690 results for ""PhD+2001"+"Professor+of+Bioinformatics"+2012+18000+citations+profile"

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• Bibliography Statistics

  EGA Statistics Bibliography Growth Community Archive Distribution Catalogue Here we expose in a yearly and cumulative manner, the publications, citations, publishers journals and impact factor of EGA related studies. Publications citing data stored at the EGA The studies that use EGA datasets are requested to cite the EGA into their bibliography. This fact allows for a faster spreading of the role and purpose of the EGA, being the availability of their studies for testability and reusability purposes. In order to track the studies we use the unique study accession, provided by the EGA when submitting a new study, and comprised of the keyword EGAS followed by 11 digits such as EGAS00000000001. We use the Europe PMC RESTful Web Service in order to query, and index studies where the EGAS accession was used. Below, you can find a chart showing the journal publishers of the studies citing data stored in the EGA being cited: Publications Citing Data Stored in the EGA pieChart('publishers-citations', 'https://stats.ega-archive.org/publishers/citations', 'Publishers') Number of publications citing data stored in the EGA by year Here, you can find a chart showing the number of publications citing data stored in the EGA by year. These publications could have deposit, or re-used the data. The study acession can be found in the publication. The default values are non-cumulative. You can see cumulative values by clicking "Cumulative". Number of Publications Citing Data Stored in the EGA by Year barChart('publications-by-year', 'https://stats.ega-archive.org/publications/year', ['Number of Publications by Year', 'Publications by Year']) Journal Impact Factor of Publications Citing Data Stored in the EGA Here, you can find a chart showing the journal impact factor of publications citing data stored in the EGA. We have used Scimago Journal Rank for this purpose. Low impact treshold was defined between 0.0 and 5.0 excluding; Medium impact treshold was defined between 5.0 and 10.0 excluding; High impact range was established from values equal to or higher than 10.0; Journal Impact Factor of Publications Citing Data Stored in the EGA pieChart('citations-publication-impact-factor', 'https://stats.ega-archive.org/citations/publication/impact/factor', 'Publication Impact Factor') Publications citing a publication containing a EGA study accession The publications, stating a EGA study accession in the bibliography, can be cited for testibility or reusability purposes. Below, you can find a chart showing the publishers of the publications being cited: Publications Citing a Publication Containing a EGA Study Accession pieChart('publications-citations', 'https://stats.ega-archive.org/publications/citations', 'Publishers') Number of publications citing a publication containing a EGA study accession by year Here, you can find a chart showing the number of publications citing a publication containing a EGA study accession by year by year. The values are non-cumulative: Number of published citations by year barChart('citations-year', 'https://stats.ega-archive.org/citations/year', ['Number of Publications', 'Citations by Year'])

  Documentation about/statistics/bibliography

• Single-cell analysis reveals fibroblast clusters linked to immunotherapy resistance in cancer

  A subset of Cancer-Associated Fibroblasts (CAF-S1) mediates immunosuppression in breast cancers (BC), but its heterogeneity and its impact on immunotherapy response remain unknown. Here, we identify 8 CAF-S1 clusters by analyzing more than 18000 single CAF-S1 fibroblasts from BC. We validate the 5 most abundant clusters by flow cytometry and in silico analyses in other cancer types, highlighting their relevance. Myofibroblasts from clusters 0 and 3, characterized by extra-cellular matrix proteins and TGF signaling respectively, are indicative of primary resistance to immunotherapies. Cluster 0 up-regulates PD-1 and CTLA-4 protein levels in regulatory T lymphocytes (Tregs), which in turn increases CAF-S1 cluster 3 cellular content. Thus, our study highlights a positive feedback loop between specific CAF-S1 clusters and Tregs and uncovers their role in immunotherapy resistance.

  Study EGAS00001004030

• Targeted sequencing of Burkitt lymphoma tumour samples from the UK's Haematological Malignancy Research Network

  The UK’s Haematological Malignancy Research Network (www.HMRN.org) was established in 2004 to provide robust generalizable data to inform clinical practice and research. HMRN is a collaboration between researchers in the Epidemiology & Statistics Group (ECSG) at the University of York, a unified Clinical Network operating across 14 hospitals, and an integrated Haematological Malignancy Diagnostic Service (HMDS) in Leeds. Covering a population of around 4 million, HMRN collects detailed information about all patients diagnosed with a haematological malignancy within the HMRN region, accruing around 2,400 new diagnoses each year. The population has a similar socio-demographic profile to the country as a whole, and HMRN’s maturing data present an increasingly valuable resource to address real questions of concern to haematologists, commissioners and health service researchers – locally, nationally and internationally. This study forms part of a larger project employing targeted exome sequencing on tumour samples from patients diagnosed with a variety of both lymphoid and myeloid malignancies. The results for samples collected from 39 Burkitt lymphoma patients, diagnosed within HMRN from 2005 to 2012, are provided.

