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• EGAD00010000744

  Subset 2 of osteoarthritis cases genotyped on Illumina 610k from the arcOGEN Consortium (http://www.arcogen.org.uk/) with consent for osteoarthritis studies only.

  Dataset EGAD00010000744

• ICGC PCAWG Dataset: PACA-CA_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: PACA-CA.

  Dataset EGAD00001003162

• Constit Genome Sequencing

  WGS blood data (fastq raw read sequences) for French ICGC leiomyosarcoma cancer sequencing project, 67 samples representing 67 donors. Sequencing was performed on Illumina HiSeq. The libraries were then sequenced with a 2 x 100bp paired-end protocol to a minimum mean coverage of 30x.

  Dataset EGAD00001003190

• Leiomyosarcoma Cancer Genome Sequencing

  WGS cancer data (fastq raw read sequences) for French ICGC leiomyosarcoma cancer sequencing project, 78 samples representing 67 donors. Sequencing was performed on Illumina HiSeq. The libraries were then sequenced with a 2 x 100bp paired-end protocol to a minimum mean coverage of 50x.

  Dataset EGAD00001003191

• ICGC PCAWG Dataset: OV-AU_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: OV-AU.

  Dataset EGAD00001003227

• NIHR BioResource Rare Diseases WGS project - Steroid Resistant Nephrotic Syndrome (SRNS) Rare Disease domain

  Short read whole genome sequencing (WGS) CRAM files for the NIHR BioResource Rare Diseases WGS project – Participants from the Steroid Resistant Nephrotic Syndrome (SRNS) Rare Disease domain

  Dataset EGAD00001004518

• NIHR BioResource Rare Diseases WGS project - Cerebral Small Vessel Disease (CSVD) Rare Disease domain

  Short read whole genome sequencing (WGS) CRAM files for the NIHR BioResource Rare Diseases WGS project – Participants from the Cerebral Small Vessel Disease (CSVD) Rare Disease domain

  Dataset EGAD00001004513

• NIHR BioResource Rare Diseases WGS project - Hypertrophic Cardiomyopathy (HCM) Rare Disease domain

  Short read whole genome sequencing (WGS) CRAM files for the NIHR BioResource Rare Diseases WGS project – Participants from the Hypertrophic Cardiomyopathy (HCM) Rare Disease domain

  Dataset EGAD00001004514

• NIHR BioResource Rare Diseases WGS project - Intrahepatic Cholestasis of Pregnancy (ICP) Rare Disease domain

  Short read whole genome sequencing (WGS) CRAM files for the NIHR BioResource Rare Diseases WGS project.Participants from the Intrahepatic Cholestasis of Pregnancy (ICP) Rare Disease domain

  Dataset EGAD00001004515

• NIHR BioResource Rare Diseases WGS project - Neuropathic Pain Disorders (NPD) Rare Disease domain

  Short read whole genome sequencing (WGS) CRAM files for the NIHR BioResource Rare Diseases WGS project – Participants from the Neuropathic Pain Disorders (NPD) Rare Disease domain

  Dataset EGAD00001004516

• NIHR BioResource Rare Diseases WGS project - Primary Membranoproliferative Glomerulonephritis (PMG) Rare Disease domain

  Short read whole genome sequencing (WGS) CRAM files for the NIHR BioResource Rare Diseases WGS project – Participants from the Primary Membranoproliferative Glomerulonephritis (PMG) Rare Disease domain

  Dataset EGAD00001004517

• NIHR BioResource Rare Diseases WGS project - Bleeding, Thrombotic and Platelet Disorders (BPD) Rare Disease domain

  Short read whole genome sequencing (WGS) CRAM files for the NIHR BioResource Rare Diseases WGS project – Participants from the Bleeding, Thrombotic and Platelet Disorders (BPD) Rare Disease domain

  Dataset EGAD00001004519

• NIHR BioResource Rare Diseases WGS project - Inherited Retinal Disorders (IRD) Rare Disease domain

  Short read whole genome sequencing (WGS) CRAM files for the NIHR BioResource Rare Diseases WGS project – Participants from the Inherited Retinal Disorders (IRD) Rare Disease domain

  Dataset EGAD00001004520

• NIHR BioResource Rare Diseases WGS project - Multiple Primary Malignant Tumours (MPMT) Rare Disease domain

  Short read whole genome sequencing (WGS) CRAM files for the NIHR BioResource Rare Diseases WGS project – Participants from the Multiple Primary Malignant Tumours (MPMT) Rare Disease domain

  Dataset EGAD00001004521

• NIHR BioResource Rare Diseases WGS project - Neurological and Developmental Disorders (NDD) Rare Disease domain

  Short read whole genome sequencing (WGS) CRAM files for the NIHR BioResource Rare Diseases WGS project – Participants from the Neurological and Developmental Disorders (NDD) Rare Disease domain

  Dataset EGAD00001004522

• NIHR BioResource Rare Diseases WGS project - Primary Immune Disorders (PID) Rare Disease domain

  Short read whole genome sequencing (WGS) CRAM files for the NIHR BioResource Rare Diseases WGS project.Participants from the Primary Immune Disorders (PID) Rare Disease domain

  Dataset EGAD00001004523

• ICGC PCAWG Dataset: MALY-DE_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: MALY-DE.

