21148 results for "Buy fc 26 coins Buyfc26coins.com is EA Sports official for FC 26 coins The process was smooth and quick..ivNx"

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• Tumour sample for patient SA682

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA682

  Dataset EGAD00001009349

• Tumour sample for patient SA681

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA681

  Dataset EGAD00001009348

• Tumour sample for patient SA680

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA680

  Dataset EGAD00001009347

• Tumour sample for patient SA679

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA679

  Dataset EGAD00001009346

• Tumour sample for patient SA678

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA678

  Dataset EGAD00001009345

• Tumour sample for patient SA677

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA677

  Dataset EGAD00001009344

• Tumour sample for patient SA676

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA676

  Dataset EGAD00001009343

• Tumour sample for patient SA675

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA675

  Dataset EGAD00001009342

• Tumour sample for patient SA674

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA674

  Dataset EGAD00001009341

• Tumour sample for patient SA673

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA673

  Dataset EGAD00001009340

• Tumour sample for patient SA590

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA590

  Dataset EGAD00001009196

• Tumour sample for patient SA595

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA595

  Dataset EGAD00001009200

• Tumour sample for patient SA593

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA593

  Dataset EGAD00001009199

• Tumour sample for patient SA592

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA592

  Dataset EGAD00001009198

• Tumour sample for patient SA591

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA591

  Dataset EGAD00001009197

• Tumour sample for patient SA589

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA589

  Dataset EGAD00001009195

• Tumour sample for patient SA588

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA588

  Dataset EGAD00001009194

• Tumour sample for patient SA586

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA586

  Dataset EGAD00001009193

• Tumour sample for patient SA585

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

  Dataset EGAD00001009192

• Tumour sample for patient SA530

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

  Dataset EGAD00001009191

• Tumour sample for patient SA404

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

  Dataset EGAD00001009190

• Tumour sample for patient SA402

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

  Dataset EGAD00001009189

• Tumour sample for patient SA398

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

  Dataset EGAD00001009188

• Tumour sample for patient SA395

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

  Dataset EGAD00001009187

• Tumour sample for patient SA394

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

  Dataset EGAD00001009186

• Tumour sample for patient SA287

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

  Dataset EGAD00001009185

• Tumour sample for patient SA283

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

  Dataset EGAD00001009184

• Tumour sample for patient SA279

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

  Dataset EGAD00001009183

• Tumour sample for patient SA276

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

  Dataset EGAD00001009182

• Tumour sample for patient SA275

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

  Dataset EGAD00001009181

• Tumour sample for patient SA274

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

  Dataset EGAD00001009180

• Tumour sample for patient SA272

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

  Dataset EGAD00001009179

• Tumour sample for patient SA219

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

  Dataset EGAD00001009178

• Tumour sample for patient SA218

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

  Dataset EGAD00001009177

• RNA data for medulloblastoma samples (ICGC)

  RNA sequencing data for 170 medulloblastoma tumor samples

  Dataset EGAD00001003279

• High-grade serous ovarian cancer refined with single-cell RNA-sequencing

  We performed single-cell RNA-sequencing of 18,403 cells unbiasedly collected from 7 treatment-naive HGSOC tumours. For each phenotypic cluster of tumour or stromal cells, we identified specific transcriptomic markers. Next, we explored which phenotypic clusters correlate with overall survival based on expression of these transcriptomic markers in 1467 bulk RNA-seq tumours. By evaluating molecular subtype signatures in single cells, we assessed to what extent a phenotypic cluster of tumour or stromal cells contributes to each molecular subtype.

  Study EGAS00001004987

• RNA-sequencing of meningiomas for integrative molecular classification.

  RNA-sequencing of meningiomas for integrative molecular classification.

  Dataset EGAD00001007494

• pe_meta_20170131

  Inverse variance weighted fixed effect meta-analysis of three European GWAS studies of the offspring of Pre-eclampsia affected births (2658 Cases and 308267 Controls).

  Dataset EGAD00010001211

• Breast Cancer FRT RNA seq

  We propose to definitively characterise the somatic genetics of ER+ve, HER2-ve breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001000338

• Single cell RNA sequencing of colorectal cancer patients (CRC-SG1)

  Raw sequencing reads were processed as single end sequencing, aligned to the human reference genome GRCh38 and processed using CellRanger 3.1.

  Dataset EGAD00001008555

• Metastatic Breast Cancer Whole Genome

  We propose to definitively characterise the somatic genetics of Metastatic breast cancer through generation of comprehensive catalogues of somatic mutations in Metastatic breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001000899

• ERDERA Diagnostic Research Workstream DAC

  The ERDERA Diagnostic Research Workstream DAC decides on data access requests according to the principles defined in the ERDERA Data Sharing Framework Agreement.

  Dac EGAC50000000728

• Tumor cells metabolically resist immune-checkpoint therapy by macrophage efferocytosis-mediated fatty acid recycling

  Tumor cells metabolically adapt to the nutrient-deprived tumor microenvironment (TME). However, the metabolic plasticity underlying immune-checkpoint blockade (ICB) adaptation remains unclear.

  Study EGAS50000001416

• Angiosarcoma_follow_up_study

  A bespoke targeted pulldown experiment will be performed on patients with Angiosarcoma. the resulting products will be sequenced to determine the prevalence of previously found mutations in these patients.

  Study EGAS00001000405

• Kidney_Single_Cell_Study

  We intend to use single cell transcriptome analysis to explore the heterogenity of different cell types within the kidney.

  Study EGAS00001002325

• Chromatin_Profiling_in_Twins

  50 lymphoblastoid cell lines of adult female Twins which are part of the MuTHER study, processed with the FAIRE assay in order to generate maps of open chromatin.

  Study EGAS00001000097

• Angiosarcoma_follow_up_2_validation_study

  A bespoke targeted pulldown experiment will be performed on patients with Angiosarcoma. the resulting products will be sequenced to determine the prevalence of previously found mutations in these patients.

  Study EGAS00001000518

• Genome and transcriptome sequence data from a metastatic pancreatic adenocarcinoma patient

  Genome and transcriptome sequence data from a metastatic pancreatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001008925

• Genome and transcriptome sequence data from a lung adenocarcinoma patient

  Genome and transcriptome sequence data from a lung adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001008926

• Genome and transcriptome sequence data from a carcinoma of unknown primary patient

  Genome and transcriptome sequence data from a carcinoma of unknown primary patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001008927