12277 results for ""statistically+reactive"+taxa+in+microbial+community"

in 27.06 milliseconds.

• WES Breast Patient-derived Tumor Organoid

  This dataset includes 18 Whole Exome Sequencing (WES) samples from 5 subjects. WES is performed on a matched pair of case/control samples, e.g., tumor/control or organoid/control. For each patient, the same control sample is used for the analysis of tumor and organoid samples. The sample name structure identifies the type of sample: <subjectId>_[TON][12]_[Case|Ctrl]_EX2; where T, O, and N refer to Tumor tissue, Organoid, and control sample, respectively. The number 1 or 2 refers to the specific tissue, and Case and Ctrl indicate a tumor tissue (or organoid) and a control sample, respectively. For example, ICSBCS007_T1_Case_EX2 is the first tumor tissue of subject ICSBCS007; ICSBCS007_O1_Case_EX2 is the tumor organoid derived from that tumor sample, and ICSBCS007_N1_Ctrl_EX2 is the matching control sample. More information can be found in the sample information table.

  Dataset EGAD50000000961

• Single-Nuclei RNA Sequencing and Spatial Transcriptomics of Human Heart Right Atrial Appendage and Pericardial Fluid in Cardiovascular Disease

  This dataset includes single-nuclei RNA sequencing (snRNA-seq) and spatial transcriptomics data from biopsies of the right atrial appendage and pericardial fluid, collected during open-heart surgeries. The samples represent various clinical contexts, including control, ischemic heart disease, heart failure, and myocardial infarction. For each biopsy, nuclei were isolated, and RNA sequencing libraries were prepared using the 10x Genomics Chromium v3 platform. Additionally, spatial transcriptomics was performed on the heart samples. The dataset provides raw sequencing data, which includes fastq files generated from these libraries, offering valuable insights into the cellular composition of heart tissues and associated fluids across different disease states.

  Dataset EGAD50000000927

• Whole genome sequencing of neuroendocrine tumors of the small intestine

  This dataset contains whole genome sequences for 13 patients with neuroendocrine (unique/multiple) tumor(s) of the small intestine. There are in total 25 tumor and 12 matched normal genomes. Libraries were prepared using a Illumina DNA PCR Free kit following the manufacturer’s recommendations and sequencing was performed on Illumina Novaseq6000 machine with a 2x151bp paired-end fashion. It contains data for : - 1 patient with 4 tumors and 1 matched normal - 1 patient with 3 tumors and 1 matched normal - 1 patient with 2 tumors, 1 liver metastasis and 1 matched normal - 2 patients with 1 tumor, 1 mesenteric nodule and 1 matched normal - 7 patients with 1 tumor and 1 matched normal - 1 patient with 3 tumors and 1 mesenteric nodule

  Dataset EGAD50000000907

• Whole Exome Sequencing of controls performed at the Broad Institute on a cohort from Bristol, UK

  These data were generated as part of a collaboration between University of Bristol, UK and the Stanley Center at the Broad Institute. This project sequenced and analysed the whole exomes of 2969 samples from the Avon Longitudinal Study of Parents and Children (ALSPAC). ALSPAC is a population-based pregnancy cohort with participants acting as ‘controls’ for this project. Genomic DNA from each sample was sequenced to a mean depth of 20x. The exome used Twist capture and samples were sequenced on Illumina NovaSeq 6000 machines producing CRAM files. ALSPAC recruited pregnant women in the Avon County of south-west England between 1991 and 1992. Of the 15,447 pregnancies, 14,901 children were alive at 1 year of age.  DNA was extracted from child blood samples taken between ages 7 and 24.

  Dataset EGAD50000000716

• Targeted Sequencing of 52 Genes for Severe COVID-19

  This dataset comprises targeted sequencing data of 52 genes previously implicated in severe COVID-19 outcomes. The study includes samples from 764 individuals with severe COVID-19 and 3,939 population-based controls from the GCAT cohort (Spain). Molecular Inversion Probes (MIPs) were utilized for cost-effective and precise sequencing of the selected genes. The targeted genes include: Inflammasome/IL-1/TNF Pathway: NLRP3, CASP1, CASP8, IL1B, TNF, RIPK1, RIPK3, MYD88, TNFRSF13B SARS-CoV-2 Entry/Replication: ACE2, TMPRSS2, FURIN, SLC6A20, DDX1, DDX58, TLR4, FYCO1, CTSB, CTSL, ADAM17 Complement System: MBL2, CFH, CFI, CFB, ADAM10, CD46 Interferon Signaling: TLR3, IFIH1, IFITM3, TBK1, TLR7, IL10RB, IFNAR1, IFNAR2, SIGLEC1, MYD88, IFNGR1 Chemokine Receptor Signaling: CCR1, CCR3, CCR2, CCR9, IL8, CXCL3, CXCL10, CXCR6, XCR1, CCL2, CCL20 Immunodeficiency Genes: CASP8, CD46, CFB, CFH, CFI, IFNAR1, IFNAR2, IFNGR1, IFIH1, MYD88, NLRP3, RIPK1, TBK1, TLR3, TLR7

  Dataset EGAD50000001378

• ProstOmics - Spatial Transcriptomics

  Spatial transcriptomics data (ST) from 32 human prostate tissue samples originating from 8 prostate cancer patients (5 patients with post-surgery relapse). The ST data was acquired using the Visium Spatial Gene Expression kit which resulted in over 20 000 spatially defined spots for the 32 tissue samples. The raw transcriptomics data is RNA-seq. The individual samples have information on patient origin and sample type (cancer, cancer-adjacent field-effect normal or normal sample far from cancer). Each ST spot has metadata such as sample origin, histology class (stroma, normal epithelium, cancer of various grading etc), number of cells and estimated cell type fractions. Patient metadata include information of age at surgery, time (months) until reported relapse, total follow-up time, pre-surgery PSA, post-surgery T-stage and metastasis status.

