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• Paired RNA-Seq for Sarcoma tumors

  Paired RNA-Seq of 199 samples of Sarcoma tumors. The sequencing was done mostly on HiSeq 4000 with Illumina TruSeq Stranded mRNA, ist was also done on NovaSeq 6000 using the same kit. Very few samples were sequenced on HiSeq X Ten with Illumina TruSeq RNA or Illumina TruSeq Stranded mRNA.

  Dataset EGAD00001010256

• RNAseq and ATACseq data

  RNAseq and ATACseq data for the FMF patients and healthy control. The RNAseq data was sequenced on a BGI MGI G400 machine, with PE100 reads. ATAC-seq libraries were prepared with Illumina Nextera primers and sequenced on NovaSeq 6000 platform with 50bp paired-end sequencing, where each sample was sequenced to approximate 60 million reads.

  Dataset EGAD00001010304

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0142_004

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0142_004 for Triple negative breast cancer sample SA1035X6XB03209

  Dataset EGAD00001011243

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0162_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0162_002 for Triple negative breast cancer sample SA1035X7XB03502

  Dataset EGAD00001011246

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0162_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0162_001 for Triple negative breast cancer sample SA1035X8XB03420

  Dataset EGAD00001011248

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0164_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0164_002 for Triple negative breast cancer sample SA530X3XB03295

  Dataset EGAD00001011250

• Sequencing data for oesophageal and related samples - Black et al (WGS)

  Data supporting: "Understanding the malignant potential of gastric metaplasia of the oesophagus and its relevance to Barrett’s Oesophagus surveillance: individual-level data analysis" Black et al (WGS BOs/normals)

  Dataset EGAD00001011255

• scRNA-seq, WES, and bulk RNA-seq on longitudinal samples from 7 Lymphoma patients treated with CD20xCD3 bispecific antibodies

  We performed scRNA-seq on 15 fresh lymph node core biopsies from 7 Lymphoma patients treated with CD20xCD3 bispecific antibodies. We also performed whole-exome sequencing (WES) and bulk RNA-seq on formalin-fixed paraffin embedded (FFPE) tumor samples from these patients. WES was additionally performed on matched germline samples (blood) for each patient.

  Dataset EGAD00001011350

• WES raw data set for the study "Genomic profiling of localized (lFL) and systemic follicular lymphoma (sFL) reveals novel insights into FL pathogenesis"

  221 patient samples including 164 initial tumor (TI) samples (53/164 fresh frozen TI samples, and 111/164 formalin-fixed paraffin-embedded (FFPE) TI samples), 22 paired matched normal samples, and 35 unpaired normal samples from healthy donors; FASTQ file format, Agilent SureSelect Human All Exon V6 Kit (Agilent Technologies, Inc., Santa Clara, California, USA)

  Dataset EGAD00001011369

• BLUEPRINT September 2016, ChIPmentation Burkitt Lymphoma from lymph node, on Genome GRCh38

  ChIPmentation data for 3 sample(s) Burkitt Lymphoma from lymph node, on Genome GRCh38. 10 run(s), 8 experiment(s), 8 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002939

• BLUEPRINT September 2016, ChIPmentation Lymphoma_Follicular from lymph node, on Genome GRCh38

  ChIPmentation data for 3 sample(s) Lymphoma_Follicular from lymph node, on Genome GRCh38. 7 run(s), 6 experiment(s), 6 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002931

• BLUEPRINT September 2016, ChIPmentation Acute Lymphocytic Leukemia from bone marrow, on Genome GRCh38

  ChIPmentation data for 1 sample(s) Acute Lymphocytic Leukemia from bone marrow, on Genome GRCh38. 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002930

• V2 Colorectal panel test

  Targeted gene screen of cell line tumour samples for testing the new V2 Colorectal gene panel.

  Dataset EGAD00001003253

• ICGC PCAWG Dataset: GACA-CN_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: GACA-CN.

