19232 results for "Buy fc coins Buyfc26coins.com is EA Sports official for FC 26 coins They are the best FC seller..nEoY"

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• WGS of 4 childhood T-ALL patients - tumor and remission

  Whole genome sequencing of 4 childhood T-ALL patients, which was further used in single-cell analysis in the paper "Single cell sequencing reveals the origin and the order of mutation acquisition in T-cell acute lymphoblastic leukemia".

  Dataset EGAD00001003951

• Maternal plasma data in FetalQuantSD accurate quantification of fetal DNA fraction by shallow-depth sequencing of maternal plasma DNA

  This dataset consist on 70 maternal plasma samples (bam files) used in the FetalQuantSD. The maternal plasma DNA samples were sequenced using the HiSeq 2000 platform (Illumina) with a 50-cycle paired-end mode.

  Dataset EGAD00001004324

• The polarity and specificity of antiviral T lymphocyte responses determine susceptibility to SARS-CoV-2 infection in cancer patients and healthy individuals.

  The goal of this study was to identify immune correlates of clinical protection against SARS-CoV-2 infection.

  Study EGAS00001005985

• Papuan Genomes: high depth (30x) whole genome sequence data

  This dataset includes the whole genomes, sequenced to high depth (30x) of 25 individuals from Papua New Guinea. The individuals were chosen from several geographically distinct Papuan groups, focusing on the highland regions: Bundi, Kundiawa, Mendi, Marawaka and Tari.

  Dataset EGAD00001001634

• Whole genome sequencing of matched esophageal tumor-normal samples

  The dataset includes whole genome sequencing (WGS) data on ten matched esophageal tumor-normal pairs. WGS was performed by the cancer sequencing service of CG with an average read coverage of approximately 50-fold. Illumina HiSeq2000 instrument was used to perform the sequencing.

  Dataset EGAD00001004832

• Paired-end RNA-seq analysis of the Hypermutation and Malignant Progression in Low-grade Glioma Patients

  44 DNA samples were derived from the tumors of the low grade glioma patients and sequenced using Illumina RNAseq paired-end technology. Dataset contains 44 BAM files aligned to hg19 using Tophat 2.

  Dataset EGAD00001005387

• Dnase1l3 deletion causes aberrations in length and end-motif frequencies in plasma DNA

  We showed that mice in which Dnase1l3 had been deleted showed aberrations in the fragmentation of plasma DNA. We also observed a change in the ranked frequencies of end motifs of plasma DNA caused by the Dnase1l3 deletion.

  Dataset EGAD00001005071

• Possible DNA Damage after paternal exposure to ionizing radiation in Radar technicians

  This dataset contains whole genome sequences from Illumina NovaSeq Devices sequenced at the WGGC Bonn to study effects of prolonged paternal exposure to ionizing radiation. Here we provide the reads, mapped to the hg19 reference genome of all samples.

  Dataset EGAD00001011043

• 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

• Whole-exome sequencing (WES) analysis of untreated head and neck cancer patient-derived xenografts (PDXs) matched patient tumor tissue and normal mucosa tissue.

  WES analysis was performed on untreated patient tumor/normal mucosa tissue and matched patient-derived xenograft (PDX) models of primary head and neck squamous cell carcinoma (HNSCC) to investigate the preservation of tumor-specific genomic alterations in the in vivo context.

  Study EGAS50000001622

• A single-cell atlas of meningioma.

  In this study, we examined the breadth of cell types and states in meningioma using the largest single-cell cohort of meningioma by generating more than 7.5 million total cells from meningioma and surrounding dura, profiled using single-nuclear RNA sequencing and high-resolution spatial transcriptomics.

  Study EGAS50000001589

• snRNA-seq of subcortical MS

  Single-nuclei RNA-sequencing (snRNA-seq) from subcortical white matter controls and MS lesions, specifically chronic active (CA) and chronic inactive (CI), that paired with the spatial transcriptomics from the same samples, was used to identify spatial niches and key cell interactions driving inflammation and disease progression.

