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• 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

• Test dataset: Sequence and variant data from public 1000 Genomes Project

  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 2508 samples from the 1000 Genomes Project (https://www.nature.com/articles/nature15393). Samples' (e.g. NA18534) data can be accessed through the IGSR portal (e.g. https://www.internationalgenome.org/data-portal/sample/NA18534) or their corresponding folder at the 1000 Genomes' FTP site (e.g. http://ftp.1000genomes.ebi.ac.uk/vol1/ftp/data_collections/1000_genomes_project/data/CHB/NA18534/exome_alignment/). There are several different types of data this dataset encompasses: Variant Calling Format (VCF, or its binary counterparts BCF) files, both joint (e.g. ALL_chr22_20130502_2504Individuals.vcf.gz) and split (HG01775.chrY.vcf.gz); exome sequencing CRAM files (e.g. NA18534.GRCh38DH.exome.cram); whole genome sequencing CRAM/BAM files (e.g. NA19239.cram). Additionally, there are multiple files that were sliced to create shorter files, which allows for a quick download, formated as "{FILE-INFO}__{NUMBER-OF-READS}r__{CHR}.{START-COORDINATE}-{END-COORDINATE}.{FILETYPE}" (e.g. "HG01500.GRCh38DH__90r__3.10000-10500__4.10000-10500.cram"). These files can be downloaded directly through the EGA-download-client PyEGA3 (https://github.com/EGA-archive/ega-download-client).

  Dataset EGAD00001003338

• High hyperdiploid ALL single cell whole genome sequencing

  This dataset was collected from viable bone marrow cells obtained at diagnosis from nine patients with high hyperdiploid ALL and one normal bone marrow sample. All samples were subjected to low pass single cell whole genome sequencing with the median sequencing coverage of 0.02x. Single nuclei in G0/G1 phase were isolated using a fluorescence-activated cell sorting (FACS) cytometer. DNA libraries were constructed and associated next-generation sequencing was carried out by European Research Institute for the Biology of Ageing (ERIBA), University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. Further details regarding the DNA libraries construction are available by Bos et. al., 2019 (https://link.springer.com/protocol/10.1007/978-1-4939-8931-7_15).

  Dataset EGAD00001008988

• scRNA-seq and snRNA-seq of trophoblast stem cells (TSCs) differentiation into extravillous trophoblast organoids (EVTs)

  This dataset is part of a study that aims to compare in vivo human trophoblast differentiation into EVTs to different in vitro trophoblast organoids using single-cell and single-nuclei RNA sequencing. This specific dataset includes scRNA-seq and snRNA-seq data from trophoblast stem cells (TSCs). Trophoblast stem cell (TSC) lines BTS5 and BTS11 derived by Okae and colleagues were grown as described previously (Okae et al. 2018) together with EVT differentiation media. This study shows that the main regulatory programs mediating EVT invasion in vivo are preserved in in vitro models of EVT differentiation from primary trophoblast organoids and trophoblast stem cells. Data for primary trophoblast organoids is available under E-MTAB-12650.

  Dataset EGAD00001010017

• An integrated single-cell reference atlas of the human endometrium

  This dataset includes both the anchor scRNA-seq and snRNA-seq datasets used to build the Human Endometrial Cell Atlas (HECA). HECA provides a comprehensive definition of endometrial cell types and states throughout the menstrual cycle in donor with and without endometriosis. It identifies consensus cell types across datasets generated by teams worldwide, as well as previously unreported cell types, all of which are validated and mapped in situ using spatial transcriptomics. Processed data is available from ArrayExpress with accession number E-MTAB-14039. See Marečková, M., Garcia-Alonso, L., Moullet, M. et al. An integrated single-cell reference atlas of the human endometrium. Nat Genet 56, 1925–1937 (2024) https://doi.org/10.1038/s41588-024-01873-w for more information.

  Dataset EGAD00001015446

• Longitudinal study of whole blood gene expression in Kenyan children exposed to malaria

  We have collected RNA samples from whole blood of Kenyan children exposed to malaria in the Kilifi region of Kenya. Collections were performed each year from 2015 until 2018. This is a follow-up study to that described in Bediako et al. (in preparation). The SIMS consortium is seeking to identifying the underlying reasons why some children are more susceptible to malaria than others. In this study we hope to track changes in children’s immune systems over time which relate to the number of malaria episodes they experience. 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 EGAD00001015405

• A Case-Controlled Study for Genotype-Phenotype Associations in Multiple Sclerosis (MS)

