525 results for "retinitis+pigmentosa+2017+surgery+blog+"my+twin+died+at+birth""

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• HipSci - Retinitis Pigmentosa - RNA Sequencing - July 2017

  HipSci - Retinitis Pigmentosa - RNA Sequencing - July 2017

  Dataset EGAD00001003542

• HipSci - Retinitis Pigmentosa - Exome Sequencing - July 2017

  HipSci - Retinitis Pigmentosa - Exome Sequencing - July 2017

  Dataset EGAD00001003527

• REL-2017-07-2030

  HipSci - Retinitis Pigmentosa - Expression Array - July 2017

  Dataset EGAD00010001388

• REL-2017-07-2015

  HipSci - Retinitis Pigmentosa - Genotyping Array - July 2017

  Dataset EGAD00010001364

• HipSci HumanHT 12 Expression BeadChip analysis - Retinitis Pigmentosa

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we performed Expression analysis using the Illumina HumanHT -12 Expression BeadChip on iPS cells generated from skin biopsies or blood samples from rare disease patients diagnosed with Retinitis Pigmentosa.

  Study EGAS00001002030

• HipSci HumanExome BeadChip analysis - Retinitis Pigmentosa

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we performed Genotyping analysis using the Infinium HumanExome BeadChip on iPS cells generated from skin biopsies or blood samples from rare disease patients diagnosed with Retinitis Pigmentosa.

  Study EGAS00001002015

• HipSci_RNASEQ_Retinitis_Pigmentosa

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we perform RNAseq on iPS lines from Retinitis Pigmentosa patients

  Study EGAS00001001996

• Whole Exome Sequencing of Spanish Patients diagnosed with rare ophtalmogenetic disorders: Macular Dystrophy, Retinitis Pigmentosa and Leber's congenital amaurosis.

  Study EGAS00001004084

• Walter and Eliza Hall Institute - University of Melbourne

  Data Access Committee for Gocuk, Lancaster et al. 2024: nanopore sequencing data of patients with choroideremia and X-linked retinitis pigmentosa, to determine X inactivation skew.

  Dac EGAC50000000301

• HipSci___Whole_Exome_sequencing___Retinitis_Pigmentosa

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we perform whole exome sequencing using Agilent whole exome pulldown method on iPS cells generated from skin biopsies or blood samples from rare disease patients diagnosed with Retinitis Pigmentosa

  Study EGAS00001001984

• Exome Sequencing of Spanish Patients with rare genetic diseases.

  Whole Exome sequencing of a set of Spanish patients suffering rare genetic diseases. The set consists of 3 patients, two were diagnosed with Aniridia (ANI-0006 and ANI-0023) and another one was diagnosed with Retinitis Pigmentosa (RP-0247).

  Dataset EGAD00001005498

• The landscape of Usher syndrome-associated transcript isoforms in the human neural retina

  Usher syndrome is an autosomal recessively inherited disorder characterized by the combination of progressive loss of visual function due to retinitis pigmentosa, sensorineural hearing loss and vestibular dysfunction in a subset of cases. Usher syndrome is clinically and genetically heterogeneous. To date, eleven genes have been identified that are associated with Usher syndrome. It is known that these genes express multiple isoforms, however, for most of the known isoforms their relative importance in the human retina is unknown. To fill this gap, using PacBio long-read mRNA sequencing we aimed to provide an overview of the Usher syndrome transcripts in the human retina.

  Study EGAS50000000504

• Whole Exome Sequencing of Spanish Patients diagnosed with rare ophtalmogenetic disorders.

  Whole Exome sequencing of a set of Spanish patients suffering rare genetic diseases. The set consists of 4 patients, one was diagnosed with Retinitis Pigmentosa (RP-1629), another one was diagnosed with Macular Dystrophy (MD-0235) and two were diagnosed with Leber's Congenital Amaurosis (LCA-0081 and LCA-0103).