  Study EGAS50000000354

• RNAseq data from 112 samples of benign or malignant ovarian tumours

  This dataset contains ~1.2 TB RNA sequencing data in fastq format from 112 samples of fresh-frozen ovarian tumours from a total of 111 women, two samples being replicates. The samples were collected from the U-CAN collection at Uppsala Biobank and include both benign (n = 18) and malignant (n = 94) tumours. The RNA sequencing samples were sequenced using paired-end sequencing (2x150 bp) on an Illumina NovaSeq 6000 instrument at the SciLifeLab National Genomics Infrastructure (NGI) in Uppsala.

  Dataset EGAD50000001521

• Phase II Trial with Correlative Genomic Analysis of Durvalumab plus Pazopanib Combination in Patients with Advanced Soft Tissue Sarcomas

  This study includes an open-label, phase 2 study to determine the activity of the anti-VEGF receptor tyrosine-kinase inhibitor, pazopanib, combined with the anti-PD-L1 immune checkpoint inhibitor, durvalumab, in unselected advanced sarcomas. We conducted whole exome and transcriptomic sequencing with pre-treatment tissue biopsy to correlate clinical outcomes with molecular and genomic biomarkers to identify patients who would most likely benefit from the combination treatment.

  Dataset EGAD50000000114

• RNA-Seq data from tumor samples collected from 12 UTSW translocation renal cell carcinoma (tRCC) patients.

  This study investigates differentially expressed genes associated with the progression of translocation renal cell carcinoma (tRCC) by analyzing RNA-Seq data from 23 tumor samples obtained from 12 patients. The samples were collected from affiliated hospitals of the University of Texas Southwestern Medical Center (UTSW), including Parkland Hospital and Children’s Medical Center. RNA isolated from tumor samples was sequenced using the Illumina platform.

  Dataset EGAD50000000172

• MassArray1-80

  234 samples genotyped at 40 loci using the MassArrayiPLEX genotyping assay using the iPLEX Gold genotyping kit (Agena Biosciences, cat. 10148-2) Gabriel et al. (2009) [Gabriel, S. , Ziaugra, L. and Tabbaa, D. (2009), SNP Genotyping Using the Sequenom MassARRAY iPLEX Platform. Current Protocols in Human Genetics, 60: 2.12.1-2.12.18. doi:10.1002/0471142905.hg0212s60]). Products were detected on a MassArray mass spectrophotometer and data were acquired in real time with MassArray RT software 4.0.0.2 (Agena Biosciences). SNP clustering and validation was carried out with Typer 4.0.26.75 software (Agena Biosciences).

  Dataset EGAD00010001906

• Clinical and genetic analysis of a rare syndrome associated with neoteny

  We describe a novel syndrome in six patients with extreme developmental delay and the defining characteristic of neoteny. In an effort to discover any genetic causes of this syndrome whole genome sequence (WGS) analysis of the patients and their families was performed on Complete Genomics’ nanoarray platform.

  Study EGAS00001002419

• H3K27ac and RNA-seq data of neuroblastoma PDXs and/or primary tumors

  This study includes H3K27ac ChIP-seq and RNA-seq data of 6 neuroblastoma PDXs. It also contains RNA-seq data of 3 pairs of neuroblastoma tumors obtained at diagnosis and relapse. The MAP-GR-B25-NB-1 PDX was derived from the relapse of pair 1.

  Study EGAS00001002505

• High_powered_complex_trait_association_mapping_through_whole_genome_sequencing_of_a_selected_subpopulation_of_the_INGI_Val_Borbera_genetic_isolate

  The VBSEQ project aims to combine available extensive genetic and phenotypic data to the latest high-throughput genome sequencing technology and ad hoc statistical analysis to identify new rare genetic variants underlying complex traits. Up to 100 Val Borbera samples will be sequenced to a 6x depth.

  Study EGAS00001000398

• Oesophageal_Adenocarcinoma_Organoid_ATAC

  ATAC Sequencing of 5 patient derived organoid cell models. Each model was derived from a piece of patient tumour taken following surgical rescetion of the tumour. All model derivations took place with the CGaP facility in Sanger. This ATAC data will be combined with other sequencing data in order to generate

  Study EGAS00001003890

• DCM-cases

  DCM-cases (149 human DCM samples) human heart biopsies from 149 patients with dilated cardiomyopathy (DCM) were subjected to RNA sequencing in order to assess transcriptome variation. We used Illumina HiSeq2000 technology. Each sample-dataset contains the output from tophat-1.4.1 (one *.bam file with the aligned reads and two *.fq files one with the not aligned forward read and one with the revers unaligned reads). We reveal extensive differences of gene expression and splicing between dilated cardiomyopathy patients and controls.