  This is a multi-centre, case-controlled study to develop a dataset containing 1000 MS cases and 1000 matched controls and to associate DNA sequence (allelic) variations with MS phenotypes. Study subjects were enrolled through a prospective effort initiated in 2003. Three MS clinical centres were involved in subject recruitment and biological specimen collection using identical inclusion/exclusion criteria, two in Europe (Vrije Universiteit Medical Center, Amsterdam; and University Hospital Basel) and one in the US (University of California San Francisco). This study recruited subjects of northern-European ancestry with a diagnosis of MS (McDonald et al., 2001), with dissemination in time and space. Patients with Clinically Isolated Syndromes (CIS) were also included if they fulfilled 3 of the 4 Barkhof criteria for dissemination in space as per application of the McDonald criteria (McDonald et al., 2001). While recruitment predominantly included subjects with a relapsing onset of MS, individuals with all clinical subtypes of the disease participated, including clinically isolated syndrome (CIS), relapsing remitting MS (RRMS), secondary progressive MS (SPMS), primary progressive MS (PPMS), and progressive relapsing MS (PRMS). The control group consisted of unrelated individuals, primarily spouses/partners, friends, and other volunteers. Control subjects were of northern-European ancestry and matched as a group, proportionally with cases according to age (±5 years) and gender. A familial history or current diagnosis of MS as well as a relation to another case or control subject were considered exclusionary for this group. Protocols were approved by the Committees on Human Research at all Institutions and informed consent was obtained from all participants prior to participation in the study. Primary Study Objective:To identify DNA sequence variations (genotype) and flanking sequences that are associated with clinical factors (phenotype) which differ between study subjects with and without MS. Secondary Study Objectives: To develop a clinical dataset including quantitative measures of 1000 well-characterized cases with MS, and 1000 ethnically matched controls. To identify other genotype-phenotype associations in MS study subjects such as magnetic resonance imaging (MRI) measures of disease burden and/or severity. To identify or confirm candidate surrogate markers of neurodegeneration using a variety of techniques including biochemical assays, blood transcriptome analysis, plasma proteomics and MRI*. GenotypingGenotyping of the complete dataset was performed at the Illumina facilities using the Sentrix® HumanHap550 BeadChip. *MRI results are not available on dbGaP.

  Study phs000171

• ARRA - NHLBI Lung Cohorts Sequencing Project: Genetic modifiers of

  The major goal of this project is to apply second generation resequencing technology to identify disease causing variants influencing pediatric and adult lung diseases in a collection of two longitudinal population cohorts of cystic fibrosis patients that have been well characterized for a comprehensive set of clinical traits. In Phase I, exome sequencing was performed on 43 cystic fibrosis patients with early Pa infection and 48 cystic fibrosis patients with late Pa infection to identify variants influencing the time to onset of Pa infection. In Phase II, additional exomes were added to the study, to reach a total of 91 individuals with early Pa infection and 96 with late Pa infection. The majority of the 340 subjects of Phase II do not have a Pa infection phenotype, but instead have a pulmonary function phenotype (121 severe vs. 124 mild impairment) as determined by the survival corrected Kulich FEV percentile of Corey et al. A small minority have intermediate phenotypes and/or show severe decline in lung function during childhood.

  Study phs000254

• POISED (Peanut Oral Immunotherapy: Safety, Efficacy, and Discovery)

  Phase 2 POISED (Peanut Oral Immunotherapy: Safety, Efficacy, Discovery) Study In this randomized, double-blind, placebo-controlled (DBPC) clinical trial, blinded placebo group received oat flour, whereas in active participants, dosage was built-up for over ~ 52 weeks and subsequently maintained on 4000 mg peanut protein, daily for next 52 weeks. 80 (98.77%) per-protocol active participants passed the food challenge at week 104. Subsequently, for 12 weeks, peanut ingestion was avoided in a randomized group of 51 blinded active participants (i.e., peanut avoidance group). 21 (41.2%) participants in the peanut avoidance group passed the 4000 mg double-blind, placebo-controlled food challenge (DBPCFC) without any allergic reaction at week 117, thus demonstrating sustained unresponsiveness. These 21 participants continued oral immunotherapy (OIT) for every three months and afterwards were allowed to continue peanut OIT discontinuation if they passed. 8 participants passed the DBPCFCs, 12 months after peanut discontinuation (week 156), i.e. they achieved long-term sustained unresponsiveness with no allergic reaction in response to food challenge. For detailed description, please refer to Chinthrajah et al., PMID: 31522849.

  Study phs003071

• Multi-Omic Profiling of Glioma Patient Tumors and Patient-Derived Model Systems

  We have created a resource of transcriptomic (RNAseq), genomic (whole-exome seq), and lipidomic (untargeted shotgun) profiling data from over 175 molecularly diverse glioma tumors and derivative models in orthotopic mouse xenografts and gliomasphere cultures from over 110 unique patient tumor lines. Provided in this dataset are matched bulk RNA and whole-exome paired-end sequencing data from resected gliomas and derived model systems performed on Illumina HiSeq and NovaSeq sequencing instruments. This comprehensive dataset powers multiple studies aiming to derive molecular signatures of intertumoral heterogeneity and perturbation responses in glioma. Through integrative multi-omic analyses in Minami, et al., 2023, PMID: 37236196, we identified that CDKN2A deletion remodels the GBM lipidome and consequently primes CDKN2A-deleted tumors for ferroptosis. Lipidomics data related to this study are publicly available here. In another study, we used a combination of molecular profiling and functional profiling of apoptotic potential to stratify patients into groups with differential vulnerability to the current standard-of-care in gliomas, and in combination with drugs targeting intrinsic apoptosis, largely informed but not limited to TP53 mutation status.

  Study phs003286