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• Genotyping by OncoArray and Global Screening Array for colorectal cancer risk prediction

  The study was conducted to build a Polygenic risk scores (PRS) based on a reported set of 140 single nucleotide polymorphisms that were identified to be associated with a higher risk of colorectal cancer (CRC). Genotyping by OncoArray and Global Screening Array was performed using DNA extracted from blood samples collected at baseline of 187 participants who develop CRC and 176 randomly selected controls without diagnosis of CRC identified within 14 years of follow-up.

  Study EGAS00001005411

• Illumina RNA sequencing for HLA expression qauntification

  In this study, we quantified mRNA expression levels of HLA class I and II genes from peripheral blood samples of 50 healthy individuals. The gene- and allele-specific mRNA expression was assessed using unique molecular identifiers, which enabled PCR bias removal and calculation of the number of original mRNA transcripts. We identified differences in mRNA expression between different HLA genes and alleles. Our results suggest that HLA alleles are differentially expressed and these differences in expression levels are quantifiable using RNA sequencing technology.

  Study EGAS00001004931

• Transcriptomic predictors of survival for palbociclib + endocrine therapy vs. capecitabine in aromatase inhibitor-resistant breast cancer from GEICAM/2013-02 PEARL

  We examined transcriptomic tumor features associated with survival from GEICAM/2013-02 PEARL, a phase III trial of palbociclib + ET vs. capecitabine in aromatase inhibitor-resistant HR+/HER2- MBC. PAM50 intrinsic subtype predicted PFS differences between palbociclib + ET and capecitabine, and lower B-cell-associated gene expression predicted longer OS with palbociclib + ET vs. capecitabine. These features may help identify HR+/HER2- tumors resistant to further ET-based treatment with CDK4/6 inhibitors.

  Study EGAS00001008177

• Progressive supranuclear palsy - bulk RNA seq of prefrontal cortex

  Dataset corresponding to the bulk RNA-seq dataset from prefrontal cortex for a total of N=42 samples. Tissue samples correspond to donors with pathologically confirmed progressive supranuclear palsy. RNA-seq was carried out using ribosomal depletion. Dataset contains paired fastq files, sample metadata and downstream quantification files. Quantification was performed with salmon v1.3.0 with Gencode 35 (GRCh38.p13).

  Dataset EGAD50000002623

• Multiple system atrophy - bulk RNA seq of prefrontal cortex

  Dataset corresponding to the bulk RNA-seq dataset from prefrontal cortex for a total of N=35 samples. Tissue samples correspond to donors with pathologically confirmed multiple system atrophy. RNA-seq was carried out using ribosomal depletion. Dataset contains paired fastq files, sample metadata and downstream quantification files. Quantification was performed with salmon v1.3.0 with Gencode 35 (GRCh38.p13). N=6 samples are overlapping with EGAS50000000301.

  Dataset EGAD50000002624

• Alzheimer's disease - bulk RNA seq of prefrontal cortex

  Dataset corresponding to the bulk RNA-seq dataset from prefrontal cortex for a total of N=72 samples. Tissue samples correspond to donors with pathologically confirmed Alzheimer's disease. RNA-seq was carried out using ribosomal depletion. Dataset contains paired fastq files, sample metadata and downstream quantification files. Quantification was performed with salmon v1.3.0 with Gencode 35 (GRCh38.p13).

  Dataset EGAD50000002625

• Dementia with Lewy bodies - bulk RNA seq of prefrontal cortex

  Dataset corresponding to the bulk RNA-seq dataset from prefrontal cortex for a total of N=80 samples. Tissue samples correspond to donors with pathologically confirmed dementia with Lewy bodies. RNA-seq was carried out using ribosomal depletion. Dataset contains paired fastq files, sample metadata and downstream quantification files. Quantification was performed with salmon v1.3.0 with Gencode 35 (GRCh38.p13).

  Dataset EGAD50000002626

• Parkinson's disease - bulk RNA seq of prefrontal cortex

  Dataset corresponding to the bulk RNA-seq dataset from prefrontal cortex for a total of N=448 samples. Tissue samples correspond to donors with pathologically confirmed Parkinson's disease. RNA-seq was carried out using ribosomal depletion. Dataset contains paired fastq files, sample metadata and downstream quantification files. Quantification was performed with salmon v1.3.0 with Gencode 35 (GRCh38.p13). N=81 samples are overlapping with EGAS50000000301.