  Study EGAS00001004649

• Targeted sequencing of diffuse large B-cell lymphoma tumour samples from the UK's Haematological Malignancy Research Network

  The UK’s Haematological Malignancy Research Network (www.HMRN.org) was established in 2004 to provide robust generalizable data to inform clinical practice and research. HMRN is a collaboration between researchers in the Epidemiology & Statistics Group (ECSG) at the University of York, a unified Clinical Network operating across 14 hospitals, and an integrated Haematological Malignancy Diagnostic Service (HMDS) in Leeds. Covering a population of around 4 million, HMRN collects detailed information about all patients diagnosed with a haematological malignancy within the HMRN region, accruing around 2,400 new diagnoses each year. The population has a similar socio-demographic profile to the country as a whole, and HMRN’s maturing data present an increasingly valuable resource to address real questions of concern to haematologists, commissioners and health service researchers – locally, nationally and internationally. This study forms part of a larger project employing targeted exome sequencing on tumour samples from patients diagnosed with a variety of both lymphoid and myeloid malignancies. The results for samples collected from 928 diffuse large B-cell lymphoma patients, diagnosed within HMRN from 2005 to 2012, are provided.

  Study EGAS00001005953

• UK10K_NEURO_FSZ REL-2012-11-27

  UK10K_NEURO_FSZ REL-2012-11-27

  Dataset EGAD00001000318

• UK10K_OBESITY_SCOOP REL-2012-01-13

  UK10K_OBESITY_SCOOP REL-2012-01-13

  Dataset EGAD00001000181

• Effects of GATA4-inhibiting compound 3i-2012 on HB-243 hepatoblastoma cells

  In order to study the effects of GATA4 inhibition, HB-243 hepatoblastoma cells were treated with GATA4-inhibiting compound 3i-2012 for 24 hours. Total RNA was extracted and sequenced.

  Study EGAS50000000999

• Genome-Wide Association Study of Lung Cancer Susceptibility in Never-Smoking Women in Asia

  To learn about the etiology of lung cancer among never-smoking women in Asia, we formed the Female Lung Cancer Consortium in Asia (FLCCA), which includes studies of lung cancer in Eastern Asia and conducted a GWAS. We analyzed a total of 5510 lung cancer cases and 4544 controls and identified 3 novel loci (Lan et al., 2012). Of these study subjects, 4922 lung cancer cases and 3959 controls are available for posting. Lan et al.., Genome-wide association analysis identifies new lung cancer susceptibility loci in never-smoking women in Asia. Nat Genet. 2012 Dec;44(12):1330-5. doi: 10.1038/ng.2456. Epub 2012 Nov 11. PubMed PMID: 23143601.

  Study phs000716

• Epigenomic profile of diverse cancer

  Epigenomic profile of diverse cancer.

  Study EGAS00001004352

• UK10K_RARE_THYROID REL-2012-01-13

  UK10K_RARE_THYROID REL-2012-01-13

  Dataset EGAD00001000152

• UK10K_RARE_SIR REL-2012-01-13

  UK10K_RARE_SIR REL-2012-01-13

  Dataset EGAD00001000153

• Plasma DNA profile in DNASE1L3 deficiency

  Plasma DNA profile in DNASE1L3 deficiency

  Study EGAS00001004342

• Plasma DNA profile in DNASE1L3 deficiency-Mouse AAV samples

  Plasma DNA profile in DNASE1L3 deficiency-Mouse AAV

  Study EGAS00001004409

• CNV profile in HSP90 inhibitor resistant K562 cells

  Analysis of the acquired copy number profile in K562 cell which got resistant against HSP90 inhibitors.

  Study EGAS00001006385

• Sardinian Chromsome Y 2012 Analysis

  1204 Sardinian males

  Dataset EGAD00001000618

• RNA sequencing of chondrosarcoma

  To profile chondrosarcoma patients.

  Study EGAS00001004585

• UK10K_NEURO_FSZNK REL-2012-11-27

  UK10K_NEURO_FSZNK REL-2012-11-27

  Dataset EGAD00001000332

• UK10K_NEURO_UKSCZ REL-2012-11-27

  UK10K_NEURO_UKSCZ REL-2012-11-27

  Dataset EGAD00001000335

• Copy number and mutation profiling of Stage 1 epithelial ovarian cancer biopsies

  This project aims at characterizing the genome-wide copy number profile and the variant profile of 139 genes om the five major histotytpes of early-stage (stage I) epithelial ovarian cancer (EOC), to provide insight in the the aethiology and development of the disease.

  Study EGAS00001004961

• UK10K_RARE_THYROID REL-2012-11-27

  UK10K_RARE_THYROID REL-2012-11-27

  Dataset EGAD00001000329

• UK10K_RARE_SIR REL-2012-11-27

  UK10K_RARE_SIR REL-2012-11-27

  Dataset EGAD00001000334

• UK10K_OBESITY_SCOOP REL-2012-11-27

  UK10K_OBESITY_SCOOP REL-2012-11-27

  Dataset EGAD00001000336

• Plasma DNA profile in DNASE1L3 deficiency

  Plasma DNA profile in DNASE1L3 deficiency

  Dataset EGAD00001006216

• REL-2017-07-2012

  HipSci - Primary Immune Deficiency - Genotyping Array - July 2017

  Dataset EGAD00010001358

• Characterization of Leukemic Stem Cells in DNMT3Amut and NPM1mut AMLs

  Trascriptomic profile of FACS-sorted LSCs from diagnostic DNMT3Amut and NPM1mut AML patients using a novel sorting strategy. Briefly, positive selection for GPR56 and a negative selection for NKG2DLigands were used to enrich for LSCs in both CD34+ and CD34- subpopulations. Primary samples were retrospectively collected based on their mutational profile.

