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• IYDP Indonesian Y chromosome Diversity Project

  Island Southeast Asia and Oceania host one of the world’s richest assemblages of human phenotypic, linguistic and cultural diversity. We compiled ~9.7 Mb of Y chromosome sequence from a diverse sample of over 380 men from this region, including 126 from Indonesian islands, first reported here. The granularity of this dataset allows us to fully resolve and date the regional Y chromosome phylogeny. This improved Y chromosome topology highlights localized events with important historical implications, including pre-Holocene contact between Mainland and Island Southeast Asia, ongoing interactions between Australia and the Papuan world, and a sustained period of diversification following the flooding of the ancient Sunda and Sahul continents as the insular landscape of today formed. The high-resolution phylogeny of the Y chromosome presented here thus enables a detailed exploration of past isolation, interaction and change in one of the world’s least understood regions.

  Study EGAS00001006028

• DNA methylation-based classification of sinonasal tumors [Proteomics data]

  The diagnosis of sinonasal tumors is challenging due to a heterogeneous spectrum of various differential diagnoses as well as poorly defined, disputed entities such as sinonasal undifferentiated carcinomas (SNUCs). In this study, we apply a machine learning algorithm based on DNA methylation patterns to classify sinonasal tumors with clinical-grade reliability. We further show that sinonasal tumors with SNUC morphology are not as undifferentiated as their current terminology suggests but rather reassigned to four distinct molecular classes defined by epigenetic, mutational and proteomic profiles. This includes two classes with neuroendocrine differentiation, characterized by IDH2 or SMARCA4/ARID1A mutations with an overall favorable clinical course, one class composed of highly aggressive SMARCB1-deficient carcinomas and another class with tumors that represent previously misclassified adenoid cystic carcinomas. The repository includes the raw mass spectrometry-based proteomics data

  Study EGAS00001006712

• DNA methylation-based classification of sinonasal tumors [DNA sequencing]

  The diagnosis of sinonasal tumors is challenging due to a heterogeneous spectrum of various differential diagnoses as well as poorly defined, disputed entities such as sinonasal undifferentiated carcinomas (SNUCs). In this study, we apply a machine learning algorithm based on DNA methylation patterns to classify sinonasal tumors with clinical-grade reliability. We further show that sinonasal tumors with SNUC morphology are not as undifferentiated as their current terminology suggests but rather reassigned to four distinct molecular classes defined by epigenetic, mutational and proteomic profiles. This includes two classes with neuroendocrine differentiation, characterized by IDH2 or SMARCA4/ARID1A mutations with an overall favorable clinical course, one class composed of highly aggressive SMARCB1-deficient carcinomas and another class with tumors that represent previously misclassified adenoid cystic carcinomas. This repository includes the results from DNA sequencing and mass spectrometry-based proteomics.

  Study EGAS00001006713

• Deregulation of FOXF1/FENDRR from t(14;16)(q32;q24) defines a subtype of high risk lineage ambiguous leukemia

  Despite great progress in understanding the genomic basis of immature T-cell acute lymphoblastic leukemia/lymphoblastic lymphoma (T-ALL) and acute leukemias of ambiguous lineage (ALAL), there are still cases that lack defining genetic markers, complicating risk stratification and limiting targeted therapeutic options. Here, we describe a subtype of leukemia defined by the t(14;16)(q32;q24) translocation, which places the FOXF1 gene and its antisense long noncoding RNA gene FENDRR under the regulatory control of the BCL11B enhancer, leading to their ectopic transcriptional activation. Analysis of different high-throughput sequencing data, including WGS, RNA-seq, scDNA-seq, scRNA-seq, ChIP-seq, ATAC-seq, and HiChIP-seq, identified BCL11B-enhancer mediated deregulation of FOXF1/FENDRR as a hallmark of a subtype of high-risk lineage ambiguous leukemia that is potentially amenable to targeted therapeutic intervention.