  Dataset EGAD50000002627

• Controls - bulk RNA seq of prefrontal cortex

  Dataset corresponding to the bulk RNA-seq dataset from prefrontal cortex for a total of N=283 samples. Tissue samples correspond to health control donors. RNA-seq was carried out using ribosomal depletion. Dataset contains paired fastq files, sample metadata and downstream quantification files. Quantification was performed with salmon v1.3.0 with Gencode 35 (GRCh38.p13). N=21 samples are overlapping with EGAS50000000301.

  Dataset EGAD50000002628

• Corticobasal degeneration - bulk RNA seq of prefrontal cortex

  Dataset corresponding to the bulk RNA-seq dataset from prefrontal cortex for a total of N=17 samples. Tissue samples correspond to donors with pathologically confirmed corticobasal degeneration. RNA-seq was carried out using ribosomal depletion. Dataset contains paired fastq files, sample metadata and downstream quantification files. Quantification was performed with salmon v1.3.0 with Gencode 35 (GRCh38.p13).

  Dataset EGAD50000002629

• Microbiome

  16S-sequencing: All stool samples were processed according to the standards of the Flemish Gut Flora Project (Falony et al., 2016). All samples were processed together and sequenced in as a single batch (dual index run DI23R22) which included positive controls (PC, identical stool sample), negative controls (PCR-mix) and ‘blanks’ or negative controls of the extraction (no sample). In addition, a Runella strain (RS) was included to check for potential cross-contamination, as this strain is not present in human samples. The V4 region of the 16S rRNA gene was amplified with the primer pair 515F and 806R (GTGYCAGCMGCCGCGGTAA and GGACTACNVGGGTWTCTAAT, resp.), modified to contain a barcode sequence between each primer and the Illumina adaptor sequences to produce dual- barcoded libraries (Tito et al., 2019). Sequencing was performed on the Illumina MiSeq. Sequences were processed using the LotuS (Hildebrand et al., 2014) and DADA2 pipeline (Callahan et al., 2016) using RDP 16 as the reference taxonomy.

  Dataset EGAD50000002027

• Single cell RNA sequencing of mononuclear cells from synovial fluid of patients with rheumatoid arthritis

  Mononuclear cells were collected from synovial fluid of anti-citrullinated positive antibodies (ACPA)-positive rheumatoid arthritis patients (n=8) and ACPA-negative RA patients (n=8). Global cell types (i.e., no enrichment) were obtained from these cryopreserved synovial fluid mononuclear cells (SFMC) samples and immediately fixed and processed using the GEM-X Flex Gene Expression Reagent Kits (10x Genomics) according to protocol. Following Gel Bead-in Emulsion (GEM) generation, samples were processed using the standard manufacturer’s protocol. Once sequencing libraries passed standard quality control metrics, libraries were sequenced on an Illumina NextSeq2000 P4 100 cycle reagent kit with the following read structure: R1: 28, R2: 90, I1: 10, I2: 10. Libraries were sequenced to obtain a read depth greater than 10,000 reads/cell for gene-expression (GEX). FASTQ files are made available. More detailed information can be obtained in Argyriou A. et al, Annals of the Rheumatic Disease, 2025.

  Dataset EGAD50000001801

• DIAMOND PCR : plasma DNA LINE-1 targeted bisulfite sequencing, a new non-invasive multi-cancer detection marker

  The detection of circulating tumor DNA, which allows non-invasive tumor molecular profiling and disease follow-up, promises optimal and individualized management of patients with cancer. However, detecting small fractions of tumor DNA released when the tumor burden is reduced remains a challenge. We developed a PCR-based targeted bisulfite method coupled to deep sequencing to detect methylation patterns of L1PA elements,which we named DIAMOND (for Detection of Long Interspersed Nuclear Element Altered Methylation ON plasma DNA). We used sodium bisulfite chemical conversion to achieve base-pair resolution analysis and designed a multiplexed PCR based on 8 amplicons covering L1PAs .

