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

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• Tam-Seq of HGSOC samples for fixative comparison study

  Targeted amplicon sequencing of samples as part of the study "Methanol-based fixation is superior to buffered formalin for next-generation sequencing of DNA from clinical cancer samples. The amplicon panel consists of 48 amplicons in TP53, PTEN, EGFR, PIK3CA, KRAS and BRAF genes as described previously [Forshew, STM 2012]. All libraries were pooled and quantify using DNA 1000 kit on Agilent 2100 Bioanalyzer and KAPA SYBR FAST ABI Prism qPCR Kit (KAPA Biosystems) on 7900HT Fast Real-Time PCR System (Applied Biosystems) according to the supplier's recommendations. Reads were aligned using bwa-mem v0.7.12-r1039 to the 1000 genomes version of human genome build GRCh37, retaining duplicate reads.

  Dataset EGAD00001001937

• Genetic Studies in the Hutterites

  We conducted genetic studies of disease-associated quantitative phenotypes, including microbiome and gene expression studies, and common diseases, such as asthma and Alzheimer's disease, by genotyping and/or sequencing in the Hutterites, a founder population of European descent. The Hutterites who have participated in our studies live on communal farms in South Dakota and are related to each other through multiple lines of descent in a 3,657-person, 13-generation pedigree with 64 founders. The small number of founding genomes reduces genetic heterogeneity whereas their communal lifestyle ensures that non-genetic factors are remarkably uniform between individuals. Our sample includes >1,600 subjects who have participated in our studies of fertility (since 1982), asthma, cardiovascular disease and other complex phenotypes (since 1993), microbiome studies (since 2011), and/or immune response (since 2012). The variable 'Total number of consented subjects' reflects the count of subjects with individual level phenotype and genotype data in dbGaP.

  Study phs000185

• Chordoma_Sequencing_Project_Whole_Genome

  This is a continuation of the Chordoma Sequencing Project, prelim #G0175-122-CF. All cancers arise due to somatically acquired abnormalities in DNA sequence. Systematic sequencing of cancer genomes allows acquisition of complete catalogues of all classes of somatic mutation present in cancer. These mutation catalogues will allow identification of the somatically mutated cancer genes that are operative and characterise patterns of somatic mutation that may reflect previous exogenous and endogenous mutagenic exposures. In this application, we aim to perform whole genome sequencing on 10 chordoma matched genome pairs. The Chordoma Foundation will fund the RNA Sequencing/Methylation and SNP6 costs for this project while the whole genome and library sequencing will be covered under the CGP, 2012-2013 core WTSI internal funding. An additional sequencing of three cancer cell lines will be added to this work, financed by the Chordoma Foundation. In this project, the Chordoma foundation will pay for the additional costs of methylation, RNA Seq,

  Study EGAS00001000409

• Genomic data from analysis of the human placenta, part of the Pregnancy Outcome Prediction study (POPs)

  The Pregnancy Outcome Prediction (POP) study is a prospective cohort study of nulliparous women attending the Rosie Hospital (Cambridge, UK) for their dating ultrasound scan. The study included 4512 women with a viable singleton pregnancy; study participants provided written informed consent and were recruited between January 2008 and July 2012. The POP study aimed both at evaluating performance of known biomarkers and serial ultrasonography in assessing maternal and fetal well-being, as well as identifying novel biomarkers. The study is sufficiently large to be powered for relatively uncommon adverse pregnancy outcomes. Women attended four study visits scheduled every 8 weeks, starting with the first trimester. Participants had blood taken during the dating/recruitment visit (at approximately 12 weeks gestation (wkGA)), as well as at three subsequent visits (at ∼20wkGA, ∼28wkGA and ∼36wkGA). For more detail, please visit: https://www.obgyn.cam.ac.uk/research/pops-2/.

  Study EGAS00001002205

• Northern Ireland COhort for the Longitudinal study of Ageing

  The Northern Ireland COhort for the Longitudinal study of Ageing (NICOLA) is a representative sample of ~8,500 people from across Northern Ireland. The study, which was set up in 2012, aims to understand what it is like to grow older in Northern Ireland. • NICOLA has a strong focus on molecular biomarkers so there is complementary genetic, epigenetic and transcriptomic data available for a subset of individuals. • We inherit much of our DNA from our parents while a small amount of this material changes as we get older. In NICOLA we have 551,839 directly genotyped and 18,148,478 imputed Single Nucleotide Polymorphisms (SNPs) currently available for 2969 participants. • Summary statistics for the association of these gene polymorphisms with ~30 phenotypes were generated. • Epigenetics provides a link between our inherited DNA and environmental influences from a person’s diet, medication and lifestyle. NICOLA has the epigenetic quality controlled profiles of 1984 individuals arising from variations in DNA methylation at 862,927 genetic sites.

