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• WGS data of paediatric B-other B cell acute lymphoblastic leukemia (set3)

  The dataset includes FASTQ and BAM/CRAM files from diagnostic and matched remission (control) samples of 10 B-other ALL patients (ALLT-369,ALLT-378, ALLK-109, ALLK-110, ALLK-115, ALLT-391, ALLK-101, ALLK-113, ALLK-123, ALLT-393). Sequencing library was made using PCR free-based WGS library preparation (PCR-), using NEBNext® Ultra™ II DNA Library Prep Kit. Both diagnostic (90x) and remission (30x) samples were sequenced using Illumina NovaSeq 6000.

  Dataset EGAD50000002158

• WGS of clonal organoids, bulk-tumor tissues, and matched blood samples derived from metastatic colorectal cancer patients

  This dataset consists of WGS fastq files from 58 clonal organoids and 18 fresh-frozen (FT) bulk-tissue samples from surgically resected primary and metastatic tumors before and after anticancer therapies in 6 patients with matched blood control samples from each patient. After DNA extraction from each sample using DNeasy Blood and Tissue Kit (Qiagen), library preparation was done using TruSeq DNA PCR-free kit. Then, paired-end fastq files were generated using Illumina NovaSeq 6000.

  Dataset EGAD50000001493

• Transrenal DNA Analysis

  The current sequencing dataset consists of 91 whole genome sequencing data files (Fastq files) of human cell-free DNA (cfDNA) obtained from plasma and urine samples. Specifically, we extracted 20 ucfDNA and 17 plasma DNA samples from healthy pregnant women, 11 ucfDNA samples from pregnant women with preeclampsia, 19 ucfDNA samples from healthy controls, and 24 ucfDNA samples from patients with proteinuria. These extracted cfDNA samples were then constructed into DNA libraries using the TruSeq Nano DNA Library Prep Kit (Illumina) and subsequently sequenced on the Nextseq2000 platform (Illumina).

  Dataset EGAD50000001127

• cfRRBS methylation profiling of cfDNA from cerebrospinal fluid from pediatric CNS tumor patients

  In this study, we explore the potential of classifying pediatric brain tumors based on methylation profiling of the cell-free DNA in cerebrospinal fluid (CSF). For this proof-of-concept study, we collected 20 cerebrospinal fluid samples of pediatric brain cancer patients via a ventricular drain placed for reasons of increased intracranial pressure. For 11 patients in this study we collected matched tumor DNA. This cohort contains fastQ files of cfRRBS data of these samples.

  Dataset EGAD50000000554

• limbal stem cells from Aniridia patients

  Limbal stem cells obtained during penetrating keratoplasty from aniridia patients with congenital aniridia (Lagali Stage 4), limbal tissue was digested in collagenase A solution (4 mg/ml) in keratinocyte serum-free medium (KSFM) (Thermo Fisher Scientific; Waltham, MA) for 20 h at 37 °C. Cell suspensions were filtered through a use of Flowmi® micro strainer (SP Bel-Art; Wayne, NJ). LSC clusters were dissociated with trypsin-EDTA (0.05%) solution and cultivated in KSFM. Medium was refreshed every other day. Subconfluent (80–90%) limbal epithelial cells were harvested at passage 2

  Dataset EGAD00001011124

• Whole-genome and transcriptome sequencing of NUT midline carcinoma

  In this study, we sequenced three NUT midline carcinoma genomes and their transcriptomes (NMC1, NMC2 and Ty-82), and two paired normal blood samples (for NMC1 and NMC2). Whole-genome sequencing libraries were generated by PCR-free methods, and sequencing run was made in HiSeq X machines. Transcriptome (mRNA) sequencing was performed in HiSeq 2500 machines. PCR duplicates-marked, indel-realigned, and base-recalibrarted BAM files are provided in our dataset.

  Dataset EGAD00001003117

• Evolutionary Genome Analysis of Transformation into Small Cell Carcinomas from Lung Adenocarcinomas

  This dataset includes the high-throughput sequencing data from a study entitled "Clonal History and Genetic Predictors of Transformation into Small Cell Carcinomas from Lung Adenocarcinomas". Whole-genome sequencing libraries were generated by PCR-free methods, and sequencing run was made in HiSeq X or HiSeq 2500 machines. PCR duplicates-marked, indel-realigned, and base-recalibrarted BAM files are provided in our dataset.

