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• Raw human sequencing data for “Characterization of intestinal immune responses in generalized human and murine lipodystrophy”

  This dataset contains raw FASTQ files generated from peripheral blood and intestinal biopsy samples collected for the study “Characterization of intestinal immune responses in generalized human and murine lipodystrophy.” Peripheral blood sequencing was performed on samples from three healthy donors as controls and from a patient with acquired generalized lipodystrophy and Crohn’s disease (AGLCD) at two distinct timepoints. Intestinal biopsy–derived immune cells were sequenced from three individuals with Crohn’s disease as disease controls, as well as from the AGLCD patient (single timepoint). The data include paired-end FASTQ files derived from single-cell RNA sequencing and T-cell receptor repertoire profiling, enabling analyses of immune composition, transcriptional states, and clonal T-cell expansion. All data are controlled-access human genomic datasets and require appropriate authorization for secondary use.

  Study EGAS50000001517

• Comprehensive benchmarking of methods for mutation calling in circulating tumor DNA

  This study provides a comprehensive benchmarking resource for somatic variant detection in cell-free DNA (cfDNA) from cancer patients. Longitudinal plasma samples from colorectal and breast cancer cohorts were selected to create patient-matched dilution series spanning ultra-low to high circulating-tumour-DNA (ctDNA) fractions, while preserving each individual’s germline and clonal haematopoiesis background. Deep whole-genome sequencing (150×) and ultra-deep whole-exome sequencing (2,000×) generated a reference call set of ~37,000 single-nucleotide variants and ~58,000 insertions/deletions. These data enabled systematic evaluation of nine somatic variant callers across variable ctDNA levels and sequencing depths, and were further used to explore machine-learning–guided parameter tuning. The resulting dataset offers an openly accessible framework for developers and clinicians to assess and optimize somatic variant calling in liquid biopsy applications.

  Study EGAS50000001313

• Multimodal epigenetic sequencing analysis of cell-free DNA identifies biomarkers for ALS diagnosis and progression

  The role of the circulating epigenome in ALS remains understudied. We aim to develop diagnostic and prognostic blood-based biomarkers for Amyotrophic Lateral Sclerosis (ALS) by profiling methylome signatures in circulating cell-free DNA (cfDNA) in 20 sporadic ALS cases, 10 C9orf72-associated ALS cases, 10 asymptomatic C9orf72 expansion carriers, and 21 healthy controls using targeted enzymatic methyl-sequencing (EM-seq) of ~4 million CpG loci. We detected numerous differentially methylated genes, including several implicated in ALS risk and pathobiology, and integrated multiple epigenetic features with our Multimodal Epigenetic Sequencing Analysis (MESA) algorithm, achieving an ROC AUC of 0.91 and detecting ~70% of ALS cases at ~100% specificity. Methylation at a subset of loci also correlated with clinical progression and cerebrospinal-fluid neurofilament levels, supporting the potential of cfDNA-based biomarkers for ALS diagnosis and monitoring.

  Study EGAS50000001267

• Identification of neoantigen from MSI-CRC patient derived organoids and its application for targeting by autologous T cells

  Targeting neoantigens expressed only by tumor cells enable tumor destruction without unexpected damages to healthy tissues. Here, we identified neoantigens from microsatellite instable (MSI) colorectal cancer (CRC) patient-derived organoids by genomics and immunopeptidomics approches. The neoantigens in this study were predicted from frame-shift mutation by whole-genome sequencing and confirmed its presentation on organoids surface class I HLA molecules by mass spectrometry. We utilized these neoantigens to isolate neoantigen-specific CD8 T cells from autologous PBMC, and proved tumor organoids killing ability of the CD8 T cells, whereas it did not attack normal organoids. This study provides a platform to identify neoantigen from patient-derived cancer organoids and a model to validate T cell recognition, which could be useful for adoptive CD8 T cell transfer treatment for MSI-CRC patient.

  Study EGAS00001006633

• 13 WGS and 8 TCS data of ENKL patients treated with pembrolizumab.