  Study EGAS00001006527

• Transcriptome analysis of soft tissue sarcoma

  We characterized mRNA expression profile of soft tissue sarcomas.

  Study EGAS50000001672

• Widespread DNA hypomethylation and differential gene expression in Turner syndrome

  Adults with 45,X monosomy (Turner syndrome) reflect a surviving minority since more than 99% of fetuses with 45,X monosomy die in utero. In adulthood 45,X monosomy is associated with increased morbidity and mortality, although strikingly heterogeneous with some individuals left untouched while others suffer from cardiovascular disease, autoimmune disease and infertility. The present study investigates the leukocyte DNAmethylation profile by using the 450K-Illumina Infinium assay and the leukocyte RNA-expression profile in 45,X monosomy compared with karyotypically normal female and male controls. We present results illustrating that genome wide X-chromosome RNA-expression profile, autosomal DNA-methylation profile, and the X-chromosome methylation profile clearly distinguish Turner syndrome from controls. Our results reveal genome wide hypomethylation with most differentially methylated positions showing a medium level of methylation. Contrary to previous studies, applying a single loci specific analysis at well-defined DNA loci, our results indicate that the hypomethylation extend to repetitive elements. We describe novel candidate genes that could be involved in comorbidity in TS and explain congenital urinary malformations (PRKX), premature ovarian failure (KDM6A), and aortic aneurysm formation (ZFYVE9 and TIMP1)

  Study EGAS00001002190

• Dense_fine_mapping_study_identifies_new_susceptibility_loci_for_primary_biliary_cirrhosis

  2,981 primary biliary cirrhosis (PBC) cases were collected by the UK PBC Consortium and genotyped on the Illumina Immunochip where 2,861 passed quality control. These cases were then compared to a UK population control to identify novel PBC risk loci and fine-map association signals. (Liu & Almarri et al., Nat Genet, 2012)

  Study EGAS00001001837

• ICGC MMML-seq Data Freeze November 2012 transcriptome sequencing

  ICGC MMML-seq Data Freeze November 2012 transcriptome sequencing

  Dataset EGAD00001000281

• Pseudotime_ordering_of_cell_cycle_state

  We will be using G&T method to sequence single cell genome and transcriptome derived from FS13B iPSCs cell line. The cell cycle state of each of the single cells is known. Hence, we will be analysing the genome and transcriptome of single cells from each of the cell cycle state to generate a copy number profile and transcriptome profile per given cell cycle stage: G1, S, G2, S.

  Study EGAS00001003293

• ICGC MMML-seq Data Freeze November 2012 whole exome sequencing

  ICGC MMML-seq Data Freeze November 2012 whole exome sequencing

  Dataset EGAD00001000279

• ICGC MMML-seq Data Freeze November 2012 whole genome sequencing

  ICGC MMML-seq Data Freeze November 2012 whole genome sequencing

  Dataset EGAD00001000278

• Gut metagenome/FR 2002

  The main goal of the project is the study the associations between the gut metagenome and human health. The dataset contains data for n=7211 FINRISK 2002 participants who underwent fecal sampling. Demultiplexed shallow shotgun metagenomic sequences were quality filtered and adapter trimmed using Atropos (Didion et al., 2017), and human filtered using Bowtie2 (Langmead and Salzberg, 2012).

  Study EGAS00001005038

• SCLC study Peifer et al. - WES dataset

  SCLC - Whole genome sequencing data Publication Peifer et al., 2012, Nature Genetics

  Dataset EGAD00001000703

• Whole-Genome Sequencing of 128 Ashkenazi Jewish individuals

  We sequenced 128 individuals of Ashkenazi Jewish ancestry. All individuals were controls in other studies: (1) Longevity (Gil Atzmon's lab; Albert Einstein College of Medicine), n=74. (2) Parkinson's disease (Lorraine Clark's lab; Columbia University Medical Center), n=54. Whole-genome, high-coverage (50x) sequencing was performed by Complete Genomics in 2012 and 2013.

  Study EGAS00001000664

• SCLC study Peifer et al. - RNAseq dataset

  SCLC - RNA sequencing data Publication Peifer et al., 2012, Nature Genetics

  Dataset EGAD00001001431

• Epigenomic data of Human muscle stem cell

  To profile the epigenomic landscape of Human muscle stem cell, ChIP-seq of histone marks , WGBS and RNA-seq data were generated.

  Study EGAS00001006159

• Cell-free DNA and bone marrow samples from myelodysplastic syndromes

  We have assessed the molecular profile of a cohort of 70 patients with MDS by next-generation sequencing (NGS) using cfDNA and compared the results to paired bone marrow (BM) DNA. Sequencing of BM DNA and cfDNA showed a comparable mutational profile and variant allele frequencies (VAF) strongly correlated between both sample types. Our results support the analysis of cfDNA as a promising strategy for performing molecular characterization, detection of chromosomal aberrations and monitoring of MDS patients.