  Dataset EGAD00001003132

• SA501X3F direct library preparation (DLP) single-cell genomes

  Microfluidic direct library preparation (DLP) single-cell whole-genome BAM files for third-passage patient-derived primary triple-negative breast cancer xenograft SA501X3F.

  Dataset EGAD00001003149

• SA501X4F direct library preparation (DLP) single-cell genomes

  Microfluidic direct library preparation (DLP) single-cell whole-genome BAM files for fourth-passage patient-derived primary triple-negative breast cancer xenograft SA501X4F.

  Dataset EGAD00001003150

• 184-hTERT-L2 direct library preparation (DLP) single-cell genomes

  Microfluidic direct library preparation (DLP) single-cell whole-genome BAM files for near-diploid immortalized breast epithelial cell line 184-hTERT-L2.

  Dataset EGAD00001003152

• Genomic Profiling of Advanced Pancreatic Cancer to inform therapy - RNA-Seq unmapped reads

  Genomics-Driven Precision Medicine for Advanced Pancreatic Cancer - Early Results from the COMPASS Trial - RNA-Seq unmapped reads

  Dataset EGAD00001003582

• Low-coverage Whole Genome Sequencing, Colorectal adenomas, NKI-AvL TGO series Stool-Proteomics

  For this tissue dataset, we applied low-pass whole genome sequencing to 98 non-advanced and advanced adenomas. As small number of lesions was sequenced multiple times, this dataset consists of 103 fastq files. These adenomas were classified as lesions with low-risk or high-risk of progression, according to the presence of specific DNA copy number changes (Carvalho et al, CancerPrevRes, 2018).

  Dataset EGAD00001004075

• RNA sequencing of multiple tumor biopsies and patient-derived spheroids from five colorectal cancer patients (BAM files)

  Whole transcriptome, strand-specific RNA-seq libraries were prepared from total RNA purified using RNeasy mini kit (Qiagen) using Ribo-Zero technology (Epicentre, an Illumina company) for depletion of rRNA followed by library preparation using ScriptSeq ScriptSeq RNA-Seq Library preparation Kit from Illumina. The paired raw sequence reads were processed using TopHat2 and mapped to the humane reference genome HG19.

  Dataset EGAD00001003820

• NIHR BioResource Rare Diseases WGS project - Stem cell and Myeloid Disorders (SMD) Rare Disease domain

  Short read whole genome sequencing (WGS) CRAM files for the NIHR BioResource Rare Diseases WGS project – Participants from the Stem cell and Myeloid Disorders (SMD) Rare Disease domain

  Dataset EGAD00001004524

• NIHR BioResource Rare Diseases WGS project - Pulmonary Arterial Hypertension (PAH) Rare Disease domain

  Short read whole genome sequencing (WGS) CRAM files for the NIHR BioResource Rare Diseases WGS project – Participants from the Pulmonary Arterial Hypertension (PAH) Rare Disease domain

  Dataset EGAD00001004525

• RNA-seq of multiple myeloma patient samples

  RNA from CD138+ plasma cells from patients with a plasma cell dyscrasia were sequenced using the TruSeq Stranded Total RNA Ribo-zero Gold kit (Illumina). Paired-end 75bp reads were generated on a NextSeq500 or HiSeq4000 (Illumina). The dataset consists of 1 MGUS sample, 5 SMM samples, 69 newly diagnosed myeloma samples, 1 relapsed myeloma sample, 1 previously treated myeloma samples, and 4 PCL samples. Matching whole genome sequencing data are available for these samples under study EGAS00001003164.