  Whole-genome sequencing (WGS) was performed for 13 pairs of tumor-normal samples from patients diagnosed with NKTL. Genomic DNA from tumor tissue was extracted with QIAamp DNA Mini Kit. The DNA for the matching normal was obtained from blood or buccal swabs and purified by Blood and Cell Culture DNA Mini kit or E.Z.N.A. Tissue DNA Kit (Omega Bio-tek) according to manufacturer’s instructions. The quantity and quality were assessed by Quant-iT PicoGreen dsDNA Assay Kit (Invitrogen) and agarose gel electrophoresis. All sequencing libraries were prepared using TruSeq Nano DNA Library Prep Kit (Illumina). Paired-end sequencing was performed on Illumina HiSeq 2000 or HiSeq X Ten as 2x101 bp or 2x151 bp, respectively. 8 NKTL FFPE specimens were screened for somatic mutations using deep targeted capture sequencing (TCS). FFPE rolls or slides were extracted using QIAamp DNA FFPE Tissue kit (QIAGEN). The FFPE genomic DNA was treated with NEBNext FFPE DNA Repair Mix and assessed by Quant-it PicoGreen dsDNA Assay Kit (Invitrogen). The library was generated from 10-200 ng DNA with SureSelectXT Low Input Target Enrichment System for Illumina Paired-End Sequencing Library (Agilent Technologies) according to manufacturer’s instructions. RNA based probe was designed with SureDesign (Agilent Technologies) to target-capture 140 genes. Next, the captured libraries were pooled in equimolar concentration and sequenced on Illumina Novaseq 6000 platform with SP or S1 chip. Reads aligning to 40 selected genes were isolated post-alignment for this submission. Prefix used in filenames: T - Tumor samples N - Matched-Normal samples

  Dataset EGAD00001004140

• Open Targets 020 Epigenomes of Cell Lines (2018-10-23)

  There is currently a drive to establish cell based assay systems of greater human biological and disease relevance through the use of well characterised transformed cell lines, primary cells and complex cellular models (e.g. co-culture, 3D models). However, although the field is gaining valuable experience in running more non-standard & complex cell assays for target validation and compound pharmacology studies, there is the lack of a systematic approach to determine if this expansion in cell assay models is reflected in increased human biological and disease relevance. The increasing wealth of publically available transcriptomic, and epigenome (ENCODE and Epigenome Roadmap) data represents an ideal reference mechanism for determining the relationship between cell types used for target & compound studies to primary human cells and tissues from both healthy volunteers & patients. The CTTV020 epigenomes of cell line project aims to generate epigenetic and transcriptomic profiles of cell lines and compare these with existing and newly generated reference data sets from human tissue and cell types. The aim is to identify assay systems which will provide greater confidence in translating target biology and compound pharmacology to patients. Multiple cell types commonly used within research have been grouped according to biology. Examples include erythroid, lung epithelial, hepatocyte cell types and immortalised models of monocyte / macrophage biology. 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/ . This dataset contains all the data available for this study on 2018-10-23.

  Dataset EGAD00001004413

• Open Targets 020 Epigenomes of Cell Lines (2018-10-23)

  There is currently a drive to establish cell based assay systems of greater human biological and disease relevance through the use of well characterised transformed cell lines, primary cells and complex cellular models (e.g. co-culture, 3D models). However, although the field is gaining valuable experience in running more non-standard & complex cell assays for target validation and compound pharmacology studies, there is the lack of a systematic approach to determine if this expansion in cell assay models is reflected in increased human biological and disease relevance. The increasing wealth of publically available transcriptomic, and epigenome (ENCODE and Epigenome Roadmap) data represents an ideal reference mechanism for determining the relationship between cell types used for target & compound studies to primary human cells and tissues from both healthy volunteers & patients. The CTTV020 epigenomes of cell line project aims to generate epigenetic and transcriptomic profiles of cell lines and compare these with existing and newly generated reference data sets from human tissue and cell types. The aim is to identify assay systems which will provide greater confidence in translating target biology and compound pharmacology to patients. Multiple cell types commonly used within research have been grouped according to biology. Examples include erythroid, lung epithelial, hepatocyte cell types and immortalised models of monocyte / macrophage biology. 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/ . This dataset contains all the data available for this study on 2018-10-23.

