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• Exome sequencing of 3 blood samples from tall man and his parents

  Exome sequencing was carried out in a tall male (height 3.5 SDS) and his parents (3 samples). The data was sequences on a Illumina Hiseq2000 and the library was prepared with Agilent SureSelect V4.

  Dataset EGAD00001007767

• Single cell Transcriptome Analysis of regulatory Tcells from blood, fat and skin

  Regulatory Tcells were FACS sorted and processed with 10x Genomics Chromium Next GEM Single Cell 5' v2 sequencing. In total 17 samples were processed. Fastq files are supplied.

  Dataset EGAD00001007665

• RNA-seq dataset

  HTG EdgeSeq fastq files of bulk baseline tumors from IMbassdor250: a randomised phase 3 trial comparing atezolizumab with enzalutamide vs enzalutamide alone in patients with metastatic castration-resistant prostate cancer.

  Dataset EGAD00001007685

• Spatial transcriptome sequence data from prostate cancer needle biopsies

  Spatial transcriptome sequencing data from prostate cancer needle biopsies. Dataset contains biopsies from before and after androgen deprivation therapy of 3 patients with 8 biopsies per patient in total. 2 sections (replicates) are taken from each biopsy.

  Dataset EGAD00001008636

• miRNA and mRNA transcriptome data

  This dataset contains 278 miRNA and 20 mRNA transcriptomes generated as part of the study "miR-374a-5p regulates inflammatory genes and monocyte function in inflammatory bowel disease."

  Dataset EGAD00001008683

• SmartSeq2 index cultures

  SmartSeq2 read out of index cultured cell sorted with the classification and erythroid-myeloid panel developed in main Figure 6.

  Dataset EGAD00001008187

• Pediatric high grade glioma RNA-Seq

  We performed RNA-Seq in DIPG and hemispheric HGG.

  Dataset EGAD00001008278

• Whole-exome sequencing of IMFT tumor samples f

  Whole-exome sequencing of IMFT tumor samples from 24 participants in the clinical phase II trial EORTC 90101 “CREATE” (CREATE IMFT cohort)

  Dataset EGAD00001007803

• snRNA-seq/snATAC-seq multiome of first and second trimester human gonads - HUGODECA dataset

  Comprehensive map of first- and second-trimester gonadal development in humans using a combination of single-cell and spatial transcriptomics, chromatin accessibility assays, and imaging. ArrayExpress Accession: E-MTAB-11708

  Dataset EGAD00001009388

• Novel Approach to High-Throughput Identification and Characterization of Neoantigens

  This study focuses on the development of novel approach for the screening, identification and characterization of neoantigen-specific T-cell receptors (TCRs). The developed method consists of collecting targeted RNA-Seq from a T-cell specific gene panel via 3' end Illumina sequencing combined to Oxford Nanopore based full-length TCR sequencing post T-cell activation. The data generated during this study demonstrates feasibility of the approach on a Jurkat control cell line as well as T-cells isolated from the blood of 3 independent healthy donors.

  Study phs002372

• Transcriptional effect of 4HTBZ on Caco-2 cells

  This study was performed to investigate the transcriptional effect of the H2S donor 4HTBZ on intestinal epithelial cells upon inflammatory stimulation. Caco-2/TC7 cells were pre-stimulated with interferon gamma (IFNG, 2.5 ng/mL) and tumor necrosis factor alpha (TNF, 10 ng/mL), followed by treatment with 4HTBZ (50 µM) or vehicle (0.1% DMSO) for 72 hours. Total RNA was extracted using the RNeasy Mini Kit (Qiagen, Hilden, Germany), and cDNA libraries were prepared with the QuantSeq 3′ mRNA-Seq Kit (Lexogen, Inc.) and sequenced on an Illumina HiSeq4000 system.

  Study EGAS50000001237

• Prime-seq of human term placenta-derived trophoblast organoids

  To study the one of the mechanisms through which obesity could affect placental cells, we used a novel microfluidic organs-on-a-chip device fabricated for co-culturing adipose spheroids and trophoblast organoids. The organoids were derived from the term placenta of a over-weight women. The adipose spheorids were derived from the white adipose tissue of a woman. And we sequenced the RNAs from the trophoblast organoids. The RNA extracted were subjective to Prime-seq library preparation protocol and being sequenced on Illumina NovaSeq 6000 at Novogene.

  Study EGAS50000000833

• Targeted exome sequencing of pleomorphic invasive lobular carcinoma (PILC).

