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• Characterizing Individual Cells Obtained from Bone Marrow Biopsies of MPN Patients

  We profiled the transcriptomes of individual cells obtained from bone marrow aspirates of 7 treatment-naïve newly diagnosed JAK2-mutant myeloproliferative neoplasm (MPN) patients (3 polycythemia vera and 4 essential thrombocythemia patients), and 2 healthy controls. The submitted data corresponds to sequencing reads mapped to the human reference genome GhRC38 build using CellRanger for a total of 9 samples (one per patient). In addition, to reconstruct the lineage histories of single cells in MPN patients, we performed whole-genome sequencing of single-cell-derived colonies of hematopoietic stem and progenitor cells from 2 essential thrombocythemia (ET) patients: 22 JAK2-mutant colonies and 20 WT colonies for patient ET 1; and 13 JAK2-mutant colonies and 21 WT colonies for patient ET 2. The submitted data consists of sequencing reads aligned to the human reference genome GhRC38 build using bwa-mem. Each file corresponds to the whole-genome sequencing data for one colony.

  Study phs002308

• GRIDSS, PURPLE, LINX: Unscrambling the tumor genome via integrated analysis of structural variation and copy number

  We have developed a novel, integrated and comprehensive purity, ploidy, structural variant and copy number somatic analysis toolkit for whole genome sequencing data of paired tumor/normal samples. We show that the combination of using GRIDSS for somatic structural variant calling and PURPLE for somatic copy number alteration calling allows highly sensitive, precise and consistent copy number and structural variant determination, as well as providing novel insights for short structural variants and regions of complex local topology. LINX, an interpretation tool, leverages the integrated structural variant and copy number calling to cluster individual structural variants into higher order events and chains them together to predict local derivative chromosome structure. LINX classifies and extensively annotates genomic rearrangements including simple and reciprocal breaks, LINE, viral and pseudogene insertions, and complex events such as chromothripsis. LINX also comprehensively calls genic fusions including chained fusions. Finally, our toolkit provides novel visualisation methods providing insight into complex genomic rearrangements.

  Study EGAS00001004034

• Centers for Common Disease Genomics (CCDG) - Whole Genome Sequencing in Type 1 Diabetes (T1DGC)

  The Type 1 Diabetes Genetics Consortium (T1DGC) was established to collect resources (biological samples and data) and conduct research to better understand the genetic basis of type 1 diabetes (T1D). Collection was initiated by ascertaining affected sib-pair families (both parents, two affected siblings and, when available, an unaffected sibling), collected from five geographic regions through four recruitment networks (Asia-Pacific, Europe, North America, United Kingdom). In addition, the T1DGC collected trio families (both parents and affected child) and cases and controls from low-prevalence populations (African-American, with four grandparents self-reporting as African ancestry; Mexican-American, with four grandparents self-reporting as ancestry from Mexico). The T1DGC also served as a repository for contributed collections from other studies, all meeting the broad data-sharing policy of the T1DGC, for inclusion in the genetic studies. These collections include T1D case samples ascertained from the UK Genetic Resource Investigating Diabetes (UK GRID) cohort, SEARCH for Diabetes in Youth (SEARCH), The Genetics of Kidneys in Diabetes (GoKinD), and control samples obtained from the British 1958 Birth Cohort, the UK National Blood Services collection, CLEAR (Consortium for the Longitudinal Evaluation of African-Americans with Early Rheumatoid Arthritis), the New York Cancer Project (NYCP), and other cohorts. For the NHGRI-funded Centers for Common Disease Genomics (CCDG) project, participants with T1D and ancestry-matched controls were identified through the T1DGC, either through direct ascertainment or by contribution from other sources to the T1DGC. As the CCDG has focused initially on non-Caucasian populations for whole genome sequencing, T1DGC participants of African, Mexican and Asian ancestry (targeting ~1200 cases and ~1200 controls in each ancestral group) and a small group of participants of Northern European ancestry (~100 cases, ~100 controls) were to be contributed to the study. Whole genome sequencing of T1DGC samples would be conducted at Washington University McDonnell Genome Institute and based upon matching case-control status within an ancestry group and prioritization by the CCDG.

  Study phs001222

• Pan Prostate Cancer Group DK BAM files

  This dataset contains the BAM files from 32 Danish patients with prostate cancer, both germline and tumor tissues. These samples are part of the Pan Prostate Cancer Genome project.

  Dataset EGAD50000002318

• Human normal brain bulk RNA-seq

  We profiled 43 normal human adult brain and 11 normal human fetal brain specimens by bulk RNA-seq. The raw fastqs are provided.

  Dataset EGAD00001005130

• Whole genome sequencing of the healthy breast

  Whole genome sequencing of 29 donors of healthy mammary tissue. BAM files of stromal and epithelial DNA are included.

  Dataset EGAD00001006402

• Ovarian cancer cfDNA dataset

  The dataset contains 23 ovarian cancer and 2 healthy control urine cfDNA samples. Shallow WGS was performed on an Illumina Novaseq S4 PE150bp. Samples are provided as raw reads without any prior processing.

  Dataset EGAD00001010848

• ARIC

  Bam files are from matched normal + "very early" plasma (diagnostic) samples, sequenced on Illumina NovaSeq 6000 instrument. After bwa alignment, duplicates were removed by picard markduplicate, and base quality scores recalibrated using gatk baserecalibrator + apply bqsr.

  Dataset EGAD00001015603

• Patient-derived models of primary breast cancer for preclinical development of novel neoadjuvant therapies

  Generation of the first large-scale cohort of mouse intraductal patient-derived xenograft (MIND-PDX) models of primary invasive breast cancer (IBC) and a collection of matched PDX-derived organoids (PDXO) representing all molecular subtypes of IBC, including estrogen receptor (ER-) positive breast cancer. Furthermore, we show that our IBC-MIND cohort can serve as a platform to test experimental neoadjuvant treatment options in different molecular subtypes of breast cancer.

  Study EGAS50000000398

• Integrated Metabolic Profiling and Gene Expression Analysis Reveals Therapeutic Modalities in Breast Cancer

  In this study, we performed metabolite profiling and RNA-sequencing on human breast cancer tumors and normal breast tissue samples, including triple negative breast cancer (TNBC), estrogen receptor positive breast cancer (ER+) and paired normal samples, and patient-derived xenografts (PDX) samples. Here, we report two distinctive groups defined by metabolites; a TNBC-HIGH group that shows high levels of pyrimidine pathway metabolites and biosynthetic enzymes, and an ER-HIGH group that shows high levels of fatty acid and arginine biosynthesis intermediates. We identify different metabolic enrichment profiles between cell lines grown in vitro vs. in vivo; cell lines grown in vivo recapitulate patient tumors metabolic profiles. Further, we identify a subset of genes that strongly correlates with the TNBC-HIGH metabolic profile using integrated metabolic and gene expression profiling, which strongly predicts patient prognosis when tested on larger human datasets. As a proof-of-principle, when we target TNBC-HIGH metabolic dysregulation with a pyrimidine biosynthesis inhibitor (Brequinar), and/or a glutaminase inhibitor (CB-839), we observe therapeutic efficacy and decreased tumor growth in representative TNBC cell lines, murine p53-null mammary tumors, and in vivo patient-derived xenografts (PDXs) upon multi-agent drug treatment. This study highlights potential new therapeutic opportunities in breast cancers guided by a genomic biomarker, which could prove impactful for breast cancers that rapidly proliferate.

  Study phs002396