  Dataset EGAD00001005746

• Exploring Extracellular Vesicle microRNAs in Usher Syndrome Type 1B: Tear-Derived EVs as Indicators of Retinal Health

  The goal of this study was to explore extracellular vesicles (EVs) from human tears and iPSC-derived RPE cells as biomarkers for Usher syndrome type 1B (USH1B), a rare inherited disorder causing deafness and retinitis pigmentosa. Researchers found that tear EVs showed higher levels and diversity of miRNAs, making them a promising non-invasive source for diagnosing USH1B. In contrast to patient-derived RPE cells, which did not express MYO7A protein despite similar expression levels in controls, the study identified specific microRNA signatures associated with retinal degeneration in both tear EVs and RPE-derived EVs. The findings suggest that tear EVs can serve as a useful biomarker for USH1B diagnosis, monitoring, and therapeutic development. Overall, this research aims to contribute to our understanding of disease mechanisms and identify potential targets for treatment in patients with Usher syndrome type 1B.

  Study EGAS50000001200

• Knee OA Functional Genomics RNAseq (2017-06-09)

  From 17 patients undergoing knee joint replacement surgery for osteoarthritis, we collected 4 samples each: intact cartilage, degraded cartilage, synovium, and meniscus. We also collected blood for DNA analysis. Multiplexed libraries were sequenced on Illumina HiSeq 2000 (75bp paired-end read length) and a cram file was produced for each sample. This dataset contains all the data available for this study on 2017-06-09.

  Dataset EGAD00001003355

• Hip OA Functional Genomics RNAseq (2017-06-09)

  From 9 patients undergoing hip joint replacement surgery for osteoarthritis, we collected 3 cartilage samples each: a low-grade sample (no obvious evidence of damage or fibrillation); a high-grade sample (damaged and fibrillated cartilage); an osteophytic sample (overlaid bony protrusions mainly around the margins of the articular surface). Multiplexed libraries were sequenced on Illumina HiSeq 2000 (75bp paired-end read length) and a cram file was produced for each sample. This dataset contains all the data available for this study on 2017-06-09.

  Dataset EGAD00001003354

• Nanopore sequencing of blood, saliva, buccal mucosa samples of patients with inherited retinal disorders

  X-linked genetic disorders typically affect females less severely than males due to the presence of a second X chromosome not carrying the deleterious variant. However, the phenotypic expression in females is highly variable, which may be explained by an allelic skew in X chromosome inactivation. Accurate measurement of X inactivation skew is crucial to understand and predict disease phenotype in carrier females, with prediction especially relevant for degenerative conditions. We propose a novel approach using nanopore sequencing to quantify skewed X inactivation accurately. By phasing sequence variants and methylation patterns, this single assay reveals the disease variant, X inactivation skew, its directionality, and is applicable to all patients and X-linked variants. Enrichment of X-chromosome reads through adaptive sampling enhances cost-efficiency. Our study includes a cohort of 16 X-linked variant carrier females affected by two X-linked inherited retinal diseases: choroideremia and RPGR-associated retinitis pigmentosa. As retinal DNA cannot be readily obtained, we instead determine the skew from peripheral samples (blood, saliva and buccal mucosa), and correlate it to phenotypic outcomes. This revealed a strong correlation between X inactivation skew and disease presentation, confirming the value in performing this assay and its potential as a way to prioritise patients for early intervention, such as gene therapy currently in clinical trials for these conditions. Our method of assessing skewed X inactivation is applicable to all long-read genomic datasets, providing insights into disease risk and severity and aiding in the development of individualised strategies for X-linked variant carrier females.

  Study EGAS50000000440

• SCANDARE TNBC transcriptomics data

  SCANDARE (NCT03017573) is a multicentric biobanking study, enrolling adult patients with newly diagnosed head and neck squamous cell carcinoma (HNSCC), triple negative breast cancer (TNBC), ovarian and cervical cancer. Tumor tissue and blood samples are collected at several time points during patient's journey, including at diagnosis, post-neoadjuvant chemotherapy in case of neoadjuvant treatment, at surgery, at recurrence and at disease progression following treatment initiated at recurrence. Since its launch in 2017 at Institut Curie, SCANDARE has enabled the longitudinal collection and preservation of samples for in-depth analyses. Here, we describe molecular alterations in 124 frozen samples (n=84 at baseline and n=40 paired at post-NAC surgery) from 91 TNBC patients using total RNAseq technology, with FASTQ files deposited in the dataset.