  Study EGAS00001005992

• Searching for DNA methylation sites associated with panic disorder

  This study aimed to identify whole-genome DNA methylation profile of panic disoeder and to search DNA methylation sites associated with the disease

  Study JGAS000111

• scWGS profile, paediatric acute lymphoblastic leukemia ALL40

  Single cell sequencing using the direct nuclear tagmentation and RNA sequencing (DNTR-seq) method was performed on the diagnostic bone marrow sample (ALL40). This dataset consists of the DNA (scWGS) profile from 384 cells. Two fastq files are associated with each cell identifier.

  Dataset EGAD50000001774

• Elucidation of molecular mechanism of NAFLD-HCC

  We analysed the somatic mutation profile of 69 genes with recurrent genetic alterations reported in HCC using surgically-resected tumor tissues of non-viral HCC patients.

  Study JGAS000523

• Progressive multifocal leukoencephalopathy (PML)

  We generated RNAseq, ATACseq, Multiomics and CITEseq for patients with Progressive multifocal leukoencephalopathy (PML) to profile the chromatin accessibility, transcriptional profiles and surface proteins at single-cell level.

  Study EGAS50000000139

• Epigenomic data of HEMa_LP

  To profile the epigenomic landscape of Human Epidermal Melanocytes , adult, lightly pigmented(HEMa-LP), whole genome bisulphite sequencing (WGBS) and ChIP-seq of histone marks data were generated.

  Study EGAS00001004016

• Gut metagenome/FINRISK 2002 (Salosensaari et al. Nature Comms 2021)

  The main goal of the project is the study the associations between the gut metagenome and human health. The dataset contains data for n=7211 FINRISK 2002 participants who underwent fecal sampling. Demultiplexed shallow shotgun metagenomic sequences were quality filtered and adapter trimmed using Atropos (Didion et al., 2017), and human filtered using Bowtie2 (Langmead and Salzberg, 2012).

  Study EGAS00001005020

• Relating Clinical Outcomes in Multiple Myeloma to Personal Assessment of Genetic Profile

  The Multiple Myeloma Research Foundation (MMRF) CoMMpass (Relating Clinical Outcomes in MM to Personal Assessment of Genetic Profile) trial (NCT01454297) is a longitudinal observation study of 1000 newly diagnosed myeloma patients receiving various standard approved treatments that aim at collecting tissue samples, genetic information, Quality of Life (QoL) and various disease and clinical outcomes over 10 years.

  Study phs000748

• RNA-seq of CD34+ HSPCs from LRMDS patients

  To profile transcriptional alterations of HSPCs in LR-MDS patients, 7AAD−CD45+Lin-CD235a−CD34+ cells were isolated from healthy donors and LR-MDS patients for RNA sequencing.

  Study EGAS00001008182

• AmsterdamUMC Data Access Committee for the study entitled "Carboxylesterase 1 mediates a distinctive metabolic profile of dendritic cells to attain an inflammatory phenotype"

  The current data access committee reviews and assesses data requests of researchers that seek to gain access to data presented in the manuscript entitled "Carboxylesterase 1 mediates a distinctive metabolic profile of dendritic cells to attain an inflammatory phenotype" as performed at the AmsterdamUMC, Amsterdam, Netherlands.

  Dac EGAC50000000178

• Whole exome sequencing of the dMMR colorectal cancer cohort

  We leveraged the ImmunoID NeXT platform, an Immune-enhanced multiomics platform to profile a cohort of patients with dMMR CRC. This sub-study includes the whole exome sequencing data

  Study EGAS50000001744

• TCR and BCR sequencing of the dMMR colorectal cancer cohort

  We leveraged the ImmunoID NeXT platform, an Immune-enhanced multiomics platform to profile a cohort of patients with dMMR CRC. This sub-study includes the TCR and BCR sequencing data

  Study EGAS50000001743

• Whole transcriptome sequencing of the dMMR colorectal cancer cohort

  We leveraged the ImmunoID NeXT platform, an Immune-enhanced multiomics platform to profile a cohort of patients with dMMR CRC. This sub-study includes the whole transriptome sequencing data

  Study EGAS50000001742

• Whone genome DNA methylation profile

  Primary human CD4+ naive T cells were cultured in vitro and sorted based on the defined number of division steps which they have undergone. Of those populations (division 0/div4/div6) EMseq data were generated to assess the whole-genome DNA methylation profile. 2 independent experiments with 2 different donors were conducted

  Dataset EGAD50000001815

• RnaSeq profile of UPS samples

  Dac EGAC00001001707

• Segmental_cherry_angioma_case

  Cherry angiomas are common benign blood vessel growths on the skin. In this study we characterise mutational profile of a cherry angioma and adjacent skin biopsied from a patient with multiple lesions with segmental presentation.

  Study EGAS00001008212

• DAC-Genomic Profile of Sporadic Multiple Meningiomas

  Dac EGAC00001002630

• Mesothelial peritoneal adhesions profile Data Access Commitee

  Dac EGAC00001002389

• Molecular profile of IMFT for the identification of potential druggable targets and biomarkers predicting crizotinib response.

  The clinical phase II trial EORTC 90101 “CREATE” showed high anti-tumor activity of crizotinib, an ALK/ROS1 inhibitor, in IMFT patients. However, results suggested that other molecular targets in addition to ALK/ROS1 might also contribute to the sensitivity of this kinase inhibitor. We therefore characterized molecular profile of IMFT to identify alterations which could play a role in the response to crizotinib.