  Pleomorphic invasive lobular carcinoma (PILC) is an aggressive variant of invasive lobular breast cancer that is associated with poor clinical outcomes. Limited molecular data are available to explain the mechanistic basis for PILC behavior. To address this issue, we performed targeted sequencing using the Beijing Genomics Institute (BGI) TumorCare™ gene panel that includes 1053 genes that were selected based upon their association with cancer. This sequencing analysis identified genes that distinguish PILC from classic ILC (CILC) and invasive ductal carcinoma (IDC) by the incidence of their genomic changes.

  Study EGAS00001002871

• Single-cell RNA sequencing on 5063 single T cells isolated from peripheral blood, tumour and adjacent normal tissues from six hepatocellular carcinoma patients.

  Single-cell RNA sequencing on 5063 single T cells isolated from peripheral blood, tumour and adjacent normal tissues from six hepatocellular carcinoma patients. The transcriptional properties of these individual cells, coupled with the assembled T cell receptor (TCR) sequences, were used to delineate the molecular subtypes, lineage, and functional properties of each T cell group. For five HCC patient, the exome-seq data of matched normal/tumor and bulk RNA-seq data of tumor are also available.

  Study EGAS00001002072

• Accuracy and repeatability of epigenome-based signatures trained on Illumina MethylationEPIC BeadChip data

  Illumina DNA methylation microarrays are popular tools for discovering methylation patterns that enable epigenome-based trait prediction. To ensure reliable and accurate predictions, the robustness of the methylation assay is critical. This dataset comprises technical quadruplicate llumina MethylationEPIC (v1.0) data from matched cervical and blood samples, derived from four individuals, to evaluate the precision of methylation values and the repeatability of epigenome-based models trained to predict disease and aging. Fresh, and frozen blood were treated as separate tissue types, so the data stems from 4 * 4 * 3 = 48 microarrays.

  Study EGAS00001007184

• MutWP5: CRUK Mutographs of Cancer: Breast: BRCA Carriers (Targeted) (2020-01-29)

  Sequencing of LCM-derived microbiopsies from 20 women who underwent risk-reducing reduction mastectomies due to germline BRCA1/2. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Targeted data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequently be sent for whole-genome sequencing. Results from this portion of the study will be compared to women who had cosmetic breast reduction surgeries and those with cancer. . This dataset contains all the data available for this study on 2020-01-29.

  Dataset EGAD00001005920

• MutWP5: CRUK Mutographs of Cancer: Breast: BRCA Carriers (Exome) (2020-01-29)

  Sequencing of LCM-derived microbiopsies from 20 women who underwent risk-reducing reduction mastectomies due to germline BRCA1/2. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequently be sent for whole-genome sequencing. Results from this portion of the study will be compared to women who had cosmetic breast reduction surgeries and those with cancer. . This dataset contains all the data available for this study on 2020-01-29.

  Dataset EGAD00001005921

• MutWP5: CRUK Mutographs of Cancer: Breast: Cancer Mastectomy (Targeted) (2020-01-29)

  Sequencing of LCM-derived microbiopsies from 30 women who mastectomies due to Breast Cancer. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Targeted data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequently be sent for whole-genome sequencing. Results from this portion of the study will be compared to women who had cosmetic breast reduction surgeries and those with germline BRCA 1/2 mutations. . This dataset contains all the data available for this study on 2020-01-29.

  Dataset EGAD00001005923

• MutWP5: CRUK Mutographs of Cancer: Breast: Cancer Mastectomy (Exome) (2020-01-29)

  Sequencing of LCM-derived microbiopsies from 30 women who underwent mastectomies due to a breast cancer diagnosis. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequently be sent for whole-genome sequencing. Results from this portion of the study will be compared to women who had cosmetic breast reduction surgeries and those with germline BRCA 1/2 mutations. . This dataset contains all the data available for this study on 2020-01-29.

  Dataset EGAD00001005924

• Single Cell Genome Sequence for DLP+ library A95618B

  Single Cell Genome Sequence for Triple negative breast cancer patient-derived xenograft SA609 passage 3 on DLP+ library A95618B

  Dataset EGAD00001009316

• Single Cell Genome Sequence for DLP+ library A95628A

  Single Cell Genome Sequence for triple negative breast cancer patient SA1162SB on DLP+ library A95628A

  Dataset EGAD00001009319

• Single Cell Genome Sequence for DLP+ library A95629B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1051D passage 1 on DLP+ library A95629B

  Dataset EGAD00001009320

• Single Cell Genome Sequence for DLP+ library A95632A

  Single Cell Genome Sequence for immortalized breast epithelium - BRCA1-/- Tp53-/- cell line 184-hTERT-22 L9 83.86 on DLP+ library A95632A