  Study EGAS00001007915

• UK10K_RARE_NEUROMUSCULAR REL-2012-07-05

  UK10K_RARE_NEUROMUSCULAR REL-2012-07-05

  Dataset EGAD00001000219

• UK10K_RARE_SIR REL-2012-07-05

  UK10K_RARE_SIR REL-2012-07-05

  Dataset EGAD00001000218

• UK10K_RARE_CILIOPATHIES REL-2012-07-05

  UK10K_RARE_CILIOPATHIES REL-2012-07-05

  Dataset EGAD00001000217

• UK10K_RARE_CHD REL-2012-07-05

  UK10K_RARE_CHD REL-2012-07-05

  Dataset EGAD00001000210

• UK10K_RARE_FIND REL-2012-07-05

  UK10K_RARE_FIND REL-2012-07-05

  Dataset EGAD00001000209

• UK10K_RARE_THYROID REL-2012-07-05

  UK10K_RARE_THYROID REL-2012-07-05

  Dataset EGAD00001000208

• UK10K_RARE_HYPERCHOL REL-2012-07-05

  UK10K_RARE_HYPERCHOL REL-2012-07-05

  Dataset EGAD00001000207

• UK10K_RARE_COLOBOMA REL-2012-07-05

  UK10K_RARE_COLOBOMA REL-2012-07-05

  Dataset EGAD00001000206

• UK10K_OBESITY_SCOOP REL-2012-02-22

  UK10K_OBESITY_SCOOP REL-2012-02-22

  Dataset EGAD00001000193

• UK10K_RARE_CHD REL-2012-02-22

  UK10K_RARE_CHD REL-2012-02-22

  Dataset EGAD00001000192

• UK10K_RARE_CILIOPATHIES REL-2012-02-22

  UK10K_RARE_CILIOPATHIES REL-2012-02-22

  Dataset EGAD00001000191

• UK10K_RARE_FIND REL-2012-02-22

  UK10K_RARE_FIND REL-2012-02-22

  Dataset EGAD00001000190

• UK10K_RARE_NEUROMUSCULAR REL-2012-02-22

  UK10K_RARE_NEUROMUSCULAR REL-2012-02-22

  Dataset EGAD00001000189

• UK10K_RARE_SIR REL-2012-02-22

  UK10K_RARE_SIR REL-2012-02-22

  Dataset EGAD00001000188

• UK10K_RARE_THYROID REL-2012-02-22

  UK10K_RARE_THYROID REL-2012-02-22

  Dataset EGAD00001000187

• UK10K_NEURO_FSZNK REL-2012-01-13

  UK10K_NEURO_FSZNK REL-2012-01-13

  Dataset EGAD00001000183

• UK10K_NEURO_UKSCZ REL-2012-01-13

  UK10K_NEURO_UKSCZ REL-2012-01-13

  Dataset EGAD00001000182

• UK10K_RARE_NEUROMUSCULAR REL-2012-01-13

  UK10K_RARE_NEUROMUSCULAR REL-2012-01-13

  Dataset EGAD00001000180

• UK10K_RARE_COLOBOMA REL-2012-01-13

  UK10K_RARE_COLOBOMA REL-2012-01-13

  Dataset EGAD00001000179

• UK10K_RARE_CHD REL-2012-01-13

  UK10K_RARE_CHD REL-2012-01-13

  Dataset EGAD00001000178

• UK10K_NEURO_ASD_FI REL-2012-01-13

  UK10K_NEURO_ASD_FI REL-2012-01-13

  Dataset EGAD00001000173

• UK10K_RARE_FIND REL-2012-01-13

  UK10K_RARE_FIND REL-2012-01-13

  Dataset EGAD00001000171

• UK10K_NEURO_MUIR REL-2012-01-13

  UK10K_NEURO_MUIR REL-2012-01-13

  Dataset EGAD00001000170

• UK10K_RARE_CILIOPATHIES REL-2012-01-13

  UK10K_RARE_CILIOPATHIES REL-2012-01-13

  Dataset EGAD00001000168

• UK10K_RARE_COLOBOMA REL-2012-02-22

  UK10K_RARE_COLOBOMA REL-2012-02-22

  Dataset EGAD00001000185

• UK10K_RARE_HYPERCHOL REL-2012-02-22

  UK10K_RARE_HYPERCHOL REL-2012-02-22

  Dataset EGAD00001000186

• UK10K_RARE_HYPERCHOL REL-2012-01-13

  UK10K_RARE_HYPERCHOL REL-2012-01-13

  Dataset EGAD00001000167

• Genomic and Transcriptomic Profile of Paired Primary-Metastasis Colorectal Tumors