  Dataset EGAD50000001416

• Precision Medicine for ABCA4 Disease: Modifier Alleles

  Genetic variation affecting the structure and function of the ABCA4 protein gives rise to a broad collection of genetically and clinically heterogeneous diseases, collectively known as ABCA4 disease, which are characterized by both phenotypic overlap and variable penetrance and expressivity. These include autosomal recessive Stargardt disease, cone-rod dystrophy, occult maculopathy, bull's eye macular dystrophy, retinitis pigmentosa-like retinal dystrophy, etc. Some phenotypic variation can be attributed to variability of highly penetrant ABCA4 mutations; however, much of the heterogeneity cannot be explained by ABCA4 mutations alone. The concept of Precision Medicine requires, by definition, identification of all genetic variation contributing to specific disease phenotypes. The main goal of this study is to identify all genetic variation resulting in phenotypes compatible with ABCA4 disease, which, in addition to biallelic disease-causing variants in the ABCA4 locus, include cis- and trans-acting modifiers and mutations in genes other than ABCA4.The study was carried out by performing whole exome sequencing (WES) of affected individuals to identify causal and modifying genetic variation for patients with macular dystrophies compatible with ABCA4 disease. All samples were sequenced with the IDT's Exome Research Panel Version 1 with SeqCap EZ Exome v2 and SeqCap EZ Exome v3 capture kits. Samples were sequenced on Illumina next-generation sequencing machines (San Diego, CA, USA) using DRAGEN Bio-IT Platform v. 2.5.1 (Illumina) to align reads to the Genome Reference Consortium Human Build 37, calling variants in accordance with the Genome Analysis Tool Kit (GATK, v.4.0.2.1) Best Practices Workflow, using ATAV (v.7.0.16) variant-calling pipeline. Variants for analysis were restricted to the consensus coding sequencing public transcripts (CCDS release 20) plus 2 base pair (bp) intronic extensions. Variants were annotated using ClinEff (DnaMiner) with Ensembl-HGRCh37.73 annotations.This set of WES data from unrelated patients of different racial and ethnic backgrounds can be stored and shared through dbGaP. These data provide information on frequencies of disease-causing variants in genes other than ABCA4 in patients with macular dystrophies. These also provide frequencies of selected pathogenic and none-pathogenic variants in different ethnicities.

  Study phs002393

• SCANDARE HNSCC DNA targeted panel sequencing

  SCANDARE (NCT03017573) is a multicentric biobanking study, enrolling adult patients with newly diagnosed head and neck squamous cell carcinoma (HNSCC), triple negative breast cancer (TNBC), ovarian and cervical cancer. Tumor tissue and blood samples are collected at several time points during patient's journey, including at diagnosis, post-neoadjuvant chemotherapy in case of neoadjuvant treatment, at surgery, at recurrence and at disease progression following treatment initiated at recurrence. Since its launch in 2017 at Institut Curie, SCANDARE has enabled the longitudinal collection and preservation of samples for in-depth analyses. Here, we describe molecular alterations in 232 FFPE samples at baseline from 83 HNSCC patients using DNA targeted panel sequencing, with FASTQ files deposited in the dataset.

  Dataset EGAD50000001654

• SCANDARE HNSCC 3' Tag RNA-seq

  SCANDARE (NCT03017573) is a multicentric biobanking study, enrolling adult patients with newly diagnosed head and neck squamous cell carcinoma (HNSCC), triple negative breast cancer (TNBC), ovarian and cervical cancer. Tumor tissue and blood samples are collected at several time points during patient's journey, including at diagnosis, post-neoadjuvant chemotherapy in case of neoadjuvant treatment, at surgery, at recurrence and at disease progression following treatment initiated at recurrence. Since its launch in 2017 at Institut Curie, SCANDARE has enabled the longitudinal collection and preservation of samples for in-depth analyses. Here, we describe molecular alterations in 264 FFPE samples at baseline from 90 HNSCC patients using 3'-tag RNA-seq technology, with FASTQ files deposited in the dataset.

  Dataset EGAD50000001655

• SCANDARE TNBC WES data

  SCANDARE (NCT03017573) is a multicentric biobanking study, enrolling adult patients with newly diagnosed head and neck squamous cell carcinoma (HNSCC), triple negative breast cancer (TNBC), ovarian and cervical cancer. Tumor tissue and blood samples are collected at several time points during patient's journey, including at diagnosis, post-neoadjuvant chemotherapy in case of neoadjuvant treatment, at surgery, at recurrence and at disease progression following treatment initiated at recurrence. Since its launch in 2017 at Institut Curie, SCANDARE has enabled the longitudinal collection and preservation of samples for in-depth analyses. Here, we describe molecular alterations in 247 frozen samples at baseline and 138 germline DNA from 139 TNBC patients using WES technology, with FASTQ files deposited in the dataset.