  Dataset EGAD00001009321

• Single Cell Genome Sequence for DLP+ library A95632C

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA609 passage 6 on DLP+ library A95632C

  Dataset EGAD00001009322

• Single Cell Genome Sequence for DLP+ library A95634A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1091A passage 1 on DLP+ library A95634A

  Dataset EGAD00001009323

• Single Cell Genome Sequence for DLP+ library A95635A

  Single Cell Genome Sequence for immortalized breast epithelium - BRCA2-/-; Tp53-/- cell line 184-hTERT-22 L9 116.126 on DLP+ library A95635A

  Dataset EGAD00001009324

• Single Cell Genome Sequence for DLP+ library A95650A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1052J passage 1 on DLP+ library A95650A

  Dataset EGAD00001009325

• Single Cell Genome Sequence for DLP+ library A95652A

  Single Cell Genome Sequence for immortalized breast epithelium BRCA2+/- Tp53-/- cell line 184-hTert L9 116.66 on DLP+ library A95652A

  Dataset EGAD00001009326

• Single Cell Genome Sequence for DLP+ library A95652B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1049A passage 1 on DLP+ library A95652B

  Dataset EGAD00001009327

• 10x Genomics Single Cell Gene Expression for TOV2295(R)

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma cell line TOV2295(R)

  Dataset EGAD00001009158

• 10x Genomics Single Cell Gene Expression for SA1035X7XB03502

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 7

  Dataset EGAD00001009151

• 10x Genomics Single Cell Gene Expression for SA535X4XB02498

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 4

  Dataset EGAD00001009152

• 10x Genomics Single Cell Gene Expression for SA1035X5XB03021

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 5

  Dataset EGAD00001009153

• 10x Genomics Single Cell Gene Expression for SA1035X6XB03216

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 6

  Dataset EGAD00001009154

• 10x Genomics Single Cell Gene Expression for SA535X5XB02891

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 5

  Dataset EGAD00001009155

• 10x Genomics Single Cell Gene Expression for SA535X5XB02895

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 5

  Dataset EGAD00001009156

• 10x Genomics Single Cell Gene Expression for SA535X9XB03617

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 9

  Dataset EGAD00001009157

• 10x Genomics Single Cell Gene Expression for SA604X9XB02425

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA604 passage 9

  Dataset EGAD00001009159

• 10x Genomics Single Cell Gene Expression for SA610X3XB03802

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA610 passage 3

  Dataset EGAD00001009160

• Exome Sequencing Analysis of Cutaneous Squamous Cell Carcinoma

  The Exome Sequencing Analysis of Cutaneous Squamous Cell Carcinoma (SCC) study is a single-center cohort study. To identify recurrent genomic aberrations that might underlie the development of this malignancy, we performed whole exome sequencing on a series of SCC-normal pairs to distill a list of 336 candidate genes that were subsequently re-sequenced in 100 SCC-normal pairs with an average depth >1200X. This study also included whole-genome copy number analysis on 5 primary SCC with KNSTRN p.Ser24Phe and 5 histologically matched SCC with wild-type KNSTRN.

  Study phs000785

• Genomic and Transcriptomic Markers Associated with Response to Immune Checkpoint Blockade

  The neoantigen presentation score (NEOPS) study was designed to better understand molecular determinants of response to immunotherapies, including pembrolizumab and nivolumab in stage III or IV melanoma patients. From this work, we developed a composite approach to predicting neoantigens (NEOPS), which takes into account additional escape mechanisms, including HLA LOH (human leukocyte antigen loss of heterozygosity) and the impact of deleterious mutations to the antigen presentation machinery (APM), yielding an improved prediction of response to immunotherapy compared to TMB (tumor mutational burden) or neoantigen burden alone.

  Study phs002388

• Next Generation Mendelian Genetics: Atypical Werner Syndrome

  Werner syndrome (WS) is an adult-onset progeroid syndrome characterized by accelerated aging. The International Registry of Werner Syndrome in the Department of Pathology, University of Washington, collects WS cases from all over the world. Classical WS is caused by WRN mutations. Those who do not carry WRN are categorized as "atypical Werner syndrome." A small subset of atypical WS is caused by LMNA mutations. There also are many cases whose causes are still unknown. The purpose of this study is to identify other causative gene(s) of atypical WS.

  Study phs000434

• Impact of Genomic Variation on Function (IGVF) Consortium

  The IGVF (Impact of Genomic Variation on Function) Consortium aims to understand how genomic variation affects genome function, which in turn impacts phenotype. The NHGRI is funding this collaborative program that brings together teams of investigators who will use state-of-the-art experimental and computational approaches to model, predict, characterize and map genome function, how genome function shapes phenotype, and how these processes are affected by genomic variation. These joint efforts will produce a catalog of the impact of genomic variants on genome function and phenotypes.