  Study EGAS00001005419

• Pan-tumor genomic biomarkers for personalization of PD-1 checkpoint blockade based immunotherapy

  Tumor mutation burden (TMB) and a T-cell-inflamed gene expression profile (GEP) independently predict clinical outcome in pembrolizumab-treated patients in 22 indications and stratify distinct targets of resistance biology.

  Study phs001572

• NHLBI TOPMed: Trans-Omics Analysis for Congestive Heart Failure (TOPCHeF)

  Heart failure (HF) is a serious, common, morbid condition that has a huge public health impact. In 2012 alone, there were >1M hospital discharges and >1.7M outpatient visits where HF was the principal diagnosis. HF is the most common hospital discharge diagnosis of the elderly and led to costs in excess of $30B in 2012. Unfortunately, HF therapies have not impacted the 50% 5-year mortality over the past two decades. Our laboratory focuses on cardiomyopathies (CMs) and HF. Dilated cardiomyopathy (DCM) has been a main focus of our laboratory and is the first and third most frequent cause of heart transplantation and HF, respectively. Attention is shifting from the mere identification and cataloging of CM/HF genes and mutations to understanding the molecular and functional cellular processes that drive HF. In this study, we will utilize whole genome sequencing (WGS) and transcriptome analysis of left ventricle samples from adult and pediatric samples from heart banks at the University of Colorado Anschutz Medical Campus and the Children's Hospital Colorado to develop a complete understanding of left ventricular biology and a partial understanding of HF inferred through the lens of a single-chamber perspective.

  Study phs002038

• Cryptic Relatedness in the Singapore Living Biobank Project

  The Singapore Living Biobank is a collection of healthy population-based Chinese and Malay individuals, for the purpose of phenotype recall study of high-impact variant carriers. These individuals are sampled from two studies: Multi-Ethnic Cohort (MEC), and the Singapore Health 2012 (SH2012). The MEC is a population-based cohort initiated in 2007 to investigate the genetic and lifestyle factors that affect the risk of developing chronic diseases such as diabetes and cardiovascular outcomes in the three ethnic groups (Chinese, Malays, and Indians). The SH2012 study is a population-based cross-sectional survey conducted in Singapore between 2012 and 2013, with over-sampling of Malays and Indians. Participants in MEC and SH2012 completed a similar set of questionnaire components, health examination, and biochemisty panels. Description of the MEC and SH2012 studies can be found at http://blog.nus.edu.sg/sphs/. We generated whole-exome sequencing data and Illumina OmniExpress array genotyping data for 1,299 Chinese and 1,229 Malays from the Singapore Living Biobank. This study includes a subset of 762 individuals that were found to be closely related (≤3rd degree), including 263 Chinese and 499 Malays.

  Study EGAS00001002619

• The data usage policy for epigenomic profile of diverse cancer

  Dac EGAC00001001540

• Gene expression profile of mesothelial cells from peritoneal adhesion biopsies

  Study EGAS00001005749

• Developmental Maturation of Hematopoietic Stem and Progenitor Cells Mediated by Lin28b/Let-7/Cbx2

  This study encompasses two human cell lines used to profile polycomb repressive complex markers during hematopoietic maturation.  This study includes epigenomic mark sequencing data obtained via the CUT&RUN protocol.

  Study phs002507

• LCCC1122: Defining the Triple Negative Breast Cancer Kinome Response to GSK1120212

  In this study the investigators looked at adaptive reprogramming impact on the kinome when a MEK inhibitor called GSK1120212 (trametinib) was administered in a "window of opportunity" trial. GSK1120212 is not yet approved by the FDA for use in breast cancer patients. The investigators gave GSK1120212 for a short period of time (one week) to examine MEK and the other kinase expression in cancer cells both before and after the study drug is given. The investigators gave this drug for research purposes only. The length of time it was given is not intended to treat cancer. Recently researchers at UNC developed a process that can comprehensively profile the majority of the individual kinases in the kinome and examine the impact on kinase expression of kinase inhibitors (Duncan et al, Cell 2012, PMID: 22500798). This can tell us which kinases need to be concurrently blocked to augment responsiveness and prevent acquired resistance so that the investigators can design the best combinations of kinase blocking drugs for triple negative breast cancer. This is especially important for individuals with triple negative breast cancer (TNBC) because there are no targeted drugs available that can block molecules that affect tumor growth. The investigators believe that kinase-blocking drugs have the potential to be a more effective treatment for people with TNBC. In this recently published study (Zawistowski et al, Cancer Discovery 2017, PMID: 28108460), TNBC patients treated with trametinib for 7 days resulted in a transcriptional response characterized by significant reprogramming of the tyrosine kinome, and this adaptive bypass response in human tumors was found to be similar to that seen in preclinical models including TNBC cell lines and mouse xenografts. In this study we also examined whether reprogramming differed between TNBC molecular subtypes, finding that basal-like and claudin-low human TNBC cells and mouse tumor subtypes had different adaptive transcriptional responses to MEK-ERK inhibition. Mechanistically we found that genome-wide enhancer remodeling drove the adaptive transcriptional response, suggesting that epigenetic approaches to reprogramming may be more durable than kinase inhibitor polypharmacology.