  Dataset EGAD50000001661

• SCANDARE TNBC WGS data

  SCANDARE (NCT03017573) is a multicentric biobanking study, enrolling adult patients with newly diagnosed head and neck squamous cell carcinoma (HNSCC), triple negative breast cancer (TNBC), ovarian and cervical cancer. Tumor tissue and blood samples are collected at several time points during patient's journey, including at diagnosis, post-neoadjuvant chemotherapy in case of neoadjuvant treatment, at surgery, at recurrence and at disease progression following treatment initiated at recurrence. Since its launch in 2017 at Institut Curie, SCANDARE has enabled the longitudinal collection and preservation of samples for in-depth analyses. Here, we describe molecular alterations in 108 FFPE samples at baseline and 108 germline DNA from 108 TNBC patients using WGS technology, with FASTQ files deposited in the dataset.

  Dataset EGAD50000001662

• SCANDARE TNBC shallow WGS data

  SCANDARE (NCT03017573) is a multicentric biobanking study, enrolling adult patients with newly diagnosed head and neck squamous cell carcinoma (HNSCC), triple negative breast cancer (TNBC), ovarian and cervical cancer. Tumor tissue and blood samples are collected at several time points during patient's journey, including at diagnosis, post-neoadjuvant chemotherapy in case of neoadjuvant treatment, at surgery, at recurrence and at disease progression following treatment initiated at recurrence. Since its launch in 2017 at Institut Curie, SCANDARE has enabled the longitudinal collection and preservation of samples for in-depth analyses. Here, we describe molecular alterations in 251 frozen samples at baseline from 143 TNBC patients using shallow WGS technology, with FASTQ files deposited in the dataset.

  Dataset EGAD50000001849

• GCAT | Genomes for life

  The GCAT project is a prospective cohort study that was designed to recruit the general population of Catalonia, the north-east region of Spain. This study is a long-term genomic, environmental and lifestyle cohort project that aims to evaluate and track multiple pathologies as well as biologically related traits. By the end of 2017, the GCAT Study had recruited a total of 20 000 participants aged 40–65 years. Participants who agreed to take part in the study completed a self-administered computer-driven questionnaire, and underwent blood pressure, cardiac frequency and anthropometry measurements. For each participant, blood plasma, blood serum and white blood cells are collected at baseline. The GCAT Study has access to the electronic health records of the Catalan Public Healthcare System. Participants are followed biannually for/during, at least, 20 years after recruitment. Therefore, the GCAT Study offers a unique opportunity to integrate diverse data to allow the identification of novel relations among different biomarkers and conditions. Results may lead to the development of new genetic, genomic, epigenomic and proteomic diagnoses and screening tests, as well as new public health recommendations. The only currently available population-based prospective cohort study in Spain to the date, including more than 4899 genotyped participants and 800 whole genome sequences is now stored in the EGA archive under accession id EGAS00001003018.

  Blog gcat-genomes-for-life

• Region-specific Transcriptome Analysis of the Human Retina and Retinal Pigment Epithelium (RPE)/Choroid

  Proper spatial differentiation of retinal cell types is necessary for normal human vision. Many retinal diseases, such as Best disease and male germ cell associated kinase (MAK)-associated retinitis pigmentosa, preferentially affect distinct topographic regions of the retina. While much is known about the distribution of cell types in the retina, the distribution of molecular components across the posterior pole of the eye has not been well-studied. To investigate regional difference in molecular composition of ocular tissues, we assessed differential gene expression across the temporal, macular, and nasal retina and retinal pigment epithelium (RPE)/choroid of human eyes using RNA-Seq. RNA from temporal, macular, and nasal retina and RPE/choroid from four human donor eyes was extracted, poly-A selected, fragmented, and sequenced as 100 bp read pairs. Digital read files were mapped to the human genome and analyzed for differential expression using the Tuxedo software suite. Retina and RPE/choroid samples were clearly distinguishable at the transcriptome level. Numerous transcription factors were differentially expressed between regions of the retina and RPE/choroid. Photoreceptor-specific genes were enriched in the peripheral samples, while ganglion cell and amacrine cell genes were enriched in the macula. Within the RPE/choroid, RPE-specific genes were upregulated at the periphery while endothelium associated genes were upregulated in the macula. Consistent with previous studies, BEST1 expression was lower in macular than extramacular regions. The MAK gene was expressed at lower levels in macula than in extramacular regions, but did not exhibit a significant difference between nasal and temporal retina. The regional molecular distinction is greatest between macula and periphery and decreases between different peripheral regions within a tissue. Datasets such as these can be used to prioritize candidate genes for possible involvement in retinal diseases with regional phenotypes. Reprinted from Whitmore, S.S., Wagner, A.H., DeLuca, A.P., Drack, A.V., Stone, E.M., Tucker, B.A., Zeng, S., Braun, T.A., Mullins, R.F., Scheetz, T.E., 2014. Transcriptomic analysis across nasal, temporal, and macular regions of human neural retina and RPE/choroid by RNA-Seq. Experimental Eye Research. Used under Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported license. Additional RNA sequencing was performed on temporal, macular, nasal, inferior, and superior retina from a fifth subject and is included in this dataset. See original publication for details.