  Dataset EGAD50000000603

• Clonal diversity analysis and inter/intra-organ heterogeneity in urothelial carcinoma under immunotherapy

  We studied a unique autopsy case of metastatic urothelial carcinoma with both sensitivity and resistance to anti-PD-1 therapy. We performed multiregional analyses of 58 paired whole exome sequencing and RNA sequencing samples of 8 different bulk tumor masses, 8 matched whole genome sequencing samples to identify structural abnormalities of each mass. Furthermore, we performed 7 whole exome sequencing from metastatic urothelial carcinoma patients who received anti-PD-1 therapy.

  Study JGAS000725

• Genomic Rearrangements in Pediatric Cancer

  Dataset EGAD00001007701

• Molecular analyses of stage IIIa NSCLC patients treated with neoadjuvant chemmoimmuntherapy

  This dataset comprises molecular and immunogenomic profiles from 60 individual NSCLC patients (30 male, 30 female), with samples collected at multiple timepoints including initial biopsies (IB), resections (RES), and peripheral blood mononuclear cells (PBMC) at different timepoints during treatment. It includes 32 FFPE tumor samples sequenced on Illumina with the FoundationOne panel, 20 FFPE samples sequenced on IonTorrent with the Oncomine Comphrehensive Assay Plus, and 41 samples assessed with IonTorrent via Oncomine Immune Response Research Assay panel for targeted gene expression. T-cell receptor (TCR) repertoire profiling was performed on 62 tumor samples (initial biopsies and resections, Oncomine TCR Beta-SR Assay), and 155 blood-derived samples were sequenced with Oncomine TCR Beta-LR Assay. Data files include processed sequencing results in bam format.

  Dataset EGAD50000001630

• Genomic Signatures of Intestinal Metaplasia in Six Countries with Varying Incidence of Stomach Cancer

  Intestinal metaplasia (IM) is a pre-cancerous condition associated with gastric cancer (GC), a deadly malignancy with varying geographic incidence. Performing a genomic analysis of over 1,500 IM samples from six countries, we identified 46 significantly mutated genes. We observed IM driver genes associated with high-risk populations and worse prognosis (ARID1A), members of the KRAS/MAPK signalling pathway (KRAS, BRAF, MAP2K1, MAP3K1, MAP2K4, NF1), and altered mucosal immunity (PIGR).

  Study EGAS50000001056

• Dataset for study Genome-wide gene expression analysis following CRISPRi of transposable elements

  Transposable elements (TEs), once regarded as parasitic genomic remnants, are now recognized as key regulators of gene expression and genome evolution, yet the functional specificity of individual TE subfamilies remains largely unexplored. This dataset investigates the transcriptional consequences of targeted repression of MER57E3 and LTR10B2 elements using CRISPR interference (CRISPRi) in human induced pluripotent stem cells (hiPSCs). hiPSCs expressing CRISPRi machinery (n = 2 biological replicates) were transduced with guide RNAs targeting individual or grouped copies of MER57E3 and LTR10B2, as well as the ZNF678 promoter or a lacZ non-targeting control. Transduced cells were subsequently differentiated into neural progenitor cells (NPCs), and total RNA was extracted for mRNA library preparation and sequencing. The dataset comprises 24 single-end mRNA-seq FASTQ files generated from these NPCs and wild-type controls.

  Dataset EGAD00001015689

• Bulk and Single-Nuclei RNA-seq with ATAC-seq of Breast Tumors Pre- and Post-Palbo ciclib/Endocrine Therapy

  This dataset comprises bulk and single-nuclei multiomic profiles from patients with ER+/HER2- early breast cancer enrolled in the NeoRHEA phase 2 trial. The bulk RNA-seq component includes 78 pre-treatment and 49 post-treatment tumor samples from 97 patients. The single-nuclei component includes matched pre- and post-treatment samples from 37 patients, totaling 63 samples analyzed by simultaneous snRNA-seq and snATAC-seq. Combined, the data contains bulk transcriptional profiles and single-nuclei gene expression/chromatin accessibility matrices for over 226,000 high-quality nuclei, encompassing tumor, immune, and stromal cells. Technologies used include Illumina NovaSeq 6000 for sequencing and the 10x Genomics Chromium platform (Multiome kit for single-nuclei, standard RNA library prep for bulk).

  Dataset EGAD50000002038

• Cookies

  Cookies https://ega-archive.org does not identify users on this site. It does use cookies, though. What is a cookie? Cookies are text files containing small amounts of information which are downloaded to your device when you visit a website. They allow a website to remember your preferences and are therefore useful to improve your online experience. Find out more information about cookies. Types of cookies we use Functional These cookies record the columns you wish to display or hide in the results page.Performance These cookies are used to analyse trends, administer the website, track visitor movements and gather broad demographic information for aggregate use. We use the information to compile reports and to help us improve our websites. These cookies are not linked to personally identifiable information. Session cookie A session cookie for a website only exists whilst the user is reading or navigating the website. When the user closes their web browser these cookies are usually removed.