  The goal of this study is to identify mechanisms of metastization in a portuguese cohort of colorectal cancer. Namely, we want to identify patterns of genomic and transcriptomic diversification associated with metastasis.

  Study EGAS00001005276

• Highly complex single-cell mixture of 5 individuals of low cell number

  Mixture of 5 unrelated individuals sequenced by 10x as a scATAC-seq with low cell count. The dataset was then processed by Cell Ranger and deconvoluted to yield each individuals genetic profile using the De-goulash pipeline. The separation file is submitted as the processed file. The bam are submitted as unprocessed files.

  Dataset EGAD50000000479

• Pediatric CNS tumor classification by DNA-methylation dataset

  In this study nanopore sequencing was applied to obtain sparse DNA methylation profiles from pediatric CNS tumor samples. A neural network was used to classify the tumor based on the obtained methylation profile.

  Dataset EGAD00010002599

• Ultra-fast deep-learned pediatric CNS tumor classification.

  In this study nanopore sequencing was applied to obtain sparse DNA methylation profiles from pediatric CNS tumor samples. A neural network was used to classify the tumor based on the obtained methylation profile.

  Dataset EGAD00001011303

• Acute myeloid leukemia bulk RNA-seq (Diagnosis and Relapse)

  To gain insight into the clonal heterogeneity of diagnosis (Dx) and relapse (Re) pairs, we employed RNA-seq to longitudinally profile two t(8;21) (AML1-ETO = RUNX1-RUNX1T1), and four FLT3-ITD AML cases. All the samples are bone marrow aspirates.

  Dataset EGAD00001008374

• Single-cell transcriptome sequencing of regulatory and conventional T cells in breast cancer patients and healthy individuals.

  Identification of tumor-specific effects on gene expression profile of regulatory T cells and conventional T cells in humans, investigation of the clonal origin of regulatory T cells and impact analysis of tumor-specific conversion of conventional T cells into induced regulatory T cells on the peripheral regulatory T cell repertoire in humans.

  Dataset EGAD00001004069

• Intercepting Progression from Pre-Invasive to Invasive Lung Adenocarcinoma

  An improved understanding of the biology of lung cancer is needed to intercept the disease at an early point in its progression. In this project we have used multidimensional methods to profile the tumor microenvironment (TME) and to determine the crosstalk between cancer cells and the TME in pre-invasive to invasive human lung non-solid adenocarcinomas. Comparative analysis of the cellular and molecular events associated with the distinct histological stages will lead to identification of the critical events triggering progression and thereby identify targets to intercept disease progression. The data being submitted represents the genomic profiles of patient samples with pre-invasive and invasive human lung adenocarcinomas.

  Study phs002818

• Maternal-Fetal Immune Responses in Preterm Labor and Congenital Anomalies

  The purpose of this study is to provide a reference profile of small extracellular RNAs in body fluids. These samples were originally obtained in a study that had a different purpose. The purpose of the original study was to learn and understand more about the causes of preterm labor, how to prevent it, and how to treat it. What the researchers learn by studying tissue, cells, and/or fluid (including blood samples, amniotic fluid, and placental tissue) may help to prevent preterm labor and prevent preterm delivery, which will improve the prenatal care women receive and improve the health of newborns.

  Study phs001693

• Single Cell RNA-Sequencing in Adenoid Cystic Carcinoma

  This study of salivary adenoid cystic carcinoma aimed to profile individual malignant and stromal cells in treatment-naive head and neck adenoid cystic carcinoma, with or without metastatic cervical lymph nodes. Clinical and pathologic information was collected on all patients, in addition to a fresh biopsy sample from the primary tumor and/or metastatic lymph node at the time of initial surgery. A fresh biopsy sample from a matched local recurrence was also collected for a single unique patient. Biopsy specimens were processed for single cell RNA-seq. A total of ~1,700 single cells from seven participants were included in the final dataset.