  Dataset EGAD00001002123

• ICGC PCAWG Dataset: EOPC-DE_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: EOPC-DE.

  Dataset EGAD00001002124

• ICGC PCAWG Dataset: BOCA-UK_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: BOCA-UK.

  Dataset EGAD00001002125

• ICGC PCAWG Dataset: PRAD-UK_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: PRAD-UK.

  Dataset EGAD00001002126

• ICGC PCAWG Dataset: PBCA-DE_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: PBCA-DE.

  Dataset EGAD00001002127

• ICGC PCAWG Dataset: PRAD-CA_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: PRAD-CA.

  Dataset EGAD00001002128

• ICGC PCAWG Dataset: BRCA-EU_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: BRCA-EU.

  Dataset EGAD00001002129

• ICGC PCAWG Dataset: CLLE-ES_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: CLLE-ES.

  Dataset EGAD00001002130

• ICGC PCAWG Dataset: RECA-EU_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: RECA-EU.

  Dataset EGAD00001002131

• ICGC PCAWG Dataset: PACA-AU_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: PACA-AU.

  Dataset EGAD00001002132

• ICGC PCAWG Dataset: PAEN-IT_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: PAEN-IT.

  Dataset EGAD00001002153

• ICGC PCAWG Dataset: PAEN-AU_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: PAEN-AU.

  Dataset EGAD00001002154

• ICGC PCAWG Dataset: LIRI-JP_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: LIRI-JP.

  Dataset EGAD00001002155

• ICGC PCAWG Dataset: ESAD-UK_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: ESAD-UK.

  Dataset EGAD00001002156

• ICGC PCAWG Dataset: MELA-AU_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: MELA-AU.

  Dataset EGAD00001002157

• RNA-seq BAM files from newborn screening dried blood spot samples

  Paired-end RNA-seq BAM files from 21 newborn screening dried blood spot (DBS) samples. These DBS samples were obtained from extremely low gestional age newborns, where 10 of them were affected by a fetal inflammatory response (FIR) before birth, and 11 were unaffected. Total RNA was sequenced using an Illumina NextSeq-500 instrument. The sample preparation protocol included the depletion of rRNA and globin mRNA using the Globin Zero Gold rRNA Removal Kit from Illumina. Libraries were prepared using the NebNext Ultra TM II Directionl RNA LIbrary Prep Kit (New England Biolabs). There is one BAM file per sample and there is an additional BAM file, corresponding to sample BS13, which was downsampled to 1/4 of its original depth (see BS13_README file for details).

  Dataset EGAD00001005009

• Pseudotime ordering of cell cycle state (2020-01-29)

  We will be using G&T method to sequence single cell genome and transcriptome derived from FS13B iPSCs cell line. The cell cycle state of each of the single cells is known. Hence, we will be analysing the genome and transcriptome of single cells from each of the cell cycle state to generate a copy number profile and transcriptome profile per given cell cycle stage: G1, S, G2, S. . This dataset contains all the data available for this study on 2020-01-29.

  Dataset EGAD00001005919

• DNA methylation sequencing profiles of 1538 breast tumors and 244 normal breast tissues

  DNA methylation sequencing profiles of 1538 breast tumors and 244 normal breast tissues. Libraries were prepared using a custom Reduced Representation Bisulfite Sequencing pipeline. Sequencing was performed on the Illumina HiSeq 2500 (v4 chemistry), with single-end reads of 125 bp length. Multiplexing was conducted at the level of 8 samples per lane. FASTQ files are provided for 1538 breast tumors and 244 normal breast tissues. Reference: Batra et al. (2021). DNA methylation landscapes of 1538 breast cancers reveal a replication-linked clock, epigenomic instability and cis-regulation.

  Dataset EGAD00001007976

• Leiomyosarcoma Whole Genome Sequencing

  DNA was extracted from fresh frozen LMS material for 29 untreated tumors (24 primary tumors, 5 metastatic 13 relapses) and 13 tumors treated with radiation (7 primaries, 6 metastatic relapses). DNA from matched blood was used as a normal reference. Whole-genome sequencing was performed using established protocols on Illumina instruments.