  Study phs001405

• Gene expression profile of mesothelial-derived carcinoma-associated fibroblasts Data Access Commitee

  Dac EGAC00001001267

• nanostring analysis

  mRNA expression profile of kidney cancer

  Dataset EGAD00010001535

• smallRNA-seq of isolated pancreatic islets

  In this study we performed smallRNA-sequencing, a sequencing method designed for small noncoding RNAs, to investigate the miRNA expression profile of human islets isolated from pancreata of donors without diabetes mellitus (n=3) and donors with type 2 diabetes (n=3).

  Study EGAS50000000865

• Deep sequencing of the gut microbiome from 946 healthy donors of the Milieu Intérieur cohort

  In this study, we aim to determine, in a thousand healthy donors, how the profile and dynamics of the gut microbiome are affected by host factors such as sex, age and lifestyle parameters.

  Study EGAS00001004437

• Deciphering molecular mechanisms underlying hematological malignancies and development of novel therapeutic approaches

  We aim to identify epigenomic features dysregulated in hematological malignancies through epigenetic analyses of hematological malignant cells. We also perform RNA sequencing to profile tumor cell-specific transcriptomes and target gene sequencing to profile somatic gene mutations in tumor cells. Regarding identified epigenomic abnormalities, we perform further analysis to determine whether they could be good candidates to translate into therapy development. To this end, we will modulate the activity of targets by using their activators and inhibitors in vitro and establish xenograft mouse models of hematological malignancies and manipulate their activity in vivo. Through these studies, we aim to develop new therapeutic agents or modalities that lead to improved patients��� prognosis.

  Study JGAS000603

• HIPSD&R-seq enables scalable genomic copy number and transcriptome profiling

  Single-cell DNA-sequencing (scDNA-seq) enables decoding somatic cancer variation. Existing methods are hampered by low throughput or cannot be combined with transcriptome sequencing in the same cell. We propose HIPSD&R-seq (HIgh-throughPut Single-cell Dna and Rna-seq), a scalable yet simple and accessible assay to profile low-coverage DNA and RNA in thousands of cells in parallel. Our approach builds on a modification of the 10X Genomics platform for scATAC and multiome profiling. In applications to human cell models and primary tissue, we demonstrate the feasibility to detect rare clones and we combine the assay with combinatorial indexing to profile over 17,000 cells.

  Study EGAS50000000691

• Whole genome, RNA-seq and single-cell Multiome profile of multiple myeloma

  Study EGAS00001007014

• EpS_methylation_850K

  Methylation profile (array data using EPIC_850K) from tumour samples (epithelioid sarcoma)

  Dataset EGAD00010002571

• Array_FL_dataset_4

  CN/LOH-profile of Translocation-negative FL_4

  Dataset EGAD00010001236

• Array_FL_dataset_10

  CN/LOH-profile of Translocation-negative FL_10

  Dataset EGAD00010001237

• Array_FL_dataset_2

  CN/LOH-profile of Translocation-negative FL_2

  Dataset EGAD00010001238

• Array_FL_dataset_6

  CN/LOH-profile of Translocation-negative FL_6

  Dataset EGAD00010001239

• Array_FL_dataset_8

  CN/LOH-profile of Translocation-negative FL_8

  Dataset EGAD00010001232

• Array_FL_dataset_7

  CN/LOH-profile of Translocation-negative FL_7

  Dataset EGAD00010001241

• Array_FL_dataset_1

  CN/LOH-profile of Translocation-negative FL_1

  Dataset EGAD00010001240

• Array_FL_dataset_5

  CN/LOH-profile of Translocation-negative FL_5

  Dataset EGAD00010001233

• Array_FL_dataset_9

  CN/LOH-profile of Translocation-negative FL_9

  Dataset EGAD00010001234

• Array_FL_dataset_11

  CN/LOH-profile of Translocation-negative FL_11

  Dataset EGAD00010001235

• NIDDK IBD Genetics Consortium Repository Immunochip

  The Immunochip is a custom Illumina Infinium chip comprising 196,524 SNPs and small indels selected primarily based on GWAS analysis of 12 autoimmune and inflammatory diseases. The chip has two purposes: fine mapping of 289 established associations corresponding to 187 distinct loci, and deep replication of suggestive, but not yet proven, associations. Fine-mapping regions were defined as 0.2cM centered on GWAS hit SNPs, and all SNPs and short indels in these regions from the 1000 Genomes Project low coverage pilot CEU samples, as well as variants discovered in resequencing experiments conducted by groups collaborating in the chip design were selected for inclusion. Replication of autoimmune and inflammatory GWAS (including Crohn's disease and ulcerative colitis) contributed the bulk of the remaining SNP lists. Approximately 25,000 SNPs were included as replication of unrelated diseases as part of the WTCCC2 project, which serve as useful null SNPs for these analyses. In total, approximately 240,000 SNPs were selected for inclusion, with an assay design success rate of ~80%. Reprinted from Jostins et al. (2012), with permission from Springer Nature (see https://www.nature.com/reprints/permission-requests.html). Jostins, L., et al. (2012) Host-microbe interactions have shaped the genetic architecture of inflammatory bowel disease. Nature, 491, 119-24. PMID: 23128233.