  Dataset EGAD00001003390

• DCM-controls

  DCM-controls (113 human non-DCM samples) human heart biopsies from 113 non-diseased controls were subjected to RNA sequencing in order to assess transcriptome variation. We used Illumina HiSeq2000 technology. Each sample-dataset contains the output from tophat-1.4.1 (one *.bam file with the aligned reads and two *.fq files one with the not aligned forward read and one with the revers unaligned reads). We reveal extensive differences of gene expression and splicing between dilated cardiomyopathy patients and controls.

  Dataset EGAD00001003391

• Genetic control of naive B cell receptor gene usage in celiac disease

  We have characterized the BCR repertoire of naïve B cells in 102 individuals with CeD and 102 control subjects by undertaking gene usage quantitative trait loci analyses based on BCR repertoire sequencing and single nucleotide polymorphism genotyping within the IGH, IGK and IGL loci.

  Study EGAS50000001881

• Somatic_evolution_in_the_psoriatic_skin

  We will use laser capture microdissection to dissect groups of a few hundred cells, from which we will isolate and sequence nucleic acids. We aim to whole-genome, whole-exome and RNA sequence the samples in effort to understand the accumulation of somatic mutations in psoriasis and their effect on transcription.

  Study EGAS00001004882

• Cellular composition of spheres derived from lymph nodes of lung cancer patients

  To decipher the cell type composition within single spheres we performed RNA-Seq of 25 selected spheres of 4 different categories (including 8 signature-/balanced, 9 signature+/balanced, 1 signature-/aberrant, 7 signature+/aberrant). To track the individual cell types within single spheres we performed deconvolution analysis.

  Study EGAS00001007369

• Identification of low frequency variants associated with ulcerative colitis using whole-genome sequencing

  2000 ulcerative colitis cases drawn from the UKIBD Genetics Consortium cohort and whole-genome sequenced at 2X depth. A case control association study using control samples whole-genome sequenced by UK10K will be undertaken to identify common, low-frequency and rare variants associated with ulcerative colitis. Data will be combined with similar data across 3000 Crohn's disease cases from the same cohort to identify inflammatory bowel disease (IBD) loci and better understand the genetic differences and similarities of the two common forms of IBD.

  Dataset EGAD00001000409

• Multiple myeloma Total Therapy trial patient sequencing

  DNA was obtained from either CD138+ cells from the bone marrow of multiple myeloma patients (tumor) or from stem cell harvests or peripheral blood cells from the same patient (control). 100 ng of DNA was fragmented, end-repaired, and adapters ligated using the HyperPlus kit (KAPA Biosystems). After PCR amplification the libraries were hybridized with probes against either a targeted panel consisting of 140 genes and chromosomal regions (Nimblegen) using SeqCap reagents (Nimblegen). Hybridized libraries underwent further amplification before being sequenced on a NextSeq500 (Illumina) using 75 bp paired end reads.

  Dataset EGAD00001004373

• McGill Sperm Methylome Sequencing Data

  The study includes NGS-based WGBS on one sperm DNA sample pooled from 30 participants, and methylC-capture sequencing (MCC-Seq) on the same pooled sperm sample as well as 45 sperm DNA samples derived from both fertile and infertile individuals in two cohorts (Toronto, a fertile cohort; Montreal, an idiopathic infertility cohort). All the data were generated with 100bp paired-end reads using the Illumina HiSeq2000 or 4000 systems.

  Dataset EGAD00001004978

• Metatranscriptomic Sequencing of Pulmonary Fluid in Immunocompromised Children

  Despite improved diagnostics, pulmonary pathogens in immunocompromised children frequently evade detection, leading to significant mortality. In version 1.0 of this study, we performed RNA-based next generation sequencing (mNGS) on 41 lower respiratory samples collected from 34 children. We identified a rich cross-domain pulmonary microbiome containing bacteria, fungi, RNA viruses, and DNA viruses in each patient. Potentially pathogenic bacteria were ubiquitous among samples but could be distinguished as possible causes of disease by parsing for outlier organisms. Potential pathogens were detected in half of samples previously negative by clinical diagnostics. In version 2.0, we included an addition 278 samples from 229 pediatric stem cell transplant patients with pulmonary disease.