  Study phs001151

• SCANDARE ovarian WES data

  SCANDARE (NCT03017573) is a multicentric biobanking study, enrolling adult patients with newly diagnosed head and neck squamous cell carcinoma (HNSCC), triple negative breast cancer (TNBC), ovarian and cervical cancer. Tumor tissue and blood samples are collected at several time points during patient's journey, including at diagnosis, post-neoadjuvant chemotherapy in case of neoadjuvant treatment, at surgery, at recurrence and at disease progression following treatment initiated at recurrence. Since its launch in 2017 at Institut Curie, SCANDARE has enabled the longitudinal collection and preservation of samples for in-depth analyses. Here, we describe molecular alterations in 91 frozen samples (n = 53 at baseline, n = 31 Post-NAC, n= 7 Recurrence, and n = 62 germline DNA) from 64 ovarian cancer patients using WES technology, with FASTQ files deposited in the dataset.

  Dataset EGAD50000001658

• DEEP IHEC release 2017

  Raw data files for DEEP's IHEC/EpiRR submission of 2017. metadata available at: http://deep.dkfz.de/#/experiments

  Study EGAS00001002655

• REL-2017-07-2022

  HipSci - Kabuki Syndrome - Expression Array - July 2017

  Dataset EGAD00010001372

• REL-2017-07-2023

  HipSci - Usher Syndrome - Expression Array - July 2017

  Dataset EGAD00010001374

• REL-2017-07-2024

  HipSci - Alport Syndrome - Expression Array - July 2017

  Dataset EGAD00010001376

• REL-2017-07-2026

  HipSci - Hypertrophic Cardiomyopathy - Expression Array - July 2017

  Dataset EGAD00010001380

• REL-2017-07_867

  HipSci - Healthy Normals - Expression Array - July 2017

  Dataset EGAD00010001330

• REL-2017-07-1277

  HipSci - Monogenic Diabetes - Expression Array - July 2017

  Dataset EGAD00010001342

• REL-2017-07-2025

  HipSci - Congenital Hyperinsulinia - Expression Array - July 2017

  Dataset EGAD00010001378

• REL-2017-07-2029

  HipSci - Macular Dystrophy - Expression Array - July 2017

  Dataset EGAD00010001386

• REL-2017-07-2031

  HipSci - Battens Disease - Expression Array - July 2017

  Dataset EGAD00010001390

• REL-2017-07-2020

  HipSci - Hereditary Cerebellar Ataxias - Expression Array - July 2017

  Dataset EGAD00010001368

• REL-2017-07-2027

  HipSci - Primary Immune Deficiency - Expression Array - July 2017

  Dataset EGAD00010001382

• REL-2017-07-2021

  HipSci - Hereditary Spastic Paraplegia - Expression Array - July 2017

  Dataset EGAD00010001370

• REL-2017-07-1276

  HipSci - Bardet-Biedl Syndrome - Expression Array - July 2017

  Dataset EGAD00010001340

• REL-2017-07-2028

  HipSci - Bleeding and Platelet Disorders - Expression Array - July 2017

  Dataset EGAD00010001384

• REL-2017-07-2016

  HipSci - Battens Disease - Genotyping Array - July 2017

  Dataset EGAD00010001366

• REL-2017-07-2007

  HipSci - Kabuki Syndrome - Genotyping Array - July 2017

  Dataset EGAD00010001348

• REL-2017-07-2008

  HipSci - Usher Syndrome - Genotyping Array - July 2017

  Dataset EGAD00010001350

• REL-2017-07-2009

  HipSci - Alport Syndrome - Genotyping Array - July 2017

  Dataset EGAD00010001352

• REL-2017-07-2010

  HipSci - Congenital Hyperinsulinia - Genotyping Array - July 2017

  Dataset EGAD00010001354

• REL-2017-07-07

  HipSci - Hypertrophic Cardiomyopathy - Genotyping Array - July 2017

  Dataset EGAD00010001356

• REL-2017-07-2014

  HipSci - Macular Dystrophy - Genotyping Array - July 2017

  Dataset EGAD00010001362

• PAGE2 Dataset Nov 2017 (Ref: PAGE2 GIM 2018)

  PAGE2 Dataset Nov 2017 (Ref: PAGE2 GIM 2018)

  Dataset EGAD00001004843

• PAGE2 Dataset Nov 2017 (Ref: PAGE2 GIM 2018)

  PAGE2 Dataset Nov 2017 (Ref: PAGE2 GIM 2018)

  Dataset EGAD00001004842

• PAGE2 Dataset Nov 2017 (Ref: PAGE2 GIM 2018)

  PAGE2 Dataset Nov 2017 (Ref: PAGE2 GIM 2018)