  Documentation cookies

• Comprehensive miRNA Sequence Analysis Reveals Survival Differences in Diffuse Large B-cell Lymphoma Patients

  Diffuse large B-cell lymphoma (DLBCL) is an aggressive disease, with 30-40% of patients failing to achieve complete responses to standard therapy. miRNAs are RNA molecules that attenuate expression of their mRNA targets. To characterize the DLBCL miRNome, we sequenced miRNAs from 92 DLBCL and 15 benign centroblast fresh frozen samples and from 140 DLBCL formalin-fixed, paraffin-embedded tissue (FFPET) samples for validation.

  Study EGAS00001001025

• Congenital Heart Disease in UK Families

  This project aims to identify highly penetrant coding variants increasing the risk of Congenital Heart Disease (CHD) performing whole exome sequencing on DNA samples from 23 affected individuals, selected from 10 families with presumed Autosomal Recessive Inheritance. This is a collaboration with Prof. Eamonn Maher and Dr. Chirag Patel from the Department of Medical and Molecular Genetics, University of Birmingham plans to sequence 23 indexed Agilent whole exome pulldown libraries on 75Bp PE HiSeq (Illumina).

  Study EGAS00001000066

• Genome-wide genotyping data and exome sequencing of 100 European-descent and 100 African-descent Belgians used in the EGAS00001001895 study

  We recruited 100 healthy, male donors of self-reported European descent (EUB) and 100 of self-reported African descent (AFB) (Ghent, Belgium). For each participant, peripheral blood mononuclear cells (PBMCs) were isolated from whole blood on Ficoll-Paque density gradients. Monocytes were then positively selected with magnetic CD14 microbeads and exposed for 6 hours to different ligands activating TLR4 (LPS), TLR1/2 (Pam3CSK4), TLR7/8 (R848) and to a human seasonal influenza A virus (IAV). High-quality RNA was obtained from unstimulated and stimulated monocytes for 970 of the 1000 samples (200 x 5 conditions), and was sequenced on an Illumina HiSeq2000. On average, 34 million 101-bp single-end reads were obtained per sample.

  Dataset EGAD00001002714

• NGS data of human NES cells and tumors

  Raw RNA-seq data for WT and 2 Gorlin NES cells, tumors derived from MYCN mis-expressed WT NES cells, tumors derived from Gorlin NES cells, and tumors derived from Gorlin NES cells transduced with mutant DDX3X (R351W and R534S) and CRISPR/Cas9 targeting GSE1 (each sample has 3 replicates/tumors except Gorlin NES cell tumors have 4). Raw whole exome sequencing data for WT and Gorlin 1 NES cells, tumors derived from MYCN mis-expressed WT NES cells, and tumors derived from Gorlin NES cells (each sample has 3 replicates/tumors except Gorlin NES cell tumors have 4). Raw data for amplicon sequencing of GSE1 and KDM3B at regions targeted by CRISPR/Cas9 in Gorlin NES cells.

  Dataset EGAD00001004990

• RNA-seq study of longitudinal blood cell samples drawn from children at risk of type 1 diabetes

  The appearance of type 1 diabetes (T1D)-associated autoantibodies is the first and only measurable parameter to predict progression toward T1D in genetically susceptible individuals. However, autoantibodies indicate an active autoimmune reaction, wherein the immune tolerance is already broken. Therefore, there is a clear and urgent need for new biomarkers that predict the onset of the autoimmune reaction preceding auto-antibody positivity or reflect progressive b-cell destruction. Here we report the mRNA sequencing-based analysis of 306 samples including fractionated samples of CD4+ and CD8+ T cells as well as CD4, CD8 cell fractions and unfractionated PBMC samples longitudinally collected from seven children who developed beta-cell autoimmunity (case subjects) at a young age and matched control subjects.

  Dataset EGAD00001005767

• Exome sequences of AL amyloidosis (ALA), multiple myeloma (MM) and ALA+MM hematological malignancies

  DNA was isolated from aberrant plasma cells (aPCs) and peripheral blood of 12 ALA, 10 ALA+MM and 29 MM individuals. DNA from aPCs was amplified using REPLI-g Mini Kit (Qiagen). Totally, we analyzed 51 patients, 102 samples. One batch of exome libraries (paired tumor-normal samples from 12 ALA, 10 ALA+MM and 6 MM) was prepared using SureSelect Human All Exon V5 Kit (Agilent Technologies) and sequenced on Illumina HiSeq 4000 platform, 100 cycles. Second batch (23 MM samples; IDs ARK01-ARK26) was prepared using SureSelect Human All Exon V5 + IGH, IGK, IGL, MYC (Agilent Technologies) library preparation kit and sequenced on Illumina HiSeq 2000 platform in paired-end settings, 75 cycles. The reads were mapped using BWA-MEM on human genome GRCh38 without alternate loci.

  Dataset EGAD00001006047

• UMCU_Molpheno_Restricted

  This dataset contains Whole Genome Sequencing and, if available, RNA-sequencing and/or ATAC-sequencing data obtained from PBMCs derived from blood samples of 34 patients with intellectual disability and/or multiple congenital anomalies and their biological parents (58) included in the University Medical Center Utrecht (The Netherlands).