  Dataset EGAD00001004543

• Whole exome and targeted sequencing data from glioblastoma multiforme samples

  Whole exome and targeted sequencing data from 11 glioblastoma multiforme patients. A total of 70 tumour specimens and 11 blood samples were used for whole exome sequencing (WES) using the Agilent SureSelectXT Human All Exon V5 Kit. Two custom targeted sequencing panels were designed using the using Agilent’s Haloplex (TES1) or Agilent SureSelect XT2 technology (TES2). Libraries were sequenced on an Illumina HiSeq2500

  Dataset EGAD00001004420

• Human Embryonic Multi-tissue ChIP-seq (Manchester)

  Histone ChIP-seq of 13 human embryonic tissues from weeks 6-8 of gestation. H3K4me3, H3K27me3 and H3K27ac. Biological replicates (n=2) for 11 tissues. Tissues (n): Brain (2); Retinal Pigmented Epithelium (eye)(2); Palate(2); Tongue (1); Left ventricle (heart)(2); Lung(2); Liver(2); Pancreas (2*); Stomach(1); Upper limb (2); Lower limb (2); Adrenal gland (2); Kidney (2)

  Dataset EGAD00001004335

• Pulldown DNA methylation study v2

  Pilot study to set up sequencing protocols for targeted pulldown methylation profiling

  Dataset EGAD00001001242

• Validation of Exome-sequencing of S7RE-iPSC lines

  PCR products were obtained from each target loci using genomic DNA from human iPS cells. Subsequently, PCR products are pooled and subjected to Illumina library preparation. The library will be sequenced either by HiSeq or MiSeq. 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/

  Dataset EGAD00001001449

• Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - 100_all_samples

  All samples from the "100" project

  Dataset EGAD00001001457

• OCCAMS_Oesophageal Cancer Organoids_1

  ***THIS DATA CAN ONLY BE USED FOR NON-COMMERCIAL CANCER RESEARCH*** Sequencing of organoid cell lines derived from oesophageal tumour sections taken from patients diagnosed with primary oesophageal cancer who underwent tumour resection surgery.

  Dataset EGAD00001001889

• Susceptibility genes for the development of SLE during treatment of IBD

  A potential and very serious side effect of treating IBD with antiTNFa therapies (the currentgold standard) is the development of systemic lupus erythematosis (SLE). This side effect israre and unpredictable. Out of several thousand cases having received treatment, theUniversity of Calgary have accumulated 12 individuals with full phenotyping and novelserological antibody discovery panel data. We propose to exome sequence these samples inan effort to identify rare highly-penetrant variants that could be underlying this severephenotype.

  Dataset EGAD00001000670

• Raw sequencing data for donor and patient fecal samples

  Microbiome analysis was performed on the patient samples collected pre-FMT and on days after FMT, and on samples collected from the FMT donor. Genomic bacterial DNA was extracted from fecal samples using the QIAamp DNA Stool kit (Qiagen, Hilden, Germany), with the addition of a bead-beating lysis step. Genomic 16S ribosomal-RNA V4 variable regions were amplified and sequenced on the Illumina MiSeq platform.

  Dataset EGAD00001004371

• Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - ds_190916_2

  ICGC Oesophageal Adenocarcinoma tissue samples

  Dataset EGAD00001002689

• Children's Hospital of Philadelphia: GWAS of Left-Sided Cardiac Defects

  This is a family-based genome-wide association study of congenital left-sided cardiac lesions (LSLs). Cases with LSLs and their parents were recruited from the Cardiac Center at The Children's Hospital of Philadelphia between 1997 and 2010. The discovery dataset included 405 LSL case-parent triads. DNA was extracted from blood or saliva samples from these subjects and genotyping was conducted using the Illumina Infinium II HumanHap550K array (V3). This study was conducted with approval from the Institutional Review Board for the Protection of Human Subjects of The Children's Hospital of Philadelphia and all research subjects provided either written informed consent or, when appropriate, assent.

