7406 results for "canc*"

in 36.39 milliseconds.

• Targeted DNA sequencing

  Targeted DNA sequencing of high-grade serous ovarian cancer (HGSC) tumour and normal samples from 15 patients with homologous recombination deficiencies. The dataset includes fastq files from 243 HGSC tumours (15 primary, 3 relapse, 225 end-stage) and 15 normals from 15 HGSC patients. Following target hybrid capture of 63 genes involved in DNA repair and response to treatment with an Agilent SureSelect XT panel, sequencing libraries were generated using the SureSelect XT Low Input Target Enrichment System (Agilent) as per the manufacturer's protocol. Libraries were sequenced on an Illumina NextSeq 500 at the Peter MacCallum Cancer Centre (Melbourne, Australia).

  Dataset EGAD00001009747

• S:CORT Stratification in COloRecTal cancer

  Colorectal cancer samples will be submitted for Illumina sequencing using a custom capture of 116 genes implicated in colorectal tumourigenesis. Driver mutations will be detected and ultimately correlated with phenotypic data.

  Dataset EGAD00001009760

• Single Cell Genome Sequence for DLP+ library A96141A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA604 passage 8 on DLP+ library A96141A

  Dataset EGAD00001009777

• Single cell RNA-sequencing of tissues from NSCLC patients treated with chemoimmunotherapy

  The goal of this study is to characterize immune cell populations by single cell RNA-sequencing (scRNA-seq) in tumor and uninvolved normal tissues from non-small cell lung cancer (NSCLC) patients with resectable non-small cell lung cancer and who received neoadjuvant chemoimmunotherapy. scRNA-seq was performed on seven pairs of tumor and normal tissues as well as one lymph node (LN) sample. Data set includes pair-end fastq files for single cell RNA sequencing of 7 neo-immuno patients. (Total 15 samples and 50 runs).

  Dataset EGAD00001009778

• cfDNA from fractionated and paired unfractionated plasma samples of lung cancer patients

  Plasma from lung cancer patients from EDTA tubes was fractionated using size exclusion chromatography. Fractions 1-5, 7-11, 12-15, 16-20 were pooled, cfDNA was extracted from the fractions and paired unfractionated samples and PE150bp sequencing was performed on an Illumina Novaseq S4 flowcell. Samples are provided as raw reads without any prior processing.

  Dataset EGAD00001009780

• BCSA_Exome+SmartSeq3

  Multiple regions were cut out of each tumor extracted form breast cancer patients and two experiments were run: - Whole exome sequencing on each of the regions plus an adjacent normal tissue sample - Smart-Seq3 Single cell RNA sequencing on EPCAM+ CD45- sorted cells from different tumor regions

  Dataset EGAD00001009781

• Tumor Educated Platelets (TEPs) for breast cancer detection

  The TEP dataset consists of 549 Fastq samples which are divided into two experiments: a training data cohort, used to train the classifier, and a validation data cohort, used to assess classifier performance

  Dataset EGAD00001009790

• 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

• CCMA

  This dataset has the processed WGS data for the cancer models in CCMA.

  Dataset EGAD00001009633

• RNAseq of primary mesothelioma cell lines

  Mesothelioma is an aggressive cancer associated with previous exposure to asbestos and dismal prognosis. Since a pemetrexed/cisplatin combination was introduced for treatment of mesothelioma, no new first- or second-line therapies have been discovered. Thus, to better understand what drives mesothelioma carcinogenesis and to identify potential targets for therapy, in this project we aim at performing RNAseq analysis of a panel of mesothelioma cells lines.

  Dataset EGAD00001009642

• WGS of primary mesothelioma cell lines

  Mesothelioma is an aggressive cancer associated with previous exposure to asbestos and dismal prognosis. Since a pemetrexed/cisplatin combination was introduced for treatment of mesothelioma, no new first- or second-line therapies have been discovered. Thus, to better understand what drives mesothelioma carcinogenesis and to identify potential targets for therapy, in this project we aim at performing WGS analysis of a panel of mesothelioma cells lines.

  Dataset EGAD00001009641

• Single Cell Genome Sequence for DLP+ library A96228A

  Single Cell Genome Sequence for Immortalized lymphoblastoid cell line GM18507 cell line SA928,Triple negative breast cancer patient-derived xenograft SA609 passage 2 patient-derived xenograft SA609 passage 2 on DLP+ library A96228A

  Dataset EGAD00001009645

• Single Cell Genome Sequence for DLP+ library A98247A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA530 passage 3 on DLP+ library A98247A

  Dataset EGAD00001009646

• Sequencing data for the manuscript "Multi-focal sampling of de novo metastatic prostate cancer reveals complex polyclonality and enables accurate clinical genotyping"

  This submission includes targeted and whole exome paired-end fastq files.