  Study phs003070

• BIRC5 Upregulation Enhances DNMT3A-Mutant T-ALL Cell Survival and Pathogenesis

  The goal of this study was to determine how patients with T-ALL who have DNA methyltransferase 3 alpha (DNMT3A) mutations develop resistance to therapy. Since DNMT3A is a methyltransferase, we examined the effect of those mutations on epigenetic regulation using whole genome bisulfite sequencing (WGBS). We also assessed any changes in gene expression using RNA-sequencing. We found that T-ALL patients with DNMT3A mutations are resistant to apoptosis and some chemotherapies. WGBS showed that DNMT3A mutated patients clustered together by their epigenetic profile, which was associated with hypomethylation at TERT and HOX genes. RNA sequencing identified differences in JAK/STAT signaling.

  Study phs003623

• Single-Cell Transcriptomic Characterization of Microscopic Colitis

  Patients with microscopic colitis (MC), chronic diarrhea without histological signs of MC, or unaffected controls were profiled using single-cell RNA sequencing (scRNA-seq; inDrops and 10X Genomics were used). One profiled patient without clinical symptoms was found to have histological signs of MC (asymptomatic MC). Some of the subjects from dbGaP study phs003418 are controls in this study. T-Cell Receptor sequencing (TCR-Seq) was also performed on a subset of patients. Individual transcriptomes were analyzed to characterize the cellular profile associated with MC and search for mediators of disease pathology. Raw reads and processed count matrices will be available through dbGaP.

  Study phs003876

• Circulating cell-free DNA methylation profiles as noninvasive multiple sclerosis biomarkers: A proof-of-concept study

  In chronic neurodegenerative diseases such as multiple sclerosis (MS), there is a critical unmet need for cost-effective non-invasive blood biomarkers to concurrently classify disease subtypes, monitor disability severity, and predict long-term progression. In this proof-of-concept study, we performed low-coverage whole-genome bisulfite sequencing (WGBS) on 75 plasma cell-free DNA (cfDNA) samples collected from a well-characterized real-world prospective clinic cohort with longitudinal disability outcome measurements. We assessed the clinical utility of cfDNA methylation profile for differentiating MS patients from non-MS controls, classifying MS subtypes, estimating disability severity, and predicting disease trajectories.

  Study EGAS50000001277

• North American Brain Expression Consortium (NABEC) Exome Sequencing

  A fundamental challenge in the post-genome era is to understand and annotate the consequences of genetic variation, particularly within the context of human tissues. We describe a set of integrated experiments designed to investigate the effects of common genetic variability on mRNA expression distinct human brain regions. We show that brain tissues may be readily distinguished based on expression profile. We find an abundance of genetic cis regulation mRNA expression. We observe that the largest magnitude effects occur across distinct brain regions. We believe these data, which we have made publicly available, will be useful in understanding the biological effects of genetic variation.

  Study EGAS00001002110

• Meisal temporal lobe epilepsy sequencing study

  Our understanding of mesial temporal lobe epilepsy (MTLE) is one of the most common forms of drug-resistant epilepsy in humans. Using RNA- and small RNA-sequencing in parallel, we explored differentially expressed genes in the hippocampus and cortex of MTLE patients who had undergone surgical resection and non-epileptic controls. We found significant enrichment for astrocytic and microglial genes amongst up-regulated genes and down-regulation of neuron-specific genes in the hippocampus of MTLE patients. The transcriptome profile of the small RNAs reflected disease state more robustly than mRNAs, even across brain regions which show very little pathology.

  Study EGAS00001003922

• DNTR sequencing data of paediatric acute lymphoblastic leukemia

  This study used the DNTR-seq method in leukaemia samples to profile the whole-genome and mRNA jointly in single cells. Direct tagmentation is used in a collection of single-cell whole genome sequencing (scWGS) methods, including DNTR-seq, which provide high quality data at ultra-low to low coverage. The overall goal was to characterize the genetic and transcriptional heterogeneity of cancer samples. To infer clonal structure and evolutionary history, copy number analysis based workflows were implemented. Bone marrow mononuclear cells from pediatric acute lymphoblastic leukemia samples were FACS sorted into 384 plates to generate the DNA and RNA profiles.