  Study phs001721

• Exome_trios_in_patients_with_gastroschisis

  Gastroschisis (MIM 230750) is a herniation of the intestines through a defect of the abdominal wall lateral to the umbilicus (usually on the right side), and it is not covered by a membrane [Ledbetter, 2012]. Gastroschisis is a congenital anomaly with increasing incidence, easy prenatal diagnosis and extremely variable postnatal outcomes. On the basis of clinical manifestations, epidemiologic charateristics, and the presence and type of additional malformations, gastroschisis could be considered a heterogeneous condition with no gene/s discovered yet. This congenital anomaly affects approximately 1-3 infancts per 10,000 live births [Calzolari et al.1995;Parker et al.,2010] Current knowledge about causative mutations/variants. To date, no single gene has been linked to gastroschisis. Some publications have tried to link this malformation to variants in genes (such as AEBP1 (adipocyte enhancer binding protein) gene [Feldkamp et al,. 2012] or the VEGF-NOS3 pathway [Lammer et al., 2008]. Previously, a Scribble mutant mouse model (circletail) was reported to exhibit gastroschisis, however recent studies demonstrated that the Scribble knockout fetus exhibits exomphalos phenotype of gastroschisis [Carnagham et al., 2013]. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001002664

• SNU_PROSPECTIVE

  This study includes 5 paired samples of Korean AML paitients. 5 AML tumor samples are paired with each normal(Saliva or BM derived) sequencing data.The results of this WES study were analyzed by Mutect and GATK for ranking germline variants and cancer variants to make mutational profile matrix.

  Study EGAS00001002154

• single cell RNA-seq of small cell lung cancer tumors

  This study investigated the transcriptomic profile of small cell lung cancer from 10 patients. Tumors were rapidly dissociated after the surgical procedure. Libraries were constructed using the VDJ NextGEM v1.1 10x Genomics Chromium kit. Samples were sequenced on a NextSeq 550 sequencer (Illumina).

  Study EGAS50000001400

• SNU_WGS_AML

  This study includes 10 paired samples of Korean AML paitients.10 AML tumor samples are paired with each normal(Saliva or BM derived) sequencing data.The results of this WGS study were analyzed by Mutect and GATK for ranking germline variants and cancer variants to make mutational profile matrix.

  Study EGAS00001001906

• A fast, affordable and minimally-invasive diagnostic test for Cancer of Unknown Primary (CUP) using DNA methylation profiling

  CUP diagnosis on FFPE tissue and liquid biopsies (blood, pleural and peritoneal effusions) using cfRRBS (cell-free reduced representation bisulfite sequencing), a technique that allows for identification of the methylation profile starting from minimal amounts of highly fragmented DNA.

  Study EGAS50000000257

• Single cell RNA sequencing of colorectal cancer patients (KUL3/KUL5)

  Libraries for scRNA-seq were generated using the Chromium Single Cell 3′ or 5′ library and Gel Bead & Multiplex Kit from 10x Genomics. Aimed to profile 5000 cells per library (if sufficient cells were retained during dissociation).

  Study EGAS00001006049

• Dataset developed for use with EOSC4Cancer of synthetic colorectal cancer tumor/normal pairs.

  This dataset contains 10 tumor and normal pairs synthetic WGS data of colorectal cancer that were simulated in a standard format of Illumina paired-end reads. The NEAT read simulator (version 3.0, https://github.com/zstephens/neat-genreads) was utilized to synthetize these 10 pairs of tumor and normal WGS data. In the procedure of data generation, simulated parameters (i.e., sequencing error statistics, read fragment length distribution and GC% coverage bias) were learned from data models provided by NEAT. The average sequencing depth for tumor and normal samples aimed to reach around 110X and 60X, respectively. For generation of synthetic normal WGS data per each sample, a germline variant profile from a real patient was down-sampled randomly, representing 50% germline variants of a given patient. These were mixed with the other 50% in silico germline variants that were modelled randomly using an average mutation rate (0.001), finally constituting a full germline profile for normal synthetic WGS data. For generation of synthetic tumor WGS data per each sample, a pre-defined somatic short variant profile (SNVs+Indels) learnt from a real CRC patient was added to the germline variant profile used for creating the normal synthetic WGS data of the same patient, consisting of the variants for tumor sample. Neither copy number profile nor structural variation profile was introduced into the tumor synthetic WGS data. Tumor content and ploidy were assumed to be 100% and 2, respectively. For mapping/variant detection, the Sarek pipeline v3.1.2 (https://nf-co.re/sarek/3.1.2) was used, specifically: 1. BWA v0.7.17-r1188 for read mapping 2. GATK v4.3.0.0 for pre-processing BAM file (including markduplicates and recalibration). 2. Mutect2 (GATK v4.3.0.0) for somatic variant calling 3. Strelka2 v2.9.10 for germline and somatic variant calling Metadata information of 10 CRC patients used for the generation of synthetic normal and tumor WGS data: Patient_id Tumor_barcode Normal_barcode Age Sex Tissue Cancer SIM007 SIM007_T SIM007_N 71 F Rectal Primary CRC SIM008 SIM008_T SIM008_N 45 F Colon Neuroendocrine Metastasis CRC SIM010 SIM010_T SIM010_N 62 M Colon Metastasis CRC SIM011 SIM011_T SIM011_N 55 M Colon Neuroendocrine Metastasis CRC SIM012 SIM012_T SIM012_N 57 M Rectal Metastasis CRC SIM013 SIM013_T SIM013_N 69 M Colon Metastasis CRC SIM014 SIM014_T SIM014_N 68 M Colon Neuroendocrine primary CRC SIM015 SIM015_T SIM015_N 58 F Colon Primary CRC SIM016 SIM016_T SIM016_N 49 M Colon/Rectal Primary CRC SIM017 SIM017_T SIM017_N 78 M Colon Neuroendocrine primary CRC