  Study phs000781

• DNA Replication Speed controls Epigenome Integrity and T Cell Fate

  Epigenetic mechanisms maintain cellular identities by enforcing stable, cell type-specific transcriptional programs while also allowing regulated plasticity for adaptations to environmental cues like differentiation signals. Dysregulation of this dual capacity has been linked to cancer and chronic inflammation, with the regulatory mechanisms remaining poorly understood. Here, we identify DNA replication speed as a physiological regulator controlling epigenome stability and plasticity. Using T-lymphocytes as a model, we demonstrate that fast DNA replication speed impaired epigenome stability, causing DNA methylation maintenance errors at cell type-specific enhancers and heterochromatin, ultimately leading to compromised cell function. However, accelerated DNA replication speed supported epigenome plasticity during differentiation, promoting successful cell-type transitions

  Study EGAS50000001273

• Single-nuclei histone modification profiling of the adult human central nervous system unveils epigenetic memory of developmental programs

  Here, we profile the adult human CNS from distinct regions, sex and ages, for chromatin accessibility at the single-nuclei level. Tissue was collected from 20 different donors (10 male, 10 female) within the ages of 34 to 74 years old. Each donor donated fresh frozen white matter from the following three tissue regions: primary motor cortex (Brodmann area 4, BA4), arbor vitae cerebelli (CB) and fasciculi cuneatus and gracilis from and cervical spinal cord (CSC). Tissue was processed semi-randomly, ensuring that each batch of experiments had a representation of both sexes and all three tissue regions. Completed libraries were again randomly multiplexed during sequencing to minimize batch effects.

  Study EGAS50000000283

• A Genomics-Driven Artificial Intelligence-Based Model Classifies Breast Invasive Lobular Carcinoma and Discovers CDH1 Inactivating Mechanisms

  We developed an artificial intelligence (AI)-model applied to histological images using CDH1 biallelic mutations, pathognomonic for breast invasive lobular carcinoma (ILC), as ground truth. We evaluated the performance of the AI-model to predict the presence of CDH1 biallelic mutations and to diagnose ILC. Subsequently, we investigated the molecular underpinning cases of predicted by the model to harbor a CDH1 biallelic mutations but lacking these alterations according to targeted sequencing. Among this analyses, we subjected to whole genome sequencing (WGS) one ILC case lacking CDH1 biallelic mutations by targeted sequencing and lacking CDH1 promoter methylation to determine the molecular basis of its lobular phenotype.

  Study EGAS50000000485

• 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

• 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

• 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

• A95724A

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

  Dataset EGAD00001008229

• A95724B

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

  Dataset EGAD00001008230

• 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

• A96172A

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

  Dataset EGAD00001008240

• 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

• Single Cell Genome Sequence for DLP+ library A118368B

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA605 passage 3 on DLP+ library A118368B

  Dataset EGAD00001009432

• Single Cell Genome Sequence for DLP+ library A118425B

  Single Cell Genome Sequence for Immortalized breast epithelium BRCA2+/- Tp53-/- cell line 184-hTert L9 116.66 cell line SA1188 on DLP+ library A118425B

  Dataset EGAD00001009434

• Single Cell Genome Sequence for DLP+ library A118784A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1050B passage 1, patient-derived xenograft SA1050E passage 1 on DLP+ library A118784A

  Dataset EGAD00001009436

• Single Cell Genome Sequence for DLP+ library A118790A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA610 passage 3, patient-derived xenograft SA1096C passage 1 on DLP+ library A118790A

  Dataset EGAD00001009437

• Single Cell Genome Sequence for DLP+ library A118797B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1184D passage 1 on DLP+ library A118797B

  Dataset EGAD00001009438

• Single Cell Genome Sequence for DLP+ library A118804A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1162B passage 1, patient-derived xenograft SA1096B passage 1 on DLP+ library A118804A

  Dataset EGAD00001009439

• Single Cell Genome Sequence for DLP+ library A118808B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1096C passage 1 on DLP+ library A118808B

  Dataset EGAD00001009441

• Single Cell Genome Sequence for DLP+ library A118814B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1162B passage 1 on DLP+ library A118814B

  Dataset EGAD00001009443

• Single Cell Genome Sequence for DLP+ library A96171A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA501 passage 2, patient-derived xenograft SA611 passage 3 on DLP+ library A96171A

  Dataset EGAD00001009458

• 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