  Dataset EGAD00001004844

• REL-2017-07-1273

  HipSci - Monogenic Diabetes - Genotyping Array - July 2017

  Dataset EGAD00010001334

• REL-2017-07-2005

  HipSci - Hereditary Cerebellar Ataxias - Genotyping Array - July 2017

  Dataset EGAD00010001344

• REL-2017-07-2006

  HipSci - Hereditary Spastic Paraplegia - Genotyping Array - July 2017

  Dataset EGAD00010001346

• REL-2017-07-2012

  HipSci - Primary Immune Deficiency - Genotyping Array - July 2017

  Dataset EGAD00010001358

• REL-2017-07-1272

  HipSci - Bardet-Biedl Syndrome - Genotyping Array - July 2017

  Dataset EGAD00010001332

• REL-2017-07-2013

  HipSci - Bleeding and Platelet Disorders - Genotyping Array - July 2017

  Dataset EGAD00010001360

• REL-2017-07_866

  HipSci - Healthy Normals - Genotyping Array - July 2017

  Dataset EGAD00010001328

• HipSci - Congenital Hyperinsulinia - RNA Sequencing - July 2017

  HipSci - Congenital Hyperinsulinia - RNA Sequencing - July 2017

  Dataset EGAD00001003534

• HipSci - Congenital Hyperinsulinia - Exome Sequencing - July 2017

  HipSci - Congenital Hyperinsulinia - Exome Sequencing - July 2017

  Dataset EGAD00001003520

• HipSci - Usher Syndrome - Exome Sequencing - July 2017

  HipSci - Usher Syndrome - Exome Sequencing - July 2017

  Dataset EGAD00001003528

• HipSci - Hypertrophic Cardiomyopathy - Exome Sequencing - July 2017

  HipSci - Hypertrophic Cardiomyopathy - Exome Sequencing - July 2017

  Dataset EGAD00001003523

• HipSci - Battens Disease - Exome Sequencing - July 2017

  HipSci - Battens Disease - Exome Sequencing - July 2017

  Dataset EGAD00001003518

• HipSci - Kabuki Syndrome - Exome Sequencing - July 2017

  HipSci - Kabuki Syndrome - Exome Sequencing - July 2017

  Dataset EGAD00001003524

• HipSci - Battens Disease - RNA Sequencing - July 2017

  HipSci - Battens Disease - RNA Sequencing - July 2017

  Dataset EGAD00001003533

• HipSci - Hypertrophic Cardiomyopathy - RNA Sequencing - July 2017

  HipSci - Hypertrophic Cardiomyopathy - RNA Sequencing - July 2017

  Dataset EGAD00001003540

• HipSci - Macular Dystrophy - RNA Sequencing - July 2017

  HipSci - Macular Dystrophy - RNA Sequencing - July 2017

  Dataset EGAD00001003541

• HipSci - Usher Syndrome - RNA Sequencing - July 2017

  HipSci - Usher Syndrome - RNA Sequencing - July 2017

  Dataset EGAD00001003543

• HipSci - Kabuki Syndrome - RNA Sequencing - July 2017

  HipSci - Kabuki Syndrome - RNA Sequencing - July 2017

  Dataset EGAD00001003535

• HipSci - Alport Syndrome - Exome Sequencing - July 2017

  HipSci - Alport Syndrome - Exome Sequencing - July 2017