  Dataset EGAD00001007722

• RNAseq data

  Bulk RNAseq of sigmoid colon biopsies from healthy volunteers and ulcerative colitis patients. Subjects were treated with Placebo or IL-22Fc at different doses, and biopsies were collected at day 0 and day 30 post treatment and prepared for RNA sequencing.

  Dataset EGAD00001008816

• Fecal 16S UC sequencing data

  Fecal 16S-V4 rRNA gene sequence data from NCT02749630 ulcerative colitis patients. Stool samples were collected at screening as well as on days 29, 43, 64, 85, and 134 processed for 16SV4 rRNA gene sequencing

  Dataset EGAD00001008818

• Fecal 16S HV sequencing data

  Fecal 16S-V4 rRNA gene sequence data from NCT02749630 healthy volunteers. Stool samples were collected at screening as well as on days 29, 43, 64, 85, and 134 processed for 16SV4 rRNA gene sequencing

  Dataset EGAD00001008840

• Fecal WMS HV sequencing data

  Fecal WMS data from NCT02749630 healthy volunteers. Stool samples were collected at screening as well as on days 29, 43, and 64 and prepared for whole metagenomic sequencing.

  Dataset EGAD00001008841

• cfMethyl-Seq

  cfMethyl-Seq libraries were generated for 479 cfDNA samples and were sequenced with 150 bp paired-end reads.

  Dataset EGAD00001009003

• Garvan/St Vincent’s Prostate Cancer Tissue and Data

  The cohort (n=53) consists of prostate cancer patients from Australia. For each patient, a pair of blood and tumour samples were collected. The sequencing data was mapped to hg38 reference. Blood BAMs are named with “-B” as suffix and tumour BAMs are named with “-T” as suffix.

  Dataset EGAD00001009066

• Single nuclei RNA-Seq from 5 regions of the human fetal brain

  Data generated through single nuclei RNA sequencing on 5 regions of the brain (frontal cortex, ganglionic eminence, hippocampus, thalamus and cerebellum) from 3 fetuses (two of 14 and one of 15 post-conception weeks, all female). Tissue was acquired from the MRC-Wellcome Trust Human Developmental Biology Resource (HDBR) with ethical approval. snRNA-seq libraries were prepared from ∼10,000 nuclei from each sample using Chromium Single Cell 3ʹ (v3) reagents (10X Genomics). Quality control of libraries was performed using the Agilent 5200 Fragment Analyzer before sequencing on an Illumina NovaSeq 6000 to a depth of at least 865 million (median = 1.01 billion) read pairs per library. Raw sequencing data were converted into FASTQ files. For a full description of data generation, please see Cameron et al, Biological Psychiatry 2022, https://doi.org/10.1016/j.biopsych.2022.06.033.

  Dataset EGAD00001009303

• Roche Alzheimer's dataset

  The Roche Alzheimer’s disease dataset (Roche_AD) consists of 80 samples from 40 unique individuals (one sample from the temporal cortex and one from deep white matter for each individual, 12 cases, 25 controls, 3 dementia). A total of 12,000 estimated cells from each sample were loaded on the 10x Single Cell Next GEM G Chip. cDNA libraries were prepared using the Chromium Single Cell 3’ Library and Gel Bead v3 kit according to the manufacturer’s instructions. cDNA libraries were sequenced using the Illumina NovaSeq 6000 System and NovaSeq 6000 S2 Reagent Kit v1.5 (100 cycles), aiming at a sequencing depth of minimum 30K reads/nucleus.

  Dataset EGAD00001009166

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0168_003

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0168_003 for Follicular lymphoma patient sample TFRI_Cont_3

  Dataset EGAD00001010205

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0170_003

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0170_003 for Follicular lymphoma patient sample TFRI_Cont_5

  Dataset EGAD00001010207

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0167_003

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0167_003 for Follicular lymphoma patient sample TFRI_Cont_2

  Dataset EGAD00001010204

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0169_003

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0169_003 for Follicular lymphoma patient sample TFRI_Cont_4

  Dataset EGAD00001010206

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0171_003A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0171_003A for Follicular lymphoma patient sample TFRI_Cont_6

  Dataset EGAD00001010208

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0178_003A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0178_003A for Follicular lymphoma patient sample TFRI_Cont_8

  Dataset EGAD00001010209

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0187_003A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0187_003A for Follicular lymphoma patient sample TFRI_Cont_10

  Dataset EGAD00001010211