  Dataset EGAD00001004414

• Open Targets 020 Epigenomes of Cell Lines (2018-10-23)

  There is currently a drive to establish cell based assay systems of greater human biological and disease relevance through the use of well characterised transformed cell lines, primary cells and complex cellular models (e.g. co-culture, 3D models). However, although the field is gaining valuable experience in running more non-standard & complex cell assays for target validation and compound pharmacology studies, there is the lack of a systematic approach to determine if this expansion in cell assay models is reflected in increased human biological and disease relevance. The increasing wealth of publically available transcriptomic, and epigenome (ENCODE and Epigenome Roadmap) data represents an ideal reference mechanism for determining the relationship between cell types used for target & compound studies to primary human cells and tissues from both healthy volunteers & patients. The CTTV020 epigenomes of cell line project aims to generate epigenetic and transcriptomic profiles of cell lines and compare these with existing and newly generated reference data sets from human tissue and cell types. The aim is to identify assay systems which will provide greater confidence in translating target biology and compound pharmacology to patients. Multiple cell types commonly used within research have been grouped according to biology. Examples include erythroid, lung epithelial, hepatocyte cell types and immortalised models of monocyte / macrophage biology. 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/ . This dataset contains all the data available for this study on 2018-10-23.

  Dataset EGAD00001004416

• RNA-seq as a tool for evaluating human embryo competence

  The majority of embryos that are created through IVF do not implant. It seems plausible that rates of implantation would improve if we had a better understanding of molecular factors affecting embryo competence. Currently, the process of selecting an embryo for uterine transfer utilizes an ad-hoc combination of morphological criteria, the kinetics of development, and genetic testing for aneuploidy. However, no single criterion can ensure selection of a viable embryo. In contrast, RNA-sequencing of embryos could yield highly dimensional data, which may provide additional insight and illuminate the discrepancies among current selection criteria. Indeed, recent advances enabling the production of RNA-sequencing (RNA-seq) libraries from single cells have facilitated the application of this technique to the study of some transcriptional events in early human development. However, these studies have not assessed the quality of their constituent embryos relative to commonly used embryological criteria. Here, we perform proof-of-principle advancement to clinical selection procedures by generating high quality RNA-seq libraries from a trophectoderm biopsy as well as the remaining whole embryo. We combine state-of-the-art embryological methods with low-input RNA-seq to develop the first transcriptome-wide approach for use in future predictive embryology studies. Specifically, we demonstrate the capacity of RNA-seq as a promising tool in preimplantation screening by showing that biopsies of an embryo can capture valuable information content available in the whole embryo from which they are derived. Furthermore, we show that this technique can be used to generate a RNA-based digital karyotype, and to identify candidate competence-associated genes. Together, these data establish the foundation for a future RNA-based diagnostic in IVF.

  Dataset EGAD00001005044

• scRNAseq of colonic organoids derived from biopsies taken from healthy human individuals treated with IL22

  scRNAseq dataset of colonic organoids derived from epithelium from biopsies taken from three healthy human individuals. The organoids have either been grown in standard conditions (control) or treated with IL22 (treated). Includes 6 samples in total, one control from each individual (ctrl1, ctrl2, ctrl3) and one treated from each (treat1, treat2, treat3). The samples have been multiplexed using the antibody hashing technique. The 6 samples have been pooled into the one organoids sample. In order to analyse the raw files, they have to be demultiplexed first. Information necessary for demultiplexing, as well as which files belong to which sample, can be found in the map_file.csv, attached to each sample. Dataset includes raw Fastq files and processed csv count matrices. Fastq files are divided into HTO (hashtag) and RNA (transcriptome) files. HTO has one index (I1) and two read (R1, R2) files and RNA has two index (I1, I2) and two read (R1, R2) files. The fastq files are for the pooled (organoids) sample and need to be demultiplexed. Count matrices contain comma-separated values with cell barcodes as column names and gene names as row names. Since count matrices have been created after the demultiplexing step, there’s one matrix for each of the 6 individual samples. scRNA-seq data from human colon organoids was analysed in the same manner as for the Colitis dataset, apart from the following changes. Data was generated with the Cell Hashing technique, which uses oligo-tagged antibodies against surface proteins to barcode single cells. This allows for samples to be multiplexed together and run in a single experiment. The data was demultiplexed using the HTODemux() function from Seurat (Hao et al., 2021).