  Study EGAS50000001255

• Burden of DNMs in children born conceived using ART

  The dataset is composed by processed whole genome sequencing data generated from 53 children and their respective parents, forming 49 trios (mother, father and child) and 2 quartets (mother, father and two siblings). A total of 18 children were born after spontaneous conception (n = 18); 17 children were born after in vitro fertilization (IVF) and another 18 children were born after intracytoplasmic sperm injection combined with testicular sperm extraction (ICSI-TESE)

  Dataset EGAD00001008208

• Reference Epigenomes and Regulatory Landscape of CLL

  Analysis of the reference epigenomes and regulatory landscape of CLL as a whole and its major clinico-biological subtypes (with mutated and unmutated IGHV) in the light of the normal B-cell differentiation. We have extensively characterized the reference epigenomes of seven primary chronic lymphocytic leukemia samples (CLLs) with mutated (n=5) and unmutated IGHV (n=2) as well as several mature B-cell subpopulations (naive B cells from blood and tonsil, germinal center B cells, memory B cells and plasma cells from tonsil) using genome-wide maps of six histone marks (H3K4me3, H3K4me1, H3K27ac, H3K36me3, H3K9me3 and H3K27me3), DNA accessibility (ATAC-seq), DNA methylation (whole-genome bisulfite sequencing) and gene expression (RNA-seq). Furthermore, we have mapped the regulatory chromatin landscape of 100 additional CLL cases using chIP-seq of H3K27ac and ATAC-seq and linked these data to additional layers of information (whole-genome and/or whole-exome sequencing (WGS/WES), RNA-seq and DNA methylation microarrays) studied in the context of the International Cancer Genome Consortium (ICGC).

  Dataset EGAD00001004046

• ChIIP-seq and RNA-seq

  epigenome profiling in tumor tissues and paired normal tissues of LUAD patients and transcriptome profiling in tumor tissues of LUAD patients.

  Dataset EGAD00001007066

• Integrative understanding of human immune system by functional genomics and development of intervention strategies for the prevention of autoimmune diseases

  arious peripheral blood immune cell subsets from 5 rheumatoid (RA) donors were collected ("CD16p_Mono", "CL_Mono???, "DN_B", "Fr_II_eTreg???, "mDC???, "Mem_CD4" , "Naive_B" , "Naive_CD4" , ???Neu", "NK" , "pDC" , "Plasmablast", ???SM_B", "Tfh", "Th1", "Th17", "Th2" , "USM_B"). The patients were analyzed again longitudinally after abatacept treatment. RNA-seq was performed with each immune cell subset samples. After gene expression quantification samples were filtered.

  Study JGAS000602

• Integrative understanding of human immune system by functional genomics and development of intervention strategies for the prevention of autoimmune diseases

  Various peripheral blood immune cell subsets from 39 healthy volunteers and 50 rheumatoid (RA) donors were collected ("CD16p_Mono", "CL_Mono???, "DN_B", "Fr_II_eTreg???, "mDC???, "Mem_CD4" , "Naive_B" , "Naive_CD4" , ???Neu", "NK" , "pDC" , "Plasmablast", ???SM_B", "Tfh", "Th1", "Th17", "Th2" , "USM_B"). 15 RA patients were analyzed longitudinally. RNA-seq was performed with each immune cell subset samples. After gene expression quantification samples were filtered.

  Study JGAS000598

• Personalized IGM, IGK, IGL V(D)J repertoire sequencing of four Influenza A exposed individuals

  Peripheral blood mononuclear cells were used to produce paired, full-length IGM, IGK and IGL V(D)J libraries from HA-binding single memory B cells using the ISCAPE (Individualized Single Cell Analysis of Paired Expressed antigen receptors) technique. Locus-specific multiplexed nested PCR with primer sets targeting the 5’ UTR/leader and 3’ constant region was performed before well and plate indexing and paired chain sequencing with an Illumina MiSeq instrument. Expressed total IGM, IGK and IGL V(D)J libraries from each donor were acquired and analyzed to define personalized IG allele content. The fastq file names include the donor and target for expressed IGM, IGK or IGL V(D)J libraries.

  Dataset EGAD50000002018