  Dataset EGAD00001004865

• Induction of trained immunity by influenza vaccine: impact on COVID-19

  Cryopreserved PBMCs from 10 individuals before and after vaccination were used to perform single cell RNA sequencing. Equal number of cells per individual were pooled together (5 individuals per pool) and single-cell RNA sequencing was performed in paired-end mode on NovaSeq 6000 (Illumina) with a depth of 50,000 reads per cell. DNA was isolated from PBMCs and then used for genotyping by Illumina GSA Beadchip. This dataset contains the fastq sequence files, genotypes of the donors used for demultiplexing the pools and files indicating the linkages between individuals, pools and fastq files. The number of samples listed by EGA does not match the actual number of samples due to limitations on the upload scheme used.

  Dataset EGAD00001007827

• Timing chromosomal amplification events using patterns of somatic mutations in high hyperdiploid acute lymphoblastic leukemia

  This dataset included 19 paired diagnostic and remission samples with high hyperdiploid acute lymphoblastic leukemia (ALL) that were collected from four different cohorts: the Division of Clinical Genetics, Lund University, Sweden. All samples were subjected to whole genome sequencing using the Illumina HiSeqX platform. Paired-end sequencing (2x150bp) was done to ~60x coverage for diagnostic samples and ~30x coverage for remission samples. The paired-end reads were aligned to the human reference genome GRCh37 (ftp://ftp.ncbi.nlm.nih.gov/genomes/refseq/vertebrate_mammalian/Homo_sapiens/all_assembly_versions/GCF_000001405.25_GRCh37.p13/GCF_000001405.25_GRCh37.p13_genomic.fna.gz) by the Burrows-Wheeler Aligner tool (version 0.7.17). Duplicate reads marking and local realignment were performed by GATK (version 4.0.11.0).

  Dataset EGAD00001010103

• SPECIAL: scRNA-seq

  Tumour biopsies were collected from twenty-three patients (46 samples) (of which 20 were matched) with locally advanced or metastatic melanoma (stage IIIB – stage IV). Library construction was done either with the Chromium Single Cell 3ʹ GEM, Library &amp; Gel Bead Kit v3 (n = 16; 10x genomics, Cat#1000092) or the Chromium Single Cell A Chip Kit and 5’ Library &amp; Gel Bead Kit (10x genomics, Cat#1000014). All libraries were sequenced on Illumina NextSeq, HiSeq4000 or NovaSeq6000 until sufficient saturation was reached (60% on average). The reference genome used in this study was GRCh38.

  Dataset EGAD00001009291

• Whole exome sequencing study of cholesteatoma patients from affected families

  This study used whole exome sequencing on 21 patients with cholesteatoma from 10 families in order to identify variants that may attribute to cholesteatoma aetiology. Exomes were enriched for using hybridisation selection and subject to DNA-sequencing. This datasets is formed of two batches as they were sequencing at different times. Batch-1 exomes were selected for using Nimblegen capture (4-plex) and sequenced on Illumina Hiseq 4000 and batch-2 was exome selected using Agilent SureSelect Human All Exon v6 and sequenced on the Illumina NovaSeq 6000. All samples within the same family were processed within the same batch. This dataset is comprised on BAM files mapped using cgpMAP v3.2.0 (bwa-mem) using the GRCh38.

  Dataset EGAD00001008671

• RNAseq data

  RNAseq FASTq files from 797 tumors from AVANT. Sequencing libraries were generated with the TruSeq Stranded Total RNA kit (Illumina) following ribosomal RNA (rRNA) depletion with the Ribo-Zero Gold kit (Illumina). The libraries were sequenced on the HiSeq4000 (Illumina) with a sequencing protocol of 75 bp paired-end sequencing. Note: 10 samples used in the original publication were excluded from this upload due to regulations from the Human Genetics Resources Administration of China (HGRAC).

  Dataset EGAD00001009728

• Dataset for bone_cancer-RNA

  Rare cancer sequencing data of 55 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008848

• Dataset for GIST-RNA

  Rare cancer sequencing data of 50 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008852

• Dataset for breast_cancer-RNA

  Rare cancer sequencing data of 59 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008850

• Clonal origin of lineage switch leukemia following CAR-T cell and blinatumomab therapy

  Children with ALL treated with anti-CD19 therapy occasionally develop a phenotypically distinct AML. However, the precise clonal origin of such class switch leukemias remains unresolved. Here, we reconstructed the evolution of leukemia in a child with primary ALL, two ALL relapses and AML after treatment with anti-CD19 CAR-T and blinatumomab through whole-genome sequencing. The phylogeny revealed that the AML was a monoclonal outgrowth descending from the initial ALL and harbored biallelic loss of CDKN2A, PAX5 and TP53. However, none of the ALL or AML relapses directly descended from one another, suggesting the presence of a reservoir of persistent clones. Our findings suggest anti-CD19 treatment selects pre-existing clones, with many key genetic alterations underpinning the lineage switch detectable prior to treatment.

  Dataset EGAD00001009161

• Bulk-tissue RNA-sequencing paired nuclear and cytoplasmic fractions of anterior prefrontal cortex, cerebellar cortex and putamen tissues from 4 post-mortem neuropathologically-confirmed control individuals ( anterior prefrontal cortex &amp; cerebellar cortex – 4 individuals, putamen- 3 individuals)

  Profiling of paired nuclear and cytoplasmic fractions of anterior prefrontal cortex, cerebellar cortex and putamen samples by bulk-tissue RNA-sequencing. Samples were derived from 4 post-mortem neuropathologically-confirmed control individuals ( anterior prefrontal cortex – 4 individuals, cerebellar cortex – 4 individuals, putamen- 3 individuals). Paired-end FASTQ files for each of the human samples are provided. Fastp (v 0.20.0), a fast all-in-one FASTQ pre-processor, was used for adapter trimming, read filtering and base correction. Fastp default settings were used for quality filtering and base correction. Further details on parameters used are available here: https://github.com/RHReynolds/RNAseqProcessing .

