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• UKKi019-B / SAMEA17626168 WGS data

  The iPSC line UKKi019-B / SAMEA17626168 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line UKKi019-B is available for research use at www.EBiSC.org.

  Dataset EGAD50000001096

• A non-canonical lymphoblast in refractory childhood T-cell leukaemia

  Single cell mRNAseq of T-ALL samples including presentation samples for 13 with refractory disease and 8 with responsive disease, and Day 28 samples for 8 patients with refractory disease. Also includes bulk mRNA sequencing on 6 of the patients with responsive disease.

  Dataset EGAD50000001128

• Mitochondrial DNA Mutations at Low-level Heteroplasmy in Chronic Kidney Disease

  To explore for relationship between somatic or heteroplasmic mutations of mtDNA and kidney function, we here performed ultra-deep sequencing based on long-range PCR from DNAs of 78 CKD kidney tissues.

  Study JGAS000611

• Diverse Cellular Composition in Alveolar Rhabdomyosarcoma Revealed by Single Cell RNA Sequencing

  Using single cell RNAseq data to characterize tumor composition and cellular states for Alveolar Rhabdomyosarcoma. We find that that ARMS tumors harbor phenotypically and transcriptionally distinct malignant subpopulations within an immune-influenced microenvironment.

  Study EGAS50000001564

• Single Cell Targeted DNA sequencing for Variant Calling in T-ALL

  This dataset contains the raw fastq-files and the VCF files of single cell targeted DNA sequening with the MissionBio Tapestri platform. This was performed on 8 male pediatric T-ALL cases: X09-XB37-XB47-XD83-XF91-XF97-XF100-XF121. For some patients we have timepoints during treatment: XF100 and XG121. XD83 is a patient that relapsed twice.

  Dataset EGAD00001006167

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cells, (ChIP-Seq_H3K27me3 for mature neutrophil, on genome GRCh37)

  ChIP-Seq_H3K27me3 data for 131 mature neutrophil sample(s). 321 run(s), 134 experiment(s), 134 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002712

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cells, (ChIP-Seq_H3K4me3 for mature neutrophil, on genome GRCh37)

  ChIP-Seq_H3K4me3 data for 133 mature neutrophil sample(s). 208 run(s), 136 experiment(s), 136 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002711

• X Ten analysis of spiked placental tissue samples

  Metagenomics data of 80 placental tissue samples analyzed by X Ten for their possible microbial content. These 80 samples from pre-labor C-section deliveries, representing Cohort 1, were spiked with 1100 CFU Salmonella bongori. These same samples were also analyzed by 16S amplicon sequencing (search for ERP109246 in ENA).

  Dataset EGAD00001004198

• Metagenome for FINRISK2002

  The dataset contains data for n=7211 FINRISK 2002 participants who underwent fecal sampling. Demultiplexed shallow shotgun metagenomic sequences were quality filtered and adapter trimmed using Atropos (Didion et al., 2017), and human filtered using Bowtie2 (Langmead and Salzberg, 2012). The files are in FASTQ format.

  Dataset EGAD00001007035

• National Children's Study Vanguard Study Formative Research Study (NCS)

  The National Children's Study (NCS) is a multi-year prospective epidemiological study tasked with identifying a nationally representative sample of 100,000 children and following them from pregnancy through age 21 to study environmental impacts on growth, development, and health. Determination of NCS enrollee ancestry is important for assessing the diversity of study enrollees and for examining the effect of ancestry on various health outcomes. We estimated the genetic ancestry of a convenience sample of 641 parents enrolled at the 7 original NCS Vanguard sites by analyzing 29,972 markers on exome arrays, using the participants of the 1000 Genomes Project (1KG) super populations (e.g. European, East Asian) as reference populations, and compared this to self-reported ethnicity and race. Self-reported ethnicity and race agreed with predicted super population in 98.9% of individuals. NCS individuals identified as Asian by self-report had genetic ancestry of either South Asian or Asian groups, while those reporting as either Hispanic White or Hispanic Other had similar genetic ancestry. Of the 33 individuals who self-reported as Multiracial or Non-Hispanic Other, 11 (33%) matched the South Asian and Asian groups, while these groups were less represented in the other reported categories (27/609, 4.4%). Our data suggest that self-reported ethnicity and race categories have some limitations in accurately capturing this information for Hispanic and South Asian populations. Overall, our data indicate that despite the complexity of the U.S. population, individuals know their ancestral origins and that self-reported ethnicity and race is a reliable indicator of genetic ancestry.

  Study phs000662