  Dataset EGAD00001009651

• ATAC-seq of metastatic prostate tumors

  This dataset includes Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) data, in FASTQ format, from 70 metastatic castration-resistant prostate cancer tumor samples from the SU2C/PCF West Coast Dream Team (WCDT) project. The sequencing data is paired-end, 150 bp sequencing data from an Illumina NovaSeq 6000 machine. ATAC-seq libraries were prepared following the protocol described in Buenrostro et al. Nature Methods. 2013 (PMID: 24097267) and Corces et al. Nature Methods. 2017 (PMID: 28846090).

  Dataset EGAD00001009654

• Nanopore low-pass WGS of human brain tumors

  Nanopore low-pass WGS of human brain tumors for evaluation of DNA methylation-based classification of cancer

  Dataset EGAD00001009663

• Somatic mutations in facial skin from countries of contrasting skin cancer risk

  The incidence of non-melanoma skin cancer is 17-fold lower in Singapore compared to the UK1, despite Singapore receiving 2-3 times more year-round ultraviolet radiation (UV)2,3. The ageing epidermis of the skin comprises competing somatic mutant clones4,5, from which such cancers develop. We question if differences in keratinocyte skin cancer incidence are reflected in the mutational landscape by comparing ageing facial epidermis from donors of Singapore and the UK. We find UK skin to be a highly competitive, densely mutated landscape with 4-fold greater mutation burden compared to Singaporean skin and differences in clonal selection by country. We disproportionately observe multiple features common to keratinocyte skin cancers6,7,8 in UK skin, such as UV mutagenesis, copy number aberration and hotspot mutations (in particular TP53 R248W). We conclude that keratinocyte skin cancer incidence is reflected in the somatic clones of non-cancerous epidermis. Finally, we re-analyse squamous cell carcinoma exomes from Korea9 to show, even in low incidence populations, carcinogenesis is driven by UV damage.

  Dataset EGAD00001009666

• The University of Hong Kong Colon Cancer Ganciclovir Study WGS Data

  Human clonal intestinal organoids were treated with 1µM MMF (Roche), 20 μM GCV (Hainan Poly Pharm Co Ltd), or in combinations (1 µM MMF + 20 μM GCV or 1 µM MMF + 40 μM GCV) continuously for 4-6 weeks. DNA was extracted after drug treatment. WGS was performed with 150 bp PE sequencing at 30X using an Illumina Novaseq sequencer.

  Dataset EGAD00001009667

• Normal sample for patient SA1058

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1058

  Dataset EGAD00001009672

• RNA sequencing

  RNAseq of 45 high-grade serous ovarian cancer tumour samples. Libraries were generated using the NEB Ultra II Directional RNA library Prep kit with polyA enrichment. Libraries were sequenced as paired-end 50 or 100bp on an Illumina NextSeq or NovaSeq.

  Dataset EGAD00001009844

• Sequencing of longitudinal glioma pairs

  Clonal evolution drives cancer progression and therapeutic resistance. Recent studies revealed divergent longitudinal trajectories in gliomas, but early molecular traits steering post-treatment cancer evolution remain unclear. We analyzed sequencing data of 544 initial-recurrent adult diffuse glioma pairs to identify genomic and transcriptomic early predictors of tumor evolution in each molecular subtype.

  Dataset EGAD00001009845

• Mechanism of action and resistance to Trastuzumab Deruxtecan in patients with metastatic breast cancer: the DAISY trial

  198 exome sequencing samples

  Dataset EGAD00001009853

• Germline WES data of children with pathogenic mutations in cancer predisposing genes

  This data set includes bam files (aligned to hg38) from the germline of children who have pathogenic mutations in cancer predisposing genes

  Dataset EGAD00001009854

• RNAseq of breast cancer bone metastases PDX treated to IACS

  Fastq files from RNAseq of breast cancer bone metastases PDX of tumor HBC-124 treated by IACS-010759 (4 samples) or not (4 samples).

  Dataset EGAD00001009857

• Dynamics of sequence and structural cell-free DNA landscapes in small-cell lung cancer

  The dataset for the study “Dynamics of sequence and structural cell-free DNA landscapes in small-cell lung cancer” includes 171 bam files from targeted next-generation sequencing (TEC-Seq) from plasma cell-free DNA and matched white blood cell DNA from 33 individuals with small cell lung cancer, alongside 