  Dataset EGAD00001003517

• HipSci - Alport Syndrome - RNA Sequencing - July 2017

  HipSci - Alport Syndrome - RNA Sequencing - July 2017

  Dataset EGAD00001003532

• HipSci - Macular Dystrophy - Exome Sequencing - July 2017

  HipSci - Macular Dystrophy - Exome Sequencing - July 2017

  Dataset EGAD00001003525

• HipSci - Hereditary Cerebellar Ataxias - Exome Sequencing - July 2017

  HipSci - Hereditary Cerebellar Ataxias - Exome Sequencing - July 2017

  Dataset EGAD00001003521

• HipSci - Primary Immune Deficiency - Exome Sequencing - July 2017

  HipSci - Primary Immune Deficiency - Exome Sequencing - July 2017

  Dataset EGAD00001003526

• HipSci - Primary Immune Deficiency - RNA Sequencing - July 2017

  HipSci - Primary Immune Deficiency - RNA Sequencing - July 2017

  Dataset EGAD00001003536

• HipSci - Hereditary Spastic Paraplegia - RNA Sequencing - July 2017

  HipSci - Hereditary Spastic Paraplegia - RNA Sequencing - July 2017

  Dataset EGAD00001003537

• HipSci - Hereditary Cerebellar Ataxias - RNA Sequencing - July 2017

  HipSci - Hereditary Cerebellar Ataxias - RNA Sequencing - July 2017

  Dataset EGAD00001003538

• HipSci - Hereditary Spastic Paraplegia - Exome Sequencing - July 2017

  HipSci - Hereditary Spastic Paraplegia - Exome Sequencing - July 2017

  Dataset EGAD00001003522

• HipSci - Monogenic Diabetes - Exome Sequencing - July 2017

  HipSci - Monogenic Diabetes - Exome Sequencing - July 2017

  Dataset EGAD00001003516

• HipSci - Monogenic Diabetes - RNA Sequencing - July 2017

  HipSci - Monogenic Diabetes - RNA Sequencing - July 2017

  Dataset EGAD00001003530

• HipSci - Bleeding and Platelet Disorders - RNA Sequencing - July 2017

  HipSci - Bleeding and Platelet Disorders - RNA Sequencing - July 2017

  Dataset EGAD00001003539

• HipSci - Bleeding and Platelet Disorders - Exome Sequencing - July 2017

  HipSci - Bleeding and Platelet Disorders - Exome Sequencing - July 2017

  Dataset EGAD00001003519

• HipSci - Bardet-Biedl Syndrome - Exome Sequencing - July 2017

  HipSci - Bardet-Biedl Syndrome - Exome Sequencing - July 2017

  Dataset EGAD00001003515

• HipSci - Bardet-Biedl Syndrome - RNA Sequencing - July 2017

  HipSci - Bardet-Biedl Syndrome - RNA Sequencing - July 2017

  Dataset EGAD00001003531

• HipSci - Healthy Normals - Exome Sequencing - July 2017

  HipSci - Healthy Normals - Exome Sequencing - July 2017

  Dataset EGAD00001003514

• TGS - Comprehensive Molecular Characterization of Colorectal Cancer Metastases [MOSAIC] (2017-05-04)

  This dataset contains all the data available for this study on 2017-05-04.