  Study EGAS50000001247

• Single-cell profiling of neoantigen-specific T cells in lung cancers treated with neoadjuvant PD-1 blockade

  We study the expression profile of MANA-specific T cells, we used the MANA functional expansion of specific T cells (MANAFEST) assay in neoadjuvant anti-PD-1-treated lung cancers and applied their T cell receptor’s (TCR) complementarity-determining region 3 (CDR3) as a “barcode” to track and analyze their transcriptional programs in the tumor microenvironment using single cell TCR sequencing coupled with single cell RNA sequencing. We revealed distinct phenotype for MANA- and virus-specific clones in TIL and adjacent normal lung, regardless of response. MANA-specific T cells show features that drive the differences between responders and non-responders.

  Study EGAS00001005343

• Integration of Clinical and Molecular Biomarkers for Melanoma Survival (Berwick)

  The long-term goal of the InterMEL Program Project: Integration of Clinical and Molecular Biomarkers for Melanoma Survival is to identify molecular and clinical factors that predict survival of melanoma patients. Our overarching hypothesis is that we can identify factors in the primary melanoma tumor that will lead to more aggressive disease. Melanoma patients diagnosed at American Joint Committee on Cancer (AJCC) tumor, lymph nodes, and metastases (TNM) stages IIA/IIB/IIC/IIIA/IIIB/IIIC/IIID display highly variable clinical outcomes and responses to therapy. We wish to identify robust and reproducible biomarkers or sets of classifiers that distinguish patients likely to have poor prognosis. These biomarkers will help establish targets for adjuvant therapies for this set of patients before the tumors metastasize. Aim 1. Classify actionable somatic mutations, and copy number variations (CNVs) in relationship to melanoma survival. In Project 1, Targeted Sequencing and Clinicopathology to Evaluate Primary Melanoma Molecular Subtypes and Outcomes, we will profile 468 genes using the MSKIMPACT ™ assay and identify somatic mutations and CNVs associated with melanoma-specific survival, as well as their co-occurrence with other mutations, in 1,000 tumors from patients at AJCC TNM stages IIA-IIID: approximately 500 from patients who died with melanoma within five years and approximately 500 from individuals who have lived at least five years. We will also evaluate the joint effects of somatic mutations, CNVs and pathologic characteristics associated with good and poor outcomes. Aim 2. Identify primary melanoma DNA methylation profiles to evaluate subtypes and survival. Although it has been established that melanomas frequently have aberrant DNA methylation, it is unknown if DNA methylation in primary melanomas predicts outcome. In Project 2, Primary Melanoma DNA Methylation Profiling for Evaluating Subtypes and Survival, we will profile the same primary melanomas as in Project 1 with Illumina Infinium 850K methylation arrays. We expect to: identify and characterize DNA methylation-based melanoma subclasses; train, test and validate a CpG signature prognostic for survival from melanoma; determine whether this profile adds information to outcome prediction beyond AJCC TNM staging. This project is based on the hypothesis that DNA methylation in primary melanoma will define subgroups (including a poor-prognosis CIMP – ‘CpG island methylator phenotype' subtype) and that a CpG signature will be prognostic for melanoma survival. Aim 3. Define microRNA expression changes in relation to melanoma survival. MicroRNAs have been associated with poor prognosis in melanoma, as well as in other cancers. In Project 3, Prognostic and Functional Role of a Gene Expression Signature in Melanoma Patients, we hypothesize that altered miRNA expression, captured at the time of diagnosis, may contribute to the aggressive behavior of a subset of early stage primary melanomas. We will profile the same primary melanomas as in Projects 1 and 2 with a Nanostring assay. This project will define and validate a tissue-based microRNA signature in conducted to determine whether the prognostic miRNA signature, as well as other candidate genes emerging from other projects, contribute to melanoma survival. Aim 4. Integrate data from multiple platforms to identify melanoma subtypes and survival. Despite substantial literature on gene tumor mutation-, methylation- and gene expression-based prognostic and predictive signatures for melanoma, few such signatures are used in clinical practice. Project 4, Multiplatform Analysis of Melanoma Molecular Subtypes and Patient Survival Outcome, will use novel integrative clustering methods to identify molecular subtypes of melanoma jointly defined across these platforms.

  Study phs003099

• Blueprint RNAseq profile of purified plasma cells from multiple myeloma patients and tonsils of healthy donors

  In the context of an epigenomic study of multiple myeloma, a have generated RNAseq profiles of purified plasma cells from 11 multiple myeloma patients and tonsils of 4 healthy donors

  Study EGAS00001001110