  Study phs001684

• A73044B

  Whole genome sequencing for single cells for library A73044B 2085 cells; filetype=bam

  Dataset EGAD00001007101

• A73047D

  Whole genome sequencing for single cells for library A73047D 2091 cells; filetype=bam

  Dataset EGAD00001007102

• A95633B

  Whole genome sequencing for single cells for library A95633B 2259 cells; filetype=bam

  Dataset EGAD00001007104

• A96115A

  Whole genome sequencing for single cells for library A96115A 1635 cells; filetype=bam

  Dataset EGAD00001007111

• A96193B

  Whole genome sequencing for single cells for library A96193B 2410 cells; filetype=bam

  Dataset EGAD00001007118

• A96240B

  Whole genome sequencing for single cells for library A96240B 1683 cells; filetype=bam

  Dataset EGAD00001007122

• A95623A

  Whole genome sequencing for single cells for library A95623A 1897 cells; filetype=bam

  Dataset EGAD00001007607

• A95668B

  Whole genome sequencing for single cells for library A95668B 1905 cells; filetype=bam

  Dataset EGAD00001007609

• A95720A

  Whole genome sequencing for single cells for library A95720A 1467 cells; filetype=bam

  Dataset EGAD00001007613

• A96190A

  Whole genome sequencing for single cells for library A96190A 1833 cells; filetype=bam

  Dataset EGAD00001007620

• A96233B

  Whole genome sequencing for single cells for library A96233B 1601 cells; filetype=bam

  Dataset EGAD00001007623

• A98234B

  Whole genome sequencing for single cells for library A98234B 1600 cells; filetype=bam

  Dataset EGAD00001007627

• A98304A

  Whole genome sequencing for single cells for library A98304A 1560 cells; filetype=bam

  Dataset EGAD00001007636

• A108851B

  Whole genome sequencing for single cells for library A108851B 1681 cells; filetype=bam

  Dataset EGAD00001007596

• A108870A

  Whole genome sequencing for single cells for library A108870A 1795 cells; filetype=bam

  Dataset EGAD00001007598

• A95724B

  Whole genome sequencing for single cells for library A95724B 581 samples; filetype=bam

  Dataset EGAD00001008230

• A96172A

  Whole genome sequencing for single cells for library A96172A 1476 samples; filetype=bam

  Dataset EGAD00001008240

• A95724A

  Whole genome sequencing for single cells for library A95724A 503 samples; filetype=bam

  Dataset EGAD00001008229

• A96146A

  Whole genome sequencing for single cells for library A96146A 1195 samples; filetype=bam

  Dataset EGAD00001008233

• A96149B

  Whole genome sequencing for single cells for library A96149B 1792 samples; filetype=bam

  Dataset EGAD00001008235

• A96162B

  Whole genome sequencing for single cells for library A96162B 1316 samples; filetype=bam

  Dataset EGAD00001008238

• A96172B

  Whole genome sequencing for single cells for library A96172B 1694 samples; filetype=bam

  Dataset EGAD00001008241

• A96175C

  Whole genome sequencing for single cells for library A96175C 1473 samples; filetype=bam

  Dataset EGAD00001008243

• A96179B

  Whole genome sequencing for single cells for library A96179B 1396 samples; filetype=bam

  Dataset EGAD00001008245

• A96180B

  Whole genome sequencing for single cells for library A96180B 1189 samples; filetype=bam

  Dataset EGAD00001008246

• A96183C

  Whole genome sequencing for single cells for library A96183C 1036 samples; filetype=bam

  Dataset EGAD00001008247

• A96184A

  Whole genome sequencing for single cells for library A96184A 1733 samples; filetype=bam

  Dataset EGAD00001008248

• A96186A

  Whole genome sequencing for single cells for library A96186A 850 samples; filetype=bam

  Dataset EGAD00001008249

• A96186C

  Whole genome sequencing for single cells for library A96186C 525 samples; filetype=bam