  Dataset EGAD00001009264

• Separation of chronic myeloid leukemia stem cells from normal hematopoietic stem cells at single-cell resolution

  We provide whole exome DNA sequening data in fastq format for 23 clinical samples of chronic myeloid leukemia stem cells (CML-SC) plus two buccal swipes derived normal samples. CML samples are comprised of 4 to 8 replicates from two patients, at diagnosis and after treatment. Single CML stem cells before treatment and single non-transformed hematopoietic stem cells (HSC) at remission were selected from bone marrow samples by FACS, according to newly identified genetic markers CD33+CD26+ at diagnosis and CD33+CD26-/CD33-CD26- at remission. WES libraries of colony forming assays derived CML-SC and HSC populations were prepared using Agilent SureSelect Human All Exon V6 kit and sequenced running 150 cycles (2x 75bp paired-end) on an Illumina NextSeq 500 platform.

  Dataset EGAD00001009847

• Paired WES and low coverage WGS of osteosarcoma

  Longitudinal genome-sequencing analysis of 12 patients with metastatic or refractory osteosarcoma. The study was approved at the University Hospital Basel, following the approval of the ethical committee for mutational analysis of anonymized samples (“Ethikkommission beider Basel” ref. 274/12). Informed consent was obtained from all 12 patients. All tumor samples were evaluated by an experienced bone pathologist to confirm the diagnosis. WES and low coverage WGS are aligned against the reference genome GRCh37. More details in the associated publication.

  Dataset EGAD00001007509

• Dataset for other_cancer-EXON

  Rare cancer sequencing data of 137 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008896

• Dataset for neuroendocrine_adrenal_tumor-EXON

  Rare cancer sequencing data of 164 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008891

• Total RNA sequencing of 32 chronic lymphocytic leukemia (CLL) patients

  Peripheral blood mononuclear cells (PBMC) of CLL patients were isolated by density-gradient centrifugation over Linfosep (Biomedics, Madrid, Spain). B cells were purified with a CD19+ magnetic-bead system (MidiMACS, Miltenyi Biotec, Bergish Gladbash, Germany) according to the manufacturers’ instructions. Mean B-cell purity was &gt;99% and the mean percentage of CD5+/CD19+ cells after purification was &gt;98%, as measured by flow cytometry. Total RNA was extracted from purified cells in a single step using TriPure Isolation Reagent (Roche Applied Science, Vilvoorde, Belgium).Whole transcriptome sequencing libraries were prepared using the TruSeq Stranded Total RNA Sample Preparation Kit (Illumina). Libraries underwent 2 × 76 bp paired-end sequencing on a HiSeq 2500 instrument (Illumina). The median number of paired-end reads was 60.5 million (range, 49.7-79.7 million).

  Dataset EGAD00001004047

• RNA-seq of human iPSC-derived neurons to explore cellular phenotypes associated with schizophrenia.

  This dataset contains high-throughput RNA-sequencing of 12 samples, each sample comprising neural precursor cells derived from human induced pluripotent stem cells from individuals with and without the 16p13.11 microduplication (a copy number variant associated with a range of neurodevelopmental disorders). 4 samples derive from patients carrying the 16p13.11 microduplication, and 8 derive from unaffected family controls. RNA samples were processed to deplete rRNA using the TruSeq Stranded Total RNA with Ribo-Gold kit. Libraries were then sequenced using the NextSeq 500/550 High-Output v2 Kit on the Illumina NextSeq 550 platform, to produce 75 base pair paired-end sequencing reads at an average depth of around 100 million reads per sample. Raw sequencing reads data are stored in two FASTQ files per sample for these paired-end reads.

  Dataset EGAD00001004064

• Miseq (18S) analysis of spiked placental tissue samples

  We spiked a small number of placental tissue samples with different combinations of Candida albicans, Plasmodium falciparum, Toxoplasma gondii, Human Cytolomega virus and Salmonella bongori (various combination of the equivalents of 1, 10, 100, 1000 and 10000 genome copies). A DNA isolation was performed on these spiked samples and the resulting DNA was subsequently sequenced by MiSeq (18S). These same samples were also analysed by X Ten to allow for a sensitivity comparison of the two methods of the eukaryotic spiked signals (Candida albicans, Plasmodium falciparum and Toxoplasma gondii). In addition, non-spiked placental samples from 50 cases of Fetal Growth Restriction (FGR) (+ matched healthy controls) and 49 cases of Preeclampsia (+ matched healthy controls) and 100 preterm cases were analyzed for their non-human eukaryotic content.