  Dataset EGAD00001003321

• HipSci - Healthy Normals - RNA Sequencing - July 2017

  HipSci - Healthy Normals - RNA Sequencing - July 2017

  Dataset EGAD00001003529

• TRACERx 100: metastatic samples

  Whole exome sequencing of 10 metastatic biopsies from four TRACERx100 patients (see EGA dataset EGAS00001002247), collected either after relapse or death. The data from these samples are initially published with Abbosh, C. et al. Phylogenetic ctDNA analysis depicts early stage lung cancer evolution. Nature http://dx.doi.org/10.1038/nature22364 (2017). Abstract: Earlier detection of relapse following primary surgery for non-small cell lung cancer and the characterization of emerging subclones seeding metastatic sites might offer new therapeutic approaches to limit tumor recurrence. The potential to non-invasively track tumor evolutionary dynamics in ctDNA of early-stage lung cancer is not established. Here we conduct a patient-specific approach to ctDNA profiling in the first 100 lung TRACERx (TRAcking Cancer Evolution through therapy (Rx)) study participants, including one patient co-recruited to the PEACE (Posthumous Evaluation of Advanced Cancer Environment) post-mortem study. We identify independent predictors of ctDNA release in early-stage non-small cell lung cancer and perform tumor volume limit of detection analyses. Through blinded profiling of post-operative plasma, we observe evidence of adjuvant chemotherapy resistance and identify patients destined to experience recurrence of their lung cancer. Finally, we show that phylogenetic ctDNA profiling tracks the subclonal nature of lung cancer relapse and metastases, providing a new approach for ctDNA driven therapeutic studies.

  Study EGAS00001002415

• TSG knock-out in hiPSCs (2017-08-10)

  We will perform RNAseq to evaluate the effects of the loss of a list of TSGs on the transcriptome. This dataset contains all the data available for this study on 2017-08-10.

  Dataset EGAD00001003556

• Validation for human early embryonic substitutions (2017-05-11)

  PCR and MiSeq validation for early embryonic substitution candidates from 400 Breast cancer patients This dataset contains all the data available for this study on 2017-05-11.

  Dataset EGAD00001003332

• RNAseq - Colorectal organoids and tumoroids (2017-05-04)

  Transcriptome sequencing of tumour tissue, adjacent normal tissue and derived organoids/tumoroids from colorectal cancer This dataset contains all the data available for this study on 2017-05-04.

  Dataset EGAD00001003320

• Mutational Analysis of Colorectal PDX models (2017-05-11)

  Targeted exome sequencing of patient derived xenografts from primary colorectal tumours and liver metastases. This dataset contains all the data available for this study on 2017-05-11.

  Dataset EGAD00001003334

• DEEP-IHEC-release-2017

  Raw data files for the German Epigenome Project (DEEP), IHEC/EpiRR submission of 2017. metadata available at: http://deep.dkfz.de/#/experiments

  Dataset EGAD00001003974

• Correlates of Human Nerve Repair

  This is a longitudinal prospective cohort study in patients with carpal tunnel syndrome undergoing decompression surgery. Phenotypic data and skin biopsies were collected before and 6 months after surgery to determine molecular and cellular correlates associated with neural regeneration and neuropathic pain. RNA sequencing was performed in the skin samples and differential gene expression was determined post compared to pre surgery. The molecular changes identified in skin were correlated with the clinical phenotype representing neural regeneration.

  Study phs001796

• ESGI - Whole Genome Sequencing of samples from the Croatian isolated populations (2017-11-22)

  Whole genome sequencing of sampels from isolated populations from Croatia. The samples are sequenced using the Illumina HiSeq X Ten system. This dataset contains all the data available for this study on 2017-11-22.

  Dataset EGAD00001003812

• Metastatic breast cancer targeted gene screen (2017-05-11)

  The samples will be sequenced for a targeted panel of cancer relevant genes (n ~ 370) and analysed for somatic mutations. This dataset contains all the data available for this study on 2017-05-11.

  Dataset EGAD00001003330

• Somatic Genetics of lesions from a POT1 patient (2017-04-27)

  In this project we will use exome sequencing to identify somatic mutations in lesions from a patient with a germline mutation in the protection of telomeres 1 gene (POT1). This dataset contains all the data available for this study on 2017-04-27.

  Dataset EGAD00001003307

• A Genomic Approach to Improved Diagnosis and Treatment of Neuroendocrine Tumors

  These are RNA-Seq samples from patients undergoing surgery for small bowel and pancreatic neuroendocrine tumors. Normal tissue, primary tumors, lymph nodes, and liver metastases were collected at surgery and stored in RNAlater until RNA extraction was carried out for RNA-Seq.

  Study phs001772

• Study of tumor RNA expression differences between treated and untreated PitNET patients

  The goal of the study is to evaluate response of PitNET to drug therapy before surgery. Patients with and without drug therapy are compared in RNA level. The RNA is extracted from surgery material, sequenced and deferentially expressed genes (DEG) determined.

  Study EGAS00001004736