  Dataset EGAD00001003315

• The Oral Microbiome and Head and Neck Cancer

  Oral microbiota may influence head and neck squamous cell carcinoma (HNSCC) development, potentially related to carcinogen metabolism. The human oral cavity hosts a diverse microbiota, including bacteria and fungi. We performed shotgun sequencing and ITS1 sequencing on 236 HNSCC case participants who developed HNSCC during a mean follow-up of 5.1 years and 458 matched controls who remained HNSCC-free. Oral samples were obtained from a prospective nested case-control study within three epidemiological cohorts: the American Cancer Society Cancer Prevention Study II Nutrition Cohort (ACS CPS-II), the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO), and the Southern Community Cohort Study (SCCS). Control participants were selected using 2:1 frequency matching based on cohort, age, sex, race and ethnicity, and time since oral sample collection.

  Study phs004018

• Size-tagged preferred ends in maternal plasma DNAshed light on the production mechanism and showutility in noninvasive prenatal testing

  Cell-free DNA molecules in the plasma of pregnant women exhibit nonrandom fragmentation with preferred end sites. We studied if such preferred end sites might bear any re- lationship with fragment lengths of plasma DNA. Short and long plasma DNA molecules were associated with different preferred DNA end sites. Analysis of size-tagged preferred ends could be used for measuring fetal DNA fraction and for facilitating fetal trisomy 21 detection. Fetal preferred end sites were generally located in the nucleosome cores, while the maternal ones were located in the linker regions. This con- ceptual framework provides an explanation of the relative shortness of fetal DNA in maternal plasma and brings us closer to understanding the biological mechanisms that influence plasma DNA fragmentation.