  Dataset EGAD50000000646

• Calprotectin in vitro effects on human early hematopoiesis

  Dataset content : Raw data from sequencing (fastq) 184 samples from 4 experiments : - Bulk mRNA seq - 24h and 48h, CTRL, CAL, IL6 and combination treatment - single-cell RNAseq - 7days CTRL, CAL, IL6 and combination treatment - ATACseq - 7days CTRL, CAL, IL6 and combination treatment To explore the effects of calprotectin (CAL) on early hematopoiesis, we incubated CD34+ cells from four healthy donors for 7 days in the presence of stem cell factor (SCF), FLT3-ligand and thrombopoietin (TPO) without and with CAL, interleukin-6 (IL6) and the IL6_CAL combination before collecting cells. We performed the same experiment with CD34+ cells collected from three patients with JAK2-V617F-mediated myelofibrosis (MF). A total of 135,545 cells from healthy donors and 111,725 cells from myelofibrosis patients were analyzed by single-cell RNA sequencing (scRNA-seq) using the 10X Chromium droplet-based platform.

  Dataset EGAD50000000659

• A single-cell multi-omic atlas of nodal B-cell non-Hodgkin lymphomas

  CITE-Seq (cellular indexing of transcriptomes and epitopes) of 51 lymph node (LN) samples from including mantle cell lymphoma (MCL, n = 8), follicular lymphoma (FL, n = 12), germinal center (GCB, n = 5) or activated B-cell (non-GCB/ABC, n = 7) diffuse large B-cell lymphoma (DLBCL), and marginal zone lymphomas (MZL, n = 11), in addition to non-malignant reactive lymph nodes (rLN, n = 8). Of the malignant LN samples, 20 were collected at the time of initial diagnosis and 23 were from patients who had previously undergone one or more lines of systemic treatment. Relapse samples were collected at least 3 months after cessation of systemic treatment. This dataset also includes 5 prime RNA sequencing and immune receptor sequencing (10X Genomics) for 11 of these samples (2 rLN, 2 MCL, 3 FL, 2 DLBCL (GCB) and 2 MZL).

  Dataset EGAD50000000497

• RNA sequencing from patient-derived intestinal organoids

  uman duodenal tissues for establishing organoid cultures used in this study were sourced from de-identified surgical specimens (n = 3) of the duodenum obtained from patients who had undergone biopsy procedures unrelated to CeD at Tampere University Hospital. The protocol was approved by the Ethics Committee of Tampere University Hospital, Tampere, Finland (ETL code R18082). RNA from the duodenal organoids was isolated using an RNeasy Kit (Qiagen, Hilden, Germany) following the manufacturer’s instructions. RNA purity and concentration were measured using a NanoDrop One spectrophotometer (NanoDrop Technologies, Wilmington, Delaware, USA). Preparation of the RNA library and transcriptome sequencing was conducted by Novogene Co., LTD (Cambridge, UK). Messenger RNA was purified from total RNA using polyA selection and subjected to library construction. Sequencing was performed on an Illumina platform, and 150 bp paired-end reads were generated.

  Dataset EGAD50000000492

• Single nuclei ATAC-Seq data from the human ganglionic eminences

  Data generated through single nuclei ATAC sequencing on whole ganglionic eminences from 3 human fetuses (two of 16 and one of 17 gestational weeks). Tissue was acquired from the MRC-Wellcome Trust Human Developmental Biology Resource with ethical approval. snATAC-Seq libraries were prepared from ~8,000 nuclei per sample using Chromium Next GEM Single Cell ATAC (v1.1) 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 617 million read pairs per library. Raw sequencing data were converted into FASTQ files. For a full description of data generation, please see Cameron et al, Schizophrenia Bulletin 2024, https://doi.org/10.1093/schbul/sbae083. Please note that 10X generated BAM files, rather than FASTQ files, have been uploded. FASTQ files can be regenerated using the 10X Genomics bamtofastq tool. https://support.10xgenomics.com/docs/bamtofastq

  Dataset EGAD50000000601

• Longitudinal single-cell transcriptomic study in patient-derived xenografts of pediatric T-ALL

  In this study, we conducted single cell full length total RNA sequencing (VASA-seq) on 13 matched pediatric T-ALL PDX samples at initial diagnosis and relapse, along with 5 non-relapsing PDX samples collected at initial diagnosis. We identified a subpopulation of T-ALL cells with stem-like cell features that expands substantially at relapse indicating resistance to first-line therapy. Chemotherapy resistance was further validated through functional testing: Two samples were subjected to in-vitro drug testing, treated with Cytarabine for three days, followed by single-cell transcriptomic analysis using 10x Genomics. Additionally, in-vivo drug testing was conducted on one sample, involving re-engraftment into mice and treatment with a combination of Vincristine, Doxorubicin, and Dexamethasone. Single-cell transcriptomic analysis using 10x Genomics was performed after 0, 15 and 30 days of treatment.