  Dataset EGAD00001010168

• A Collaborative Search for New Genes for Non-Syndromic Deafness

  We seek to identify the DNA variants underlying sensorineural hearing loss. We obtain the DNA sequence of affected individuals and their family members. DNA variants are filtered to determine their segregation in affected families.

  Study phs003701

• Genetic analysis in lifestyle-related disease, arteriosclerotic disease, and aging-related diseases.

  Exome sequence analysis was conducted in patients with hypertension (Stage 3). Rare variants in candidate susceptible genes discovered by previous GWASs were prioritised and further analysed for an additional case-control association study.

  Study JGAS000016

• 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

• A_study_of_the_molecular_pathogenesis_of_Splenic_Marginal_Zone_and_Diffuse_Large_B_Cell_Lymphoma

  We will perform exome sequencing on selected cases of splenic marginal zone lymphoma (SMZL) and diffuse large B-cell lymphoma (DLBCL) in order to characterise their genetic makeup and identify biomarkers for prognosis and prediction of treatment response.

  Study EGAS00001000335

• CIAO Clinical Trial

  Whole exome and RNA sequencing for samples from CIAO (Checkpoint Inhibitors Assessment in Oropharynx cancer) (NCT03144778) clinical trial testing neoadjuvant anti-PD-L1 durvalumab with or without the anti-CTLA-4 tremelimumab in oropharynx cancer

  Study EGAS50000001174

• 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

• TCELL_PILOT_ATAC_SEQ

  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/

  Study EGAS00001000758

• Lymphocyte_RNA_profiling

  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/

  Study EGAS00001000564

• Whole exome sequencing of papillary thyroid carcinoma in the Chinese population

  Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer. Here we submitted the sequencing results for PTC using 91 tumor-normal pairs through exome sequencing in the Chinese Han population.

  Study EGAS00001001268

• Preclinical_evolution_of_haematological_malignancies_

  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/

  Study EGAS00001002128

• CELM

  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/

  Study EGAS00001002261

• Whole-exome analysis of corticotropin-independent Cushing's syndrome

  We performed WES for 8 cases with corticotropin-independent Cushing’s syndrome, in whom paired tumor and normal DNA was obtained from fresh frozen adenomas and either normal adrenal tissues or peripheral blood, respectively.

  Study EGAS00001000661

• Genetics_and_Networks_of_Congenital_Heart_Defects

  Exome sequencing of families with Congenital Heart Defects of diverse sub-phenotypes. Comprises both parent-offspring trios for sporadic cases and multiplex families. Collaboration with David Brook, University of Nottingham. Funded by the British Heart Foundation.

  Study EGAS00001000762

• Characterization_of_iPSC_derived_macrophages___cardiovascular_pilot

  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/

  Study EGAS00001000876

• Genetic and expression landscape of Waldenstrom macroglobulinemia

  Exome analyses for the identification of somatic mutation in Waldenstrom macroglobulinemia by comparison of tumor and CD3+(germ line control) population in 16 patients. transcription profiling of a series of Waldenstrom macroglobulinemia samples

  Study EGAS00001003603

• LifeLines-NEXT pilot study

  The pilot study from the LifeLines-NEXT (NEXT) cohort consisting of 30 mother-infant pairs with longitudinal sampling from pregnancy till 3 months after birth. Shotgun data is available for virome and microbiome annotation.

  Study EGAS00001005969

• RNA-sequencing of platelets and immortalized megakaryocyte cell lines for inherited thrombocytopenia

  Total RNA-sequencing of platelets and immortalized megakaryocyte cell lines for inherited thrombocytopenia. Libraries were prepared using Illumina TruSeq Stranded Total RNA with Ribo-Zero Gold kits. The samples were paired-end sequenced using the NovaSeq 6000 platform at a depth of 60 million reads per sample with a read length of 100 base pairs.

