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• Normal sample for patient SA1026

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1026

  Dataset EGAD00001009587

• Normal sample for patient SA1027

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1027

  Dataset EGAD00001009588

• Normal sample for patient SA1028

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1028

  Dataset EGAD00001009589

• Normal sample for patient SA1040

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1040

  Dataset EGAD00001009590

• Normal sample for patient SA1064

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1064

  Dataset EGAD00001009591

• Normal sample for patient SA1065

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1065

  Dataset EGAD00001009592

• Normal sample for patient SA1069

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1069

  Dataset EGAD00001009593

• Normal sample for patient SA1073

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1073

  Dataset EGAD00001009594

• Normal sample for patient SA1074

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1074

  Dataset EGAD00001009595

• Normal sample for patient SA576

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA576

  Dataset EGAD00001009596

• Normal sample for patient SA610

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA610

  Dataset EGAD00001009597

• Normal sample for patient SA992

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA992

  Dataset EGAD00001009598

• Normal sample for patient SA994

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA994

  Dataset EGAD00001009599

• Normal sample for patient SA288

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA288

  Dataset EGAD00001009601

• Normal sample for patient SA299

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA299

  Dataset EGAD00001009602

• Normal sample for patient SA415

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA415

  Dataset EGAD00001009603

• Normal sample for patient SA666

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA666

  Dataset EGAD00001009604

• Tumour sample for patient SA1065

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1065

  Dataset EGAD00001009605

• Tumour sample for patient SA1064

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1064

  Dataset EGAD00001009606

• Tumour sample for patient SA1026

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1026

  Dataset EGAD00001009607

• Tumour sample for patient SA1069

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1069

  Dataset EGAD00001009608

• Tumour sample for patient SA1017

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1017

  Dataset EGAD00001009609

• Tumour sample for patient SA1027

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1027

  Dataset EGAD00001009610

• Tumour sample for patient SA1073

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1073

  Dataset EGAD00001009611

• Tumour sample for patient SA1074

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1074

  Dataset EGAD00001009612

• Tumour sample for patient SA576

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA576

  Dataset EGAD00001009613

• Tumour sample for patient SA1028

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1028

  Dataset EGAD00001009614

• Tumour sample for patient SA1040

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1040

  Dataset EGAD00001009615

• Tumour sample for patient SA992

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA992

  Dataset EGAD00001009616

• Tumour sample for patient SA610

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA610

  Dataset EGAD00001009617

• Normal sample for patient SA416

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA416

  Dataset EGAD00001009618

• Normal sample for patient SA1070

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1070

  Dataset EGAD00001009619

• Tumour sample for patient SA1070

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1070

  Dataset EGAD00001009620

• Tumour sample for patient SA997

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA997

  Dataset EGAD00001009621

• DNA methylation changes associated with hyperglycemia in type 1 diabetes

  This dataset includes DNA methylation profiles from 112 young with Type 1 Diabetes (T1D) at T1D diagnosis, who were longitudinally monitored for hyperglycemia over an average duration of 3 years. These datasets were generated using whole-genome bisulfite sequencing. It includes 1872 fastq files (i.e. 936 paired-end fastq files) generated through 150 bp paired-end sequencing on Illumina HiSeqX.

  Dataset EGAD50000000545

• 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

• 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

• Pulldown DNA methylation study v2

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

  Dataset EGAD00001001242

• 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

• Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - ds_190916_2

  ICGC Oesophageal Adenocarcinoma tissue samples

  Dataset EGAD00001002689

• bulkRNA

  Bulk RNA-seq for cALL patient-derived PDX samples

  Dataset EGAD00001006133

• scRNA PDX

  Single cell RNA-seq for PT1-derived PDX samples

  Dataset EGAD00001006134

• Multiregion exome sequencing

  Multiregional analysis of three cases of GBM. For each tumor, 9 portions were analyzed by whole exome sequencing. A total of 27 bam files are present in our dataset.

  Dataset EGAD00001007063

• Single-cell ATAC-Seq (Chromium Next GEM Single Cell ATAC kit v1.1 from 10X Genomics )

  Human data for chromatin accessibility (scATAC-Seq) in CD34+ B cell precursors.

  Dataset EGAD00001010910

• Mult-omics Palbociclib Resistance Study in HR+/HER2– Metastatic Breast Cancer

  Resistance to CDK4/6 inhibitors and endocrine therapy (ET) are common and poorly understood since they have been real game changer in patients with HR-positive and HER2-negative MBC. A comprehensive genomic and transcriptomic analysis of pre-treatment and post-treatment tumors from patients treated with palbociclib plus ET identified novel markers associated with poor prognosis such as genomic scar features caused by homologous repair deficiency (HRD), estrogen response signatures, and four unique prognostic clusters with distinct molecular features. Tumors with TP53 mutations co-occurring with a unique HRD-high cluster responded poorly. By comparing genomic and transciptomic profiles of paired samples, tumors were found to be further enriched in HRD genomic scars and many had switched to aggressive molecular subtypes. Furthermore, we identified high frequencies of acquired genomic alterations upon disease progression in RB1, ESR1, PTEN, and KMT2C. Our findings provide new insight into potential predictive biomarkers that could be targeted to overcome resistance. (NCT03401359)

  Study EGAS00001005736