  Dataset EGAD00001008250

• A96199B

  Whole genome sequencing for single cells for library A96199B 1170 samples; filetype=bam

  Dataset EGAD00001008251

• A96201A

  Whole genome sequencing for single cells for library A96201A 536 samples; filetype=bam

  Dataset EGAD00001008252

• A96205A

  Whole genome sequencing for single cells for library A96205A 1907 samples; filetype=bam

  Dataset EGAD00001008253

• A96210C

  Whole genome sequencing for single cells for library A96210C 1191 samples; filetype=bam

  Dataset EGAD00001008254

• A96211C

  Whole genome sequencing for single cells for library A96211C 1397 samples; filetype=bam

  Dataset EGAD00001008255

• A96215A

  Whole genome sequencing for single cells for library A96215A 1312 samples; filetype=bam

  Dataset EGAD00001008256

• A96216A

  Whole genome sequencing for single cells for library A96216A 1001 samples; filetype=bam

  Dataset EGAD00001008257

• A96220B

  Whole genome sequencing for single cells for library A96220B 1267 samples; filetype=bam

  Dataset EGAD00001008258

• A96244A

  Whole genome sequencing for single cells for library A96244A 1374 samples; filetype=bam

  Dataset EGAD00001008259

• A98176A

  Whole genome sequencing for single cells for library A98176A 1003 samples; filetype=bam

  Dataset EGAD00001008260

• A98176B

  Whole genome sequencing for single cells for library A98176B 1389 samples; filetype=bam

  Dataset EGAD00001008261

• A98284A

  Whole genome sequencing for single cells for library A98284A 1265 samples; filetype=bam

  Dataset EGAD00001008262

• A98284B

  Whole genome sequencing for single cells for library A98284B 1582 samples; filetype=bam

  Dataset EGAD00001008263

• A98289B

  Whole genome sequencing for single cells for library A98289B 1032 samples; filetype=bam

  Dataset EGAD00001008264

• A98293B

  Whole genome sequencing for single cells for library A98293B 703 samples; filetype=bam

  Dataset EGAD00001008265

• Tumour sample for patient SA667

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA667

  Dataset EGAD00001009210

• Tumour sample for patient SA668

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA668

  Dataset EGAD00001009211

• Tumour sample for patient SA669

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA669

  Dataset EGAD00001009212

• Tumour sample for patient SA671

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA671

  Dataset EGAD00001009213

• Tumour sample for patient SA672

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA672

  Dataset EGAD00001009214

• Tumour sample for patient SA535

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA535

  Dataset EGAD00001009215

• Normal sample for patient SA1035

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1035

  Dataset EGAD00001009216

• Normal sample for patient SA604

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA604

  Dataset EGAD00001009217

• Normal sample for patient SA605

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA605

  Dataset EGAD00001009218

• Normal sample for patient SA609

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA609

  Dataset EGAD00001009219

• Normal sample for patient SA218

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA218

  Dataset EGAD00001009220

• Normal sample for patient SA219

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA219

  Dataset EGAD00001009221

• Normal sample for patient SA272

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA272

  Dataset EGAD00001009222

• Normal sample for patient SA274

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA274

  Dataset EGAD00001009223

• Normal sample for patient SA275

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA275

  Dataset EGAD00001009224

• Normal sample for patient SA276

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA276

  Dataset EGAD00001009225

• Normal sample for patient SA279

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA279

  Dataset EGAD00001009226

• Normal sample for patient SA283

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA283

  Dataset EGAD00001009227

• Normal sample for patient SA287

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA287

  Dataset EGAD00001009228

• Normal sample for patient SA394

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA394

  Dataset EGAD00001009229

• Normal sample for patient SA395

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA395

  Dataset EGAD00001009230

• Normal sample for patient SA398

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA398

  Dataset EGAD00001009231

• Normal sample for patient SA402

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA402

  Dataset EGAD00001009232

• Normal sample for patient SA404

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA404

  Dataset EGAD00001009233

• Normal sample for patient SA530

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA530

  Dataset EGAD00001009234

• Normal sample for patient SA535

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA535

  Dataset EGAD00001009235

• Normal sample for patient SA585

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA585

  Dataset EGAD00001009236