker Analysis From the Phase 3 CheckMate 214 Trial of Nivolumab Plus Ipilimumab (N+I) or Sunitinib (S) in Advanced Renal Cell Carcinoma (aRCC)

  Dataset EGAD00001007938

• Transcriptomic Profile of Colorectal Cancer Samples

  Samples encompass primary colorectal tumors or metastasis of 75 patients, collected by Medical Pathologists from surgically removed specimens. Tissues were embedded in optimal cutting temperature (OCT) medium, snapshot frozen in liquid nitrogen within 40 minutes of collection and preserved at -80ºC. Samples were collected between June 2010 and October 2017 as part of a prospective biobanking project.

  Dataset EGAD00001009506

• Paired ONT and downsampled Illumina cfDNA dataset

  The dataset contains 12 lung cancer plasma cfDNA samples, 8 bladder cancer and 2 healthy control urine cfDNA samples collected in EDTA collection tubes. Shallow WGS was performed using both Oxford Nanopore Technologies' MinION platform with an R9.4.1 flow cell and the SQK-PBK004 kit (22 files) and Illumina Novaseq platform with an S4 flow cell in PE150bp configuration (2x22 files).

  Dataset EGAD00001009392

• NEC

  This multi-centre, non-randomized, open-label, phase II trial (NCT03016338), assessed niraparib monotherapy (cohort 1, C1), or niraparib and dostarlimab (cohort 2, C2) in patients with recurrent serous or endometrioid endometrial carcinoma. The primary endpoint was clinical benefit rate (CBR). Secondary outcomes were safety and objective response rate (ORR). Translational research was an exploratory outcome. Potential biomarkers were evaluated in archival tissue by immunohistochemistry and next generation sequencing panel. Feasibility of liquid biopsy by ctDNA was assessed.

  Dataset EGAD00001010056

• Whole exome sequencing (WES)

  The whole study comprises of two patient cohorts. Screening cohort: 40 patients of Germany; validation cohort: 40 patients from Asia. Further, bile duct and CCA cell lines have been analyzed. This dataset contains whole exome sequencing data of 37 tumor/normal pairs from the screening cohort plus an additional relapse tumor of one of those 37 patients. Data was generated on Illumina HiSeq 2000 device in paired-end mode and is stored in BAM file format.

  Dataset EGAD00001011324

• RNA-seq of PBX1 knock-down or overexpressing cell lines

  The whole study comprises of two patient cohorts. Screening cohort: 40 patients of Germany; validation cohort: 40 patients from Asia. Further, bile duct and CCA cell lines have been analyzed. This dataset contains 44 samples derived from RNA-sequencing data of bile duct and CCA cell lines. Data was generated on Illumina NovaSeq 6000 device in paired-end mode and is stored in compressed FASTQ file format.

  Dataset EGAD00001011325

• Single-cell RNA and TCR sequencing of 37 PBMC pools of advanced HCC patients.

  scRNAseq and scTCRseq of serial peripheral blood mononuclear cell (PBMC) samples (n=72) taken at various timepoints before and during treatment (Week 0 (W0), Week 3 (W3), Week 6 (W6)). PBMC samples were pooled together into 37 pools, loading 2 or three samples per lane in the 10X Genomics chip, in equal proportions, according to a pre-designed pooling matrix.

  Dataset EGAD00001011345

• Cancer Genetic Markers of Susceptibility (CGEMS) Breast Cancer Genome-wide Association Study (GWAS) - Primary Scan: Nurses' Health Study - Additional Cases: Nurses' Health Study 2

  The initial stage of the Cancer Genetic Markers of Susceptibility (CGEMS) breast cancer genome-wide association study (GWAS) included genotyping 528,173 SNPs (Illumina HumanHap550) in 1,145 postmenopausal women of European ancestry with invasive breast cancer and 1,142 controls from the Nurses' Health Study (NHS). Subsequently, incident invasive breast cancer cases from the Nurses' Health Study 2 (NHS2) cohort were genotyped using the Illumina HumanHap 610 quad. The NHS2 cases are younger than the cases in the first stage of the CGEMS breast cancer GWAS, which only included postmenopausal women. The NHS2 cases are a mix of pre- and postmenopausal women