  Study EGAS00001002831

• Genome-Wide Association Study of Patients with Coccidioidomycosis

  BackgroundValley Fever is typically an infection of the lungs caused by the fungi Coccidioides immitis and Coccidioides posadasii. The incidence of Coccidioidomycosis (CM), or infection with Coccidioides, has dramatically increased over the last 20 years. This is particularly true in the Southwest of the United States, where people often breathe fungal spores that arise from the soil. Reasons for increased infection rates are thought to include population growth and construction in these endemic regions, an increase in the number of people whose immune systems are compromised due to infection or treatment with drugs required for organ transplants, climate change, as well as improved testing practices and greater physician awareness. Mild CM most commonly presents itself with flu-like symptoms and rashes, which can last weeks to months. Individuals with compromised immune systems, specifically-- substantial suppression of the immune cells known as T cells, can develop severe pulmonary and disseminated disease. Infection that remains localized to the lungs is referred to as pulmonary disease, but when the infection spreads out of the lungs into other parts of the body it represents a more serious condition referred to as a disseminated disease, or disseminated CM. In nature, Coccidioides spp. exists as mold and lives in dust and soil. When the contaminated soil or dust is disturbed by human activity, animals, or weather, the Coccidiodies spores are released into the air. Airborne spores are taken up by breathing and settle in the lungs. Once in the moist and warm environment of the lung, spores transform into spherules, which divide and become filled with smaller spores, called endospores. When the spherules get large enough, they rupture and release these endospores, which can spread and disseminate to surrounding tissue. The cycle then repeats itself as these endospores develop into new spherules3. Different ethnic groups have been described to vary in their susceptibility to developing disseminated CM after initial infection with Coccidioides. For example, evidence suggests that African-American and Filipino patients suffer the disseminated disease at a greater rate than other ethnicities. The suggestion that race plays a role in the clinical expression of the disease is still a source of debate amongst the scientific community and any genetic mechanisms responsible for these differences have yet to be fully elucidated. If our genetic makeup influences our ability to limit the spread of infection, finding which DNA differences cause these variances could provide clues to how the body successfully fights infection, and provide opportunities to boost the body’s ability to do this. Further, if we are able to identify the specific genetic risk factors that correlate with the development of disseminated infection, physicians could perform genetic screenings to identify high-risk patients and provide them with preemptive antifungal therapy prior to developing disseminated disease.The genome, made up of DNA, contains all of the information needed for humans to develop and grow. Genome-wide association studies (GWAS) allow us to look for inherited differences that are more common between people who share a particular trait, for example, height or susceptibility to certain diseases, compared to those who do not share the trait. Although some traits and diseases are controlled by a single gene, the majority are influenced by contribution from several, or even many, different genes. To find evidence of genes that contribute to specific traits, GWAS typically compares genome information from large numbers of people who have a particular disease (referred to as “cases”) looking for DNA sequences that are common among these samples, and are different from DNA sequences seen in large numbers of people who lack the trait, but are as much like the cases as possible (referred to as “controls”). The DNA sequence data from each group, cases versus controls, are analyzed to see if there are specific genomic differences that tend to be associated with the disease. MethodsTwo separate GWAS approaches were taken to look for genetic differences that could be responsible for the observed differences between the different patient populations we are studying. The first method, known as genotyping, scans for differences at a set of positions across the genome, which includes both the genes that encode our proteins and the larger amount of DNA that does not. The second method, known as exome sequencing, allows us to compare the entire sequence of the portion of the genome that codes for proteins.  For this study, DNA from patients with either pulmonary or disseminated CM were genotyped and exome sequenced to look for DNA differences that are associated with one condition or the other. All patients were at least 18 years old, had no evidence of immunosuppression, and had proven or probable pulmonary coccidioidomycosis according to established diagnostic criteria. Of these patients, a subset demonstrated disseminated disease, i.e., they showed evidence of coccidioidal infection outside of the thorax by biopsy/aspiration, had radiographic imaging, and show positive coccidioidal serology. Our criteria for including patients with the pulmonary disease were that they must not require ongoing antifungal treatment or show evidence of active CM (in skin test positive patients), show no evidence of extrapulmonary dissemination, and have no evidence of ongoing pulmonary infection (pulmonary nodules are accepted) beyond six months from diagnosis.Patient DNA was purified from blood or from sputum samples by the labs of our collaborators, Drs. George Thompson (UC Davis School of Medicine) and John Galgiani (University of Arizona Health Sciences). Genome-wide association (GWAS) analysis was carried out to look for candidate loci associated with pulmonary versus disseminated disease, taking into account the population structure of the samples. Single nucleotide or insertion/deletion variants were identified from whole-exome sequences (WES) using the Picard/BWA/GATK pipeline. ResultsTable 1. Pulmonary versus Disseminated Cases of Coccidiomycosis for GWAS, Sorted by EthnicityEthnicityPulmonary CasesDisseminated CasesAsian85Black/African American1664Caucasian/White4015Filipino03Hispanic/Latino3414Indian21Mexican American1039Pacific Islander01Samoan03Vietnamese10Unknown16917More than one race02Total373134Table 1 shows the number of samples analyzed from patients with pulmonary versus disseminated disease, and patient ethnicity, where known. In all, we worked with 507 samples, including 134 samples from patients with disseminated disease and 373 samples from patients with pulmonary disease. Of these, 505 samples were genotyped using the Multi-Ethnic Global Array from Illumina Inc. In addition, we were able to generate whole-exome sequence from 498 patient samples. No significant associations were detected that differed between samples from patients with pulmonary versus disseminated disease; that is, no particular DNA sequences were found to be significantly enriched in patients with disseminated disease compared to patients with pulmonary disease. The ability to detect genetic association between specific sequences and genetically determined traits is influenced by several factors, including how many patient samples are available to compare, how many different genes contribute to the trait and how strong their contributions are. When the number of genes is small and the contribution of each gene is great, smaller numbers of patient samples are needed to detect an association. When more genes are involved, or the contribution from each gene is more modest, larger numbers of patient samples must be examined. While we were not able to detect any associated within this study, it does not mean that subsequent studies would not find this connection. Our study suggests significantly more samples should be analyzed in further studies.Whole-exome sequences were generated from 498 samples and were aligned to reference sequences to identify positions where the sequences differed from the reference. These data are being analyzed to determine if any variants are associated with pulmonary, versus disseminated, disease. 

  Study phs002170