  Study phs003472

• A Prospective Study of the Oral Microbiome and Pancreatic Cancer

  Two prospective cohort studies - the Black Women's Health Study and the Southern Community Cohort Study - were used to investigate the oral microbiome in relation to pancreatic cancer risk. Using a nested case-control study design, 148 cases and 510 matched controls were included (122 Black American pancreatic cancer cases and 409 matched controls). DNA was extracted from oral wash samples, using the PowerSoil Pro kit. Paired-end whole metagenomic shotgun sequencing was performed, using the Illumina HiSeq2000 platform with a read length of 100 bp (insert size 350 bp).

  Study phs002454

• WES of Mino-VEN-R Mantle Cell Lymphoma Cells

  This project investigates the genetic basis of therapy resistance in mantle cell lymphoma (MCL) using whole exome sequencing (WES) of the Mino_VEN_R cell line, a model of resistance to pirtobrutinib, a non-covalent BTK inhibitor. Our study suggested that drug-tolerant persister (DTP) cells evade therapy through metabolic and phenotypic reprogramming. By analyzing the exome profile of resistant cells, this study aims to identify mutations associated with treatment escape and cellular plasticity. The findings will contribute to a better understanding of resistance mechanisms and support the development of more effective therapeutic strategies.

  Study EGAS50000001088

• IgM heavy chain V(D)J library sequencing using varied PCR parameters

  When amplifying the rearranged V(D)J genes encoding antigen receptors during adaptive immune receptor repertoire sequencing (AIRR-seq), each cycle of the PCR can produce spurious “chimeric” hybrids of two or more different template sequences. To test the effects of PCR protocol variation on chimera formation in AIRR-seq, we produced IgM heavy chain V(D)J repertoire libraries under 8 conditions, varying the number of PCR cycles, indexing PCR template, input RNA, and extension time. Three donors were sequenced using all 8 conditions.

  Study EGAS50000001037

• DO NOT USE - Whole genome sequencing of SI-NETs from six patients

  Small intestine neuroendocrine tumor (SI-NET), the most common cancer of the small bowel, often displays a curious multifocal phenotype with several intestinal tumors centered around a regional lymph node metastasis, yet the typical path of evolution of these lesions remains unclear. Here, we determined the complete genome sequences of 24 tumor and 3 adjacent normal tissue samples with their paired normal blood samples (totally 33 whole genomes) from 6 patients with multifocal SI-NETs, allowing elucidation of phylogenetic relationships between multiple intestinal tumors and metastases in individual patients.

  Study EGAS00001005009

• Nurminen et al ("GP2Men") Study Primary and Metastatic Prostate Cancer Whole Genome Sequence Data

  We used novel processing techniques to obtain whole genome data together with 3D anatomic and histomorphologic analysis in two men (GP5 and GP12) with high risk PrCa undergoing radical prostatectomy. A total of 22 whole genome-sequenced sites (16 primary cancer foci and 6 lymph node metastatic) were analyzed using evolutionary reconstruction tools and spatio-evolutionary models. Probability models were used to trace spatial and chronological origins of the primary tumor and metastases, chart their genetic drivers, and distinguish metastatic and non-metastatic subclones.

  Study EGAS50000000005

• Contribution of specific cell types to the development of Barrett’s esophagus and carcinoma via germline genetic risk

  This study was designed to elucidate how individual cell types in Barrett’s esophagus (BE) and esophageal adenocarcinoma (EAC) contribute to disease development via germline genetic risk. We performed single cell RNA-sequencing (scRNA-seq) of BE, EAC and paired normal esophagus and gastric fundus tissue samples. After analyzing individual cell types, we integrated the scRNA-seq data and data of a genome-wide association study (GWAS) on BE/EAC to determine cell type-specific genetic risk. Raw data from the RNA-sequencing is provided here.

  Study EGAS50000000530

• Transcriptomic profiling of fragile X syndrome unmethylated full mutation carriers

  Total RNA sequencing of fibroblasts from two unrelated FMR1 unmethylated full mutation carriers, a fragile X patient and a control individual. The existence of rare, unmethylated full mutation carriers who carry the mutation that causes fragile X syndrome but do not gain methylation at the locus offers a rare opportunity to study the mechanisms underlying fragile X syndrome. This study aims to compare the transcriptomes of these four individuals in order to elucidate the mechanism behind the methylation a the FMR1 CGG repeat expansion that causes Fragile X syndrome.

  Study EGAS50000000647