  Dataset EGAD50000000564

• Copy number analysis by SNP array

  Hybridization-based genomic profiling arrays were performed using Genome-Wide Human SNP Array 6.0 or the CytoScan HD array, according to the manufacturer’s instructions (Affymetrix, Santa Clara, CA, USA) now part of Thermo Fisher Scientific (Thermo Fisher Scientific, Inc.) Following the procedures of sample preparation, hybridization, and scanning, the CEL file of Genome-Wide Human SNP Array 6.0 was analyzed as previously described (Magrangeas et al. 2012) and the CEL file of CytoScan HD array was analyzed using the Chromosome Analysis Suite (ChAS) software (Thermo Fisher Scientific, Inc).

  Study EGAS00001005125

• UK10K_COHORT_ALSPAC REL-2012-06-02

  UK10K_COHORT_ALSPAC REL-2012-06-02: Low-coverage whole genome sequencing; variant calling, genotype calling and phasing

  Dataset EGAD00001000740

• UK10K_NEURO_UKSCZ REL-2012-07-05

  UK10K_NEURO_UKSCZ REL-2012-07-05

  Dataset EGAD00001000256

• PBAT sequencing of naïve human ESCs

  This project investigates the DNA methylation landscape of naïve human embryonic stem cells (hESCs) derived from human embryos, assessing the impact of ERK inhibition (ERKi). Naïve ESCs were cultured in UXGL or PXGL media. Post bisulphite adaptor tagging protocol was used to profile genome-wide DNA methylation.

  Study EGAS50000001006

• WGS-Lung Cancer sample 30 pair

  This study includes 30 paired samples of Korean Lung Cancer paitients. 30 Lung Cancer samples are paired with each normal(Saliva derived for control) sequencing data.The results of this WGS study were analyzed by Mutect and GATK for ranking germline variants and cancer variants to make mutational profile matrix.

  Study EGAS00001001474

• 2018_ETO_WGS

  This study includes 12 paired samples of Korean AML-ETO paitients.12 AML-ETO tumor samples are paired with each normal(Saliva or BM derived) sequencing data.The results of this WGS study were analyzed by Mutect and GATK for ranking germline variants and cancer variants to make mutational profile matrix.

  Study EGAS00001002804

• Korean Lung Cancer - 36 pair WES data

  This study includes 36 paired samples of Korean Lung Cancer paitients.36 Lung Cnacer samples are paired with each normal(Saliva derived for control) sequencing data.The results of this WES study were analyzed by Mutect and GATK for ranking germline variants and cancer variants to make mutational profile matrix.

  Study EGAS00001002843

• High-resolution analyses of human sperm dynamic methylome reveals thousands of novel age-related epigenetic alterations

  Age-dependent modifications of the germ cells epigenome remain poorly understood. Our objective was to assess the DNA methylation profile of human spermatozoa during aging. A cohort study was designed to investigate the effects of age and fertility status on sperm DNA methylation.

  Study EGAS00001004168

• 2015_AML_ETO

  This study includes 10 paired samples of 2015 Korean AML-ETO paitients.10 AML-ETO tumor samples are paired with each normal(Saliva or BM derived) sequencing data.The results of this WGS study were analyzed by Mutect and GATK for ranking germline variants and cancer variants to make mutational profile matrix.

  Study EGAS00001002897

• 2015_AML_ETO_WGS_additional

  This study includes 2 paired samples of 2015 Korean AML-ETO paitients. 2 AML-ETO tumor samples are paired with each normal(Saliva or BM derived) sequencing data.The results of this WGS study were analyzed by Mutect and GATK for ranking germline variants and cancer variants to make mutational profile matrix.

  Study EGAS00001002898

• Transcriptomic and Clonal Characterization of T Cells in the Human Central Nervous System

  The cerebrospinal fluid (CSF) is thought to be a main route for immune surveillance in the central nervous system (CNS). Understanding the composition and state of CSF in healthy individuals may provide insight into perturbations present during neuroinflammation. Here, we have used single-cell RNA and TCR sequencing to profile CSF and peripheral blood mononuclear cells (PBMCs) from healthy individuals and patients with relapsing-remitting multiple sclerosis (MS), a chronic autoimmmune disease. In addition, with the goal of understanding how transcriptional artefacts are introduced in transcriptomics experiments, we have performed single-cell and TCR sequencing to profile PBMCs from a healthy individual that were processed with the same enzymatic digestion used for tissues (such as the brain) in the presence or absence of transcription inhibitors. 

  Study phs002222