  Study phs000147

• Ameloblastoma Cell Line Resource

  Ameloblastoma (AB) is an odontogenic tumor that is locally destructive to the jaw bone. Treatment entails surgical resection, but AB often recurs locally. Recent driver mutations have been identified in the MAPK and Hedgehog pathways. However, translation to molecularly-targeted therapies has been hampered by the lack of AB cell line models. The goal of our study has been to create a new AB cell line resource that reflects the spectrum of AB driver mutations. We created 6 new AB cell lines, and by targeted exome sequencing, defined their driver mutations. We showed the utility of these cell lines in preclinical studies of oncogene dependence and drug sensitivity (which includes whole transcriptome assays).

  Study phs002753

• National Institute of Mental Health (NIMH) Amish Mennonite Bipolar Genetics Study (AmBiGen)

  Bipolar affective disorder is a severe, heritable condition affecting about one percent of the population. The mode of inheritance is poorly understood and probably involves multiple loci of small to moderate effect. In this project, we use genetic mapping and sequencing methods to identify genetic markers and variations that contribute to the risk of bipolar disorder. Individuals diagnosed with bipolar disorder are studied, along with their relatives. Phenotypic information obtained from clinical interviews and family history is correlated with genotypic information obtained from genetic marker and sequencing methods. The goal is to identify genes involved in bipolar disorder and related conditions so that better methods of diagnosis, treatment, and prevention can be developed.

  Study phs000899

• Whole blood RNAseq from a large ALS case-control study at Univ of Michigan

  Patients with amyotrophic lateral sclerosis (ALS), a rare fatal neurodegenerative disease, face a lengthy diagnostic process, and, although most survive only 2 to 4 years from diagnosis, lack information regarding their specific anticipated disease course due to a lack of prognostic tools. Although ALS is a heterogeneous disease of varied etiology, peripheral immune system dysfunction is ubiquitous, reflected in altered whole blood transcriptome. Herein, we profiled whole blood gene expression by RNA sequencing in a large cohort of ALS cases versus controls. Several machine learning classifiers trained on our gene expression dataset predicted case-control status and survival, and integration analysis with external cohorts led to the identification of drug candidates.

  Study EGAS50000001019

• Metagenomic characterization of tracheal aspirates from non-pulmonary sepsis patients

  Our previous studies in mechanically ventilated Intensive Care Unit (ICU) patients with extrapulmonary sepsis revealed that pulmonary dysbiosis within 8 h from sepsis diagnosis was associated with ICU mortality. These observations offer promising options that could be technologically adapted to rapidly identify those patients at higher risk of death. However, they relied on 16S rRNA sequencing experiments which impedes deep characterization of the bacterial communities that could help to further substantiate the association. To further discern this association, here we assessed the pulmonary bacterial communities in these patients by leveraging metagenomics and evaluated if the presence of antibiotic resistance genes could explain the higher mortality of the patients.

  Study EGAS50000000384

• Genome-to-genome analysis highlights the impact of the human innate and adaptive immune systems on the hepatitis C virus

  Outcomes of hepatitis C virus (HCV) infection and treatment depend on viral and host genetic factors. We use human genome-wide genotyping arrays and new whole-genome HCV viral sequencing technologies to perform a systematic genome-to-genome study of 542 individuals chronically infected with HCV, predominately genotype 3. We show that both HLA alleles and interferon lambda innate immune system genes drive viral genome polymorphism, and that IFNL4 genotypes determine HCV viral load through a mechanism that is dependent on a specific polymorphism in the HCV polyprotein. We highlight the interplay between innate immune responses and the viral genome in HCV control.