  Dataset EGAD00001004197

• GWAS on covid-19 severity and susceptibility in the province of Bergamo, Italy

  This is a case-control GWAS that involved the voluntary recruitment of inhabitants of the Bergamo province via an online questionnaire. We collected detailed clinical data and verified all information through personal interviews. Cases (severe COVID-19; G1) and controls (mild or asymptomatic COVID-19, G2; non-infected, G3) were matched by age, sex and risk factors

  Study EGAS00001007310

• Primary Prostate Tumor Tissue DNA Methylation Profiles

  The study cohort includes 525 Caucasian and African American prostate cancer (PCa) patients who underwent radical prostatectomy (RP) as primary therapy for clinically localized adenocarcinoma of the prostate. These patients were previously enrolled in one of two population-based studies: 1) men 40-64 years of age, diagnosed between January 1993 and December 1996; and, 2) men 35-74 years of age, diagnosed between January 2002 and December 2005. Gleason grade and sum, diagnostic PSA, and pathological tumor stage were obtained from the SEER cancer registry. Formalin-fixed paraffin-embedded prostate tumor tissue blocks were obtained from RP specimens and used to make hematoxalin and eosin stained slides, which were reviewed by pathologists to confirm the presence/location of adenocarcinoma. For each patient two 1-mm tumor tissue cores from the dominant lesion that were enriched with &#62;&#61;75% tumor cells were taken for DNA purification. The RecoverAll Total Nucleic Acid Isolation Kit (Ambion/Applied Biosciences, Austin, TX) was used to extract DNA, which was then quantified (PicoGreen), aliquoted onto 96-well plates and shipped to Illumina for DNA methylation profiling using the Infinium&#174; HumanMethylation450 BeadChip.

  Study phs001921

• Circulating RNA profiles of healthy and preeclamptic pregnancies

  This prospective study investigated whether circulating RNA (C-RNA; cell free RNA present in the bloodstream) measurements could non-invasively monitor pregnancy status, with emphasis on detecting molecular markers associated with preterm preeclampsia. Whole blood samples were collected from pregnant women at the time of diagnosis with early-onset preeclampsia with severe features. Blood samples were also obtained normotypical control pregnancies and from patients diagnosed with late-onset preeclampsia for comparison. For all samples, C-RNA was extracted from 4 mL blood and whole transcriptome enrichment performed on cDNA libraries prior to sequencing to a target depth of 50M reads on an Illumina HiSeq 2000 platform. Throughout the course of this work, whole transcriptome RNA sequencing data was obtained from 289 C-RNA samples collected from 178 subjects. The complete dataset consists of samples from the following cohorts: Illumina Preeclampsia Cohort (iPEC): 40 pregnancies at the time of early-onset preeclampsia diagnosis and 73 gestational age-matched controls PEARL preeclampsia cohort: 12 early-onset and 12 late-onset preeclampsia patients PEARL healthy control cohort: 152 longitundinal samples collected from 41 healthy pregnancies

  Study phs002017

• E5103 Correlative Studies

  ECOG-ACRIN E5103 (E5103) was a phase III adjuvant breast cancer trial that randomized 4994 patients with node-positive or high-risk node-negative breast cancer to intravenous doxorubicin and cyclophosphamide every 2 or 3 weeks (at the discretion of treating physician), for four cycles of adriamycin and cyclophosphamide (AC) followed by 12 weeks of weekly paclitaxel (80 mg/m2) alone (Arm A), or to the same chemotherapy with either concurrent bevacizumab (Arm B), or concurrent plus sequential bevacizumab (Arm C). To develop predictive genetic biomarkers for chemotherapy efficacy and toxicities, we have successfully performed genome-wide genotyping and whole exome sequencing in the germline (blood) DNA of 3215 and 672 patients, respectively, from the E5103 trial to investigate the association of genetic variants with chemotherapy efficacy and toxicities. Case and control studies were performed with genome-wide analyses (GWAS) and whole exome analyses (WES) across all arms of E5103 to identify genotypes at single-nucleotide polymorphisms (SNPs) and deleterious gene mutations that were associated with paclitaxel-induced peripheral neuropathy (TIPN). Through GWAS, we have identified a SNP, rs3125923, and through WES, Cytochrome P450 oxidoreductase (POR), that was significantly associated with grade 3-4 TIPN.

  Study phs003201

• The taxonomic composition of the human microbiome of CRC patients and healthy donors

  In this study, single homogenized human stool samples from five healthy donors and one CRC patient were analyzed by shotgun sequencing to generate a baseline for the establishment of humanized microbiome to be transferred into mice. Briefly, fecal DNA was isolated from these samples using the DNeasy PowerSoil DNA Isolation Kit (Qiagen), according to the kit manual, except that samples were homogenized using the TissueLyzerII for five minutes at 40Hz instead of intense vortexing. The extracted DNA was further purified and concentrated using the DNA Clean and Concentrator Kit (Zymo Research). This DNA was thawed and refrozen once at -80°C for 16s sequencing before being thawed again for WGS. 200 ng of DNA was used for metagenomic library preparation using the Next Generation Sequencing DNA Library Prep Kit (Westburg), according to the user manual using an average insert size of libraries of 450 base pairs. Following quantification and quality control (Qubit® dsDNA BR Assay Kit (Thermofisher Scientific); Bioanalyzer High Sensitivity DNA Analysis Kit (Agilent Technologies)), sequencing was performed on a NextSeq500 instrument using 2×150 base pair read lengths.