  Dataset EGAD50000000831

• 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

• BAM files of total RNA-Seq data of POPS control samples (GRCh37)

  Placental biopsies (n = 64 female placentas, n = 67 male placentas) were selected from healthy pregnancies from the POPs cohort. A quality control process was also applied for the RNA-Seq datasets: reads were trimmed with Trim Galore!, which uses cutadapt internally and were mapped to the same version of human genome reference (hg19). TopHat2, a splice-aware mapper built on top of Bowtie2 short-read aligner, was used in the mapping process in which so-called two-pass (or two-scan) alignment protocol was applied to rescue unmapped reads from the initial mapping step. In the second mapping, previously unmapped reads were re-aligned to the exon-intron junctions detected in the first-mapping by TopHat2 and were combined across all 131 placenta samples. The initial and second mapped reads were merged by samtools

  Dataset EGAD00001003462

• 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

• Whole exome and targeted DNA sequencing data for formalin-fixed paraffin embedded tissue from de novo small cell prostatic carcinoma cases

  This dataset consists of 44 compressed paired fastq files, 15 of which are generated from whole exome sequencing, and 29 of which are generated from DNA sequencing using a targeted gene panel capturing the exonic regions of 73 prostate cancer driver genes. Targeted DNA sequencing was performed on an Illumina MiSeq (v3 600 cycle kit), and exome sequencing was done using an Illumina HiSeq 2500 (v4 250 cycle kit) machine. The fastq files are named in accordance with the sample aliases provided, which reflect the pathology of interest to this study (small cell prostatic carcinoma--SCPC), whether it was sequenced using an exome or targeted gene panel, whether the FFPE sample was sourced from tumor or benign tissue (labeled T or B, respectively), and whether there exists multiple samples belonging to a single patient.

  Dataset EGAD00001004139

• Lung cancer organoids

  Organoids are self-organizing 3D structures grown from stem cells that recapitulate essential aspects of organ structure and function. Here we describe a method to establish long-term culture conditions of human airway epithelial organoids that contain all major cell populations and allow personalized human disease modelling. We collected macroscopically inconspicuous lung tissue from non-small-cell lung cancer (NSCLC) patients undergoing medically indicated surgery and isolated epithelial cells to engineer 3D organoids. We exploit the potential to derive sub-clones from AOs to demonstrate the feasibility of CRISPR gene editing. Finally, we show that AOs readily allow modelling of viral infections such as RSV and for the first time demonstrate the possibility to study neutrophil-epithelium interaction in an organoid model. Taken together, we anticipate that human AOs will find broad applications in the study of adult human airway epithelium in health and disease.

  Dataset EGAD00001004013

• Cancer Genomics of the Kidney

  The aim of CAGEKID is to carry out comprehensive detection of DNA markers for conventional (clear cell) renal carcinoma. The project includes complete analysis of somatic and constitutional DNA variation, methylation patterns and expression in a large number of constitutional/tumor pairs. CAGEKID is a part of the International Cancer Genome Consortium, ICGC.

  Dataset EGAD00001004018

• Exome sequencing of 142 gastric cancer and matched normal from Japanese cohorts (UT)

  As a contribution to the International Cancer Genome Consortium, exome sequencing of 142 Japanese gastric cancer with various histological subtypes have been conducted. This study aims to identify unique and common driver genes and molecular subtypes in Japanese gastric cancer. Please refer ICGC website for detail: http://icgc.org/icgc/cgp/69/420/1012357

  Dataset EGAD00001004041

• Exome sequencing of 102 gastric cancer and matched normal from Japanese cohorts (YCU)

  As a contribution to the International Cancer Genome Consortium, exome sequencing of 102 Japanese gastric cancer with various histological subtypes have been conducted. This study aims to identify unique and common driver genes and molecular subtypes in Japanese gastric cancer. Please refer ICGC website for detail: http://icgc.org/icgc/cgp/69/420/1012357