  Study EGAS00001002324

• Epiclomal: probabilistic clustering of sparse single-cell DNA methylation data

  We present Epiclomal, a probabilistic clustering method arising from a hierarchical mixture model to simultaneously cluster sparse single-cell DNA methylation data and infer their corresponding hidden methylation profiles. Using synthetic and published single-cell CpG datasets we show that Epiclomal outperforms non-probabilistic methods and is able to handle the inherent missing data feature which dominates single-cell CpG genome sequences. Using a recently published single-cell 5mCpG sequencing method (PBAL), we show that Epiclomal discovers sub-clonal patterns of methylation in aneuploid tumour genomes, thus defining epiclones. We show that epiclones may transcend copy number determined clonal lineages, thus opening this important form of clonal analysis in cancer.

  Study EGAS00001003504

• Understanding_the_multicellular_dynamics_of_clear_cell_renal_cell_carcinoma___visium

  This study will reconstruct the single cellular phylogeny of tumour and immune cells in relation to both genomic, functional, and spatial location. 20 tumours in total will be studied, including non-progressing small renal masses, progressing small renal masses, relatively indolent larger tumours, and high risk tumour with metastatic sampling. We aim to: Generate a focused, comprehensive phylogenetic characterisation of tumour cells Understand the dependencies of the cancer genome, transcriptome, tissue architecture and the single cellular micro-environment Quantify the single cellular composition and functional intra- and inter- tumoural heterogeneity Determine the phylogeny of tumour associated lymphocytes and their relationship to neo-epitopes and the immune microenvironment Investigate the mechanisms by which the tumour-normal interface constrains tumoural growth.

  Study EGAS00001006045

• The mutational landscape of normal human endometrial epithelium - Additional Samples

  All normal somatic cells are thought to acquire mutations but understanding of the rates, patterns, causes and consequences of somatic mutation in normal cells is limited. Uterine endometrium adopts multiple physiological states over a lifetime and is lined by a gland-forming epithelium. Whole genome sequencing of normal endometrial glands from women aged 19 to 81 years showed them to be clonal cell populations derived from recent common ancestors, with total mutation burdens that increase with age at ~29 base substitutions/year and which are many-fold lower than endometrial cancers. Normal endometrial glands frequently carry driver mutations in cancer genes. Driver mutation burdens increase with age and correlate negatively with parity. Phylogenetic trees of normal endometrial glands constructed using whole genome sequences indicated that clones with drivers often originate during the first decades and spread to colonise the endometrial epithelial lining. The results show that driver mutation landscapes differ between normal cell types, perhaps shaped by differences in normal tissue physiology, and suggest that the procession of neoplastic changes leading to endometrial cancer is initiated early in life.

  Dataset EGAD00001005214

• NHLBI GO-ESP: Family Studies (Familial Interstitial Pneumonia)

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. The Familial Interstitial Pneumonia (FIP) project seeks to identify genetic variants in coding regions of the human genome that are linked to FIP by examining the coding regions among relatives with FIP. These data will be used in conjunction with our other genetic studies to help us better understand how and why some individuals develop pulmonary fibrosis.

  Study phs000582

• Systems Analysis of Single-Cell Heterogeneity Underlying Glioma Drug Resistance

  This study characterizes the transcriptional regulatory mechanisms that drive responses of two patient-derived glioblastoma multiforme (GBM) stem-like cells (PD-GSCs) that have distinct phenotypes - one sensitive and another resistant to the drug pitavastatin. This study investigates the differing mechanisms driving drug response in the two PD-GSCs at the single-cell level, and provides an approach that can be used to infer transcriptional regulatory network models, which can then be used to identify mechanisms driving cell-state transitions, e.g., proneural-to-mesenchymal transitions (PMT), which has been observed experimentally and clinically in GBM. The use of these network models enabled the identification of transcription factor and gene targets that perturbed drug-induced PMT through 1) simulations of network dynamics network, and 2) characterization of gene program activities over the time-course response to drug treatment. These results enabled the identification of multiple siRNAs and the drug vinflunine as secondary components that potentiate the efficacy of pitavastatin. This work demonstrates an approach to uncover the transcriptional network topology (TRN) topology of PD-GSCs, and use it to rationally predict combinatorial treatments that block treatment escape and acquired resistance to drugs in GBM.

  Study phs003501