  Study EGAS50000000759

• Leukemia Relapse via Genetic Immune Escape after Allogeneic Hematopoietic Cell Transplantation

  Graft-versus-leukemia (GvL) reactions are responsible for the effectiveness of allogeneic hematopoietic cell transplantation as a treatment modality for myeloid neoplasia, whereby donor T- effector cells recognize leukemia neoantigens. However, a substantial fraction of patients experience relapses because of the failure of the immunological responses to control leukemic outgrowth. Here we demonstrate, through a broad immunogenetic study, that germline and somatic reduction of human leucocyte antigen (HLA) heterogeneity enhances the risk of leukemic recurrence. We show that preexistent germline-encoded low evolutionary divergence of class II HLA genotypes constitutes an independent factor associated with disease relapse and that acquisition of clonal somatic defects in HLA alleles may lead to escape from GvL control. Both class I and II HLA genes are targeted by somatic mutations as clonal selection factors potentially impairing cellular immune responses and responses to immunomodulatory strategies. These findings define new molecular modes of post-transplant leukemia escape contributing to relapse.The present dataset provides HLA peripheral blood and bone marrow samples supporting the genotyping studies performed for this research. This sample set originates from patients with acute myeloid leukemia or myelodysplastic syndromes receiving allogeneic hematopoietic cell transplantation and relapsing after transplant.

  Study phs003235

• Whole exome sequencing of bladder tumors

  Bladder carcinomas are immunogenic, and patients with bladder cancer benefit from immune checkpoint therapy. This is correlated to a high tumor mutation burden, which provides a higher number of neoepitopes that can be recognized by tumor-specific CD8+ T cells. Intravesical Bacillus Calmette-Guérin (BCG) is used to treat non-muscle invasive bladder cancer (NMIBC), but its mechanism of action remains elusive. Most lymphocytes appearing in the urine of BCG-treated patients are CD4+ T cells though preclinical studies showed that CD8+ T cells are also necessary for BCG treatment efficacy. It is currently unknown which proportion of patients with non-metastatic bladder cancer develop a spontaneous antitumor CD8+ response, and if BCG treatment influences this response. were prepared using the xGen Dual Index UMI Adapters (IDT), and genomic DNA (gDNA) extracted (DNeasy kit, Qiagen) from formalin-fixed paraffin- embedded (FFPE) or snap-frozen tumor tissue, as well as autologous lymphocytes. Libraries were subjected to paired-end sequencing using Illumina HiSeq4000 with a coverage depth of 250X. Library preparation was carried out with the AllType FASTplex NGS 11 Loci Flex Kit (One Lambda), and sequencing was conducted on the Illumina MiSeq platform.

  Study EGAS50000001248

• SmMIP-tools:a computational toolset for processing and analysis of single-molecule molecular inversion probes derived data

  Single-molecule molecular inversion probes (smMIPs) provides a modular and cost-effective platform for high-multiplex targeted next-generation sequencing (NGS). Nevertheless, translating the raw smMIP-derived sequencing data into accurate and meaningful information currently requires proficient computational skills and a large amount of computational work, prohibiting wide-scale adoption of smMIP-based technologies. To enable easy, efficient, and accurate interrogation of smMIP-derived data, we developed SmMIP-tools, a computational toolset that combines the critical analytic steps for smMIP data interpretation into a single computational pipeline. Here, we describe in detail two major components of the software. The first is a read processing tool that performs quality control steps, generates read-smMIP linkages and retrieves molecular tags. The second is an error-aware variant caller capable of detecting single nucleotide variants (SNVs) and short insertions and deletions (indels). Using a cell-line DNA dilution series and a cohort of blood cancer patients, we benchmarked SmMIP-tools and evaluated its performance against clinical sequencing reports. We anticipate that SmMIP-tools will increase accessibility to smMIP-technology, enabling cost-effective genetic research to push personalized medicine forward.

  Study EGAS00001005359

• Hominin-specific NOTCH2 paralogs expand human cortical neurogenesis through regulation of Delta/Notch interactions.

  The human cerebral cortex has undergone rapid expansion and increased complexity during recent evolution. Hominid-specific gene duplications represent a major driving force of evolution, but their impact on human brain evolution remains unclear. Using tailored RNA sequencing (RNAseq), we profiled the spatial and temporal expression of Hominid-specific duplicated (HS) genes in the human fetal cortex, leading to the identification of a repertoire of 36 HS genes displaying robust and dynamic patterns during cortical neurogenesis. Among these we focused on NOTCH2NL, previously uncharacterized HS paralogs of NOTCH2. NOTCH2NL promote the clonal expansion of human cortical progenitors by increasing self-renewal, ultimately leading to higher neuronal output. NOTCH2NL function by activating the Notch pathway, through inhibition of Delta/Notch interactions. Our study uncovers a large repertoire of recently evolved genes linking genomic evolution to human brain development, and reveals how hominin-specific NOTCH paralogs may have contributed to the expansion of the human cortex. The dataset contains raw sequences (FASTQ files) from the Illumina 2x150bp paired-end RNA sequencing profiles of 11 fetal human brain samples at 7, 9, 12, 15 and 21 gestational weeks.

  Study EGAS00001002798

• UAMS Smoldering Myeloma Myeloma Sequencing

  Identifying high risk smoldering myeloma patients and progression mechanism is a prerequisite to implement effective inception strategies and curve myeloma related morbidity and mortality. We hypothesize that genomics may help identify determinants of progression that may help predict outcome and offer effective chemo preventive targets. Eighty-two patients underwent a custom targeted panel sequencing with an additional capture for the translocation loci. These results were compared to 223 newly diagnosed patients (EGAS00001003223 and EGAD00001004117) and 17 MGUS and 10 early myeloma patients. DNA was obtained from either CD138+ cells from the bone marrow of multiple myeloma patients (tumor) or from stem cell harvests or peripheral blood cells from the same patient (control). 100 ng of DNA was fragmented, end-repaired, and adapters ligated using the HyperPlus kit (KAPA Biosystems). After PCR amplification the libraries were hybridized with probes against either a targeted panel consisting of 140 genes and chromosomal regions (Nimblegen) using SeqCap reagents (Nimblegen). Hybridized libraries underwent further amplification before being sequenced on a NextSeq500 (Illumina) using 75 bp paired end reads. Overall, these data highlight the importance of dysregulation of the MAPK pathway in the progression to MM.