  Dataset EGAD00001004042

• 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

• A compendium of mutational signatures due to environmental exposures

  Whole-genome-sequencing (WGS) of human tumours has revealed distinct mutation patterns that hint at the causative origins of cancer. We examined mutational-signatures in 324 WGS of human induced pluripotent stem cells (iPSCs) following exposure to known or suspected environmental carcinogens. 79 agents were tested with or without metabolic activation at concentrations that produced measurable cytotoxicity; 41 yielded characteristic substitution mutational signatures. Some exhibit similarity with signatures found in human tumours. Additionally, 6 agents produced double-substitution signatures and 8 produced indel signatures. Investigating mutation asymmetries across genome topography reveals fully functional mismatch and transcription-coupled repair pathways in iPSCs. Primary adducts induced by environmental carcinogens can be resolved by disparate repair/replicative pathways, resulting in an assortment of signature outcomes even for a single mutagen. This compendium of experimentally-induced mutational-signatures permits further exploration of roles of environmental agents in cancer aetiology, and underscores how human stem cell DNA is directly vulnerable to environmental agents.

  Dataset EGAD00001004583

• Next Generation Sequencing in an IBD Pedigree Whole Genome Data

  In 2009 we identified a four-generation family with over 700 members and 41 affected with Crohn's disease (CD). At the time we sequenced the exome of 6 affected individuals but did not identify any coding variants which appear to explain the high prevalence of disease. Since then we have collected DNA from a large number of additional family members, genotyped linkage arrays on the entire family to refine genomic regions shared by identity by descent and genotyped affected and unaffected members at known CD risk loci identified by Genome Wide Association Studies (GWAS). These analyses have confirmed that a significant unexplained excess of disease remains after accounting for all known genetic factors, and that several regions of the genome are shared by a large fraction of affected individuals. We therefore perform whole genomes sequencing from 8 individuals which will allow us to impute the complete sequence of nearly all the members of the two largest and most severely affected branches of the family.

  Dataset EGAD00001000399

• Whole Genome Sequencing of a secondary myelodysplastic syndrome (MDS)

  Illumina HiSeq sequence data (with >30x coverage) were aligned to the hg19 human reference genome assembly using BWA (Li and Durbin, 2009); duplicate reads were removed from the final BAM file. No realignment or recalibration was performed. Sample derived from secondary myelodysplastic syndrome (MDS), arising after treatment for medulloblastoma in an 11-year old female Li-Fraumeni syndrome case (LFS-MB1; Rausch et al., 2012; matching WGS data available under EGAS00001000085).

  Dataset EGAD00001000665

• Comparison of transcriptional response of induced pluripotent stem (iPS) cell-derived and monocyte-derived macrophages to bacterial lipopolysaccharide stimulation

  In the first part of this project, we will differentiate IPS cells from 5 human donors into macrophages, and extract RNA from unstimulated and LPS stimulated macrophages to perform RNA sequencing. We will also extract RNA before and after stimulation in blood- derived macrophages from 5 additional, unrelated healthy samples. In the second part of the project, RNA-seq data will be analysed to compare LPS response of these two macrophage populations. In summary, we will perform 75bp PE RNA-seq on 20 samples (10 pre and post stimulus), on the HiSeq 2500 platform. Samples will be multiplexed at 5 samples / lane, so we will require 4 flow cells in total.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/

  Dataset EGAD00001001106

• Targeted Sequencing of 173 genes

  Targeted sequencing of 173 genes in 2433 primary breast tumours. Data includes 2433 tumour samples, 523 adjacent normal (breast) samples and 127 blood samples. Libraries were prepared with Illumina's Nextera custom enrichment kit targetting all the exons of the most frequently mutated breast cancer genes. Libraries were multiplexed (48 libraries per lane) and sequenced on Illumina HiSeq 2000 (100bp paired-end reads). Somatic mutations were calling with a custom pipeline. We identified 40 mutation-driver (Mut-driver) genes, and determined associations between mutations, driver CNA profiles, clinical-pathological parameters and survival. We assessed the clonal states of Mut-driver mutations, and estimated levels of intra-tumour heterogeneity using mutant-allele fractions. The results emphasize the importance of genome-based stratification of breast cancer, and have important implications for designing therapeutic strategies. Referece: Pereira et al. (2016) The somatic mutation profiles of 2,433 breast cancers refines their genomic and transcriptomic landscapes. Nature Communications

  Dataset EGAD00001002115

• 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