  Dataset EGAD50000001818

• M116 CHIP Amplicon Sequencing

  Genomic DNA was obtained from M116 peripheral blood sample and was used for targeted deep sequencing (TDS) studies. Barcoded libraries were prepared according to the manufacturer’s instructions, using a probe-based panel (KAPA HyperCap, Roche®) targeting frequently mutated regions of 50 myeloid-related genes. Samples were run on a MiSeq (Illumina®) sequencer for paired-end 2x75 bp reads with a mean coverage of 1000X.

  Dataset EGAD50000001287

• Patient-derived organoids cohort raw FASTQ from SGMedical

  Raw FASTQ files for a glioblastoma multiforme organoid study, including exome sequencing and RNA-seq. 29 runs (paired-end), 58 FASTQ.c4gh files (R1/R2). Short-read Illumina; library strategies include exome capture and stranded total RNA-seq (see Experiment records for kit/instrument details). No processed results are included; access is controlled under the selected Policy.

  Dataset EGAD50000001741

• 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

• EDi018-A / SAMEA4771918 WGS data

  The iPSC line EDi018-A / SAMEA4771918 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 EDi018-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001027

• EDi019-A / SAMEA4774918 WGS data

  The iPSC line EDi019-A / SAMEA4774918 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 EDi019-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001029

• RCi009-A / SAMEA4339688 WGS data

  The iPSC line RCi009-A / SAMEA4339688 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 RCi009-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001030

• EDi016-A / SAMEA4562366 WGS data

  The iPSC line EDi016-A / SAMEA4562366 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 EDi016-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001032

• EDi017-A / SAMEA4768918 WGS data

  The iPSC line EDi017-A / SAMEA4768918 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 EDi017-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001033

• EDi019-C / SAMEA4777168 WGS data

  The iPSC line EDi019-C / SAMEA4777168 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 EDi019-C is available for research use at www.EBiSC.org.

  Dataset EGAD50000001036

• EDi010-A / SAMEA4459354 WGS data

  The iPSC line EDi010-A / SAMEA4459354 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 EDi010-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001038

• BIONi010-C / SAMEA3158050 WGS data

  The iPSC line BIONi010-C / SAMEA3158050 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 BIONi010-C is available for research use at www.EBiSC.org.

  Dataset EGAD50000001039

• UKKi019-C / SAMEA17626918 WGS data

  The iPSC line UKKi019-C / SAMEA17626918 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-C is available for research use at www.EBiSC.org.

  Dataset EGAD50000001042

• EDi011-B / SAMEA4459359 WGS data

  The iPSC line EDi011-B / SAMEA4459359 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 EDi011-B is available for research use at www.EBiSC.org.

  Dataset EGAD50000001044

• EDi011-C / SAMEA4459360 WGS data

  The iPSC line EDi011-C / SAMEA4459360 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 EDi011-C is available for research use at www.EBiSC.org.

  Dataset EGAD50000001045

• EDi012-A / SAMEA4459361 WGS data

  The iPSC line EDi012-A / SAMEA4459361 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 EDi012-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001046

• EDi015-A / SAMEA4459373 WGS data

  The iPSC line EDi015-A / SAMEA4459373 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 EDi015-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001047

• EDi015-C / SAMEA4459376 WGS data

  The iPSC line EDi015-C / SAMEA4459376 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 EDi015-C is available for research use at www.EBiSC.org.

  Dataset EGAD50000001048

• EDi017-B / SAMEA4770418 WGS data

  The iPSC line EDi017-B / SAMEA4770418 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 EDi017-B is available for research use at www.EBiSC.org.

  Dataset EGAD50000001049

• EDi011-A / SAMEA4459357 WGS data

  The iPSC line EDi011-A / SAMEA4459357 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 EDi011-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001050

• EDi013-B / SAMEA4459367 WGS data

  The iPSC line EDi013-B / SAMEA4459367 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 EDi013-B is available for research use at www.EBiSC.org.

  Dataset EGAD50000001052

• BIONi010-A / SAMEA3105765 WGS data

  The iPSC line BIONi010-A / SAMEA3105765 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 BIONi010-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001054

• 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

• UKKi019-A / SAMEA17624668 WGS data

  The iPSC line UKKi019-A / SAMEA17624668 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-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001094