  Study EGAS00001003629

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: Oesophageal adenocarcinoma

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute (40X and 20X depth respectively). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development. This dataset contains all the data available for this study on 2021-09-27.

  Dataset EGAD00001006083

• RNA-seq of high grade serous ovarian tumours

  Somatic RNA for 40 samples matched to the WGS was extracted using the Qiagen Qiasymphony RNA protcol (cat no 931636). The tissue was initially homogenised using a Qiagen Bioruptor, followed by the manufacturers recommended protocol (including DNase digestion). The resulting RNA the underwent quality control as follows: firstly, A260 and A280nm were measured on a Denovix DS-11 Fx to qualitatively illustrate A260/280nm and A260/230nm ratios as measures of RNA purity. A260/280 had to be 2.0 and A260/230 had to be 2.0-2.2. Then RNA was quantified using LifeTechnologies Qubit RNA BR kit (cat no Q10210). RNAseq was carried out by the Edinburgh Clinical Research Facility on an Illumina NExtSeq500. Total RNA samples were assessed on the Agilent Bioanalyser (Agilent Technologies, #G2939AA) with the RNA 6000 Nano Kit (#5067-1512) for quality and integrity of total RNA, and then quantified using the Qubit 2.0 Fluorometer (Thermo Fisher Scientific Inc, #Q32866) and the Qubit RNA HS assay kit (#Q32855). Libraries were prepared from total-RNA sample using the NEBNext Ultra 2 Directional RNA library prep kit for Illumina (#E7760S) with the NEBNext rRNA Depletion kit (#E6310) according to the provided protocol. 400ng of totalRNA was then added to the ribosomal RNA (rRNA) depletion reaction using the NEBNext rRNA depletion kit (Human/mouse/rat) (#E6310). This step uses specific probes that bind to the rRNA in order to cleave it. rRNA-depleted RNA was then DNase treated and purified using Agencourt RNAClean XP beads (Beckman Coulter Inc, #66514). RNA was then fragmented using random primers before undergoing first strand and second strand synthesis to create cDNA. cDNA was end repaired before ligation of sequencing adapters, and libraries were enriched by PCR using the NEBNext Multiplex oligos for Illumina set 1 and 2 (#E7500). Final libraries had an average peak size of 271bp. Libraries were quantified by fluorometry using the Qubit dsDNA HS assay and assessed for quality and fragment size using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Sequencing was performed using the NextSeq 500/550 High-Output v2 (150 cycle) Kit (# FC- 404-2002) on the NextSeq 550 platform (Illumina Inc, #SY-415-1002). Libraries were combined in an equimolar pool based on the library quantification results and run across 5 High-Output Flow Cell v2.5.

  Dataset EGAD00001009048

• RNA-seq of high grade serous ovarian tumours

  Somatic RNA for 37 samples was extracted using the Qiagen Qiasymphony RNA protcol (cat no 931636). The tissue was initially homogenised using a Qiagen Bioruptor, followed by the manufacturers recommended protocol (including DNase digestion). The resulting RNA the underwent quality control as follows: firstly, A260 and A280nm were measured on a Denovix DS-11 Fx to qualitatively illustrate A260/280nm and A260/230nm ratios as measures of RNA purity. A260/280 had to be 2.0 and A260/230 had to be 2.0-2.2. Then RNA was quantified using LifeTechnologies Qubit RNA BR kit (cat no Q10210). RNAseq was carried out by the Edinburgh Clinical Research Facility on an Illumina NExtSeq500. Total RNA samples were assessed on the Agilent Bioanalyser (Agilent Technologies, #G2939AA) with the RNA 6000 Nano Kit (#5067-1512) for quality and integrity of total RNA, and then quantified using the Qubit 2.0 Fluorometer (Thermo Fisher Scientific Inc, #Q32866) and the Qubit RNA HS assay kit (#Q32855). Libraries were prepared from total-RNA sample using the NEBNext Ultra 2 Directional RNA library prep kit for Illumina (#E7760S) with the NEBNext rRNA Depletion kit (#E6310) according to the provided protocol. 400ng of totalRNA was then added to the ribosomal RNA (rRNA) depletion reaction using the NEBNext rRNA depletion kit (Human/mouse/rat) (#E6310). This step uses specific probes that bind to the rRNA in order to cleave it. rRNA-depleted RNA was then DNase treated and purified using Agencourt RNAClean XP beads (Beckman Coulter Inc, #66514). RNA was then fragmented using random primers before undergoing first strand and second strand synthesis to create cDNA. cDNA was end repaired before ligation of sequencing adapters, and libraries were enriched by PCR using the NEBNext Multiplex oligos for Illumina set 1 and 2 (#E7500). Final libraries had an average peak size of 271bp. Libraries were quantified by fluorometry using the Qubit dsDNA HS assay and assessed for quality and fragment size using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Sequencing was performed using the NextSeq 500/550 High-Output v2 (150 cycle) Kit (# FC- 404-2002) on the NextSeq 550 platform (Illumina Inc, #SY-415-1002). Libraries were combined in an equimolar pool based on the library quantification results and run across 5 High-Output Flow Cell v2.5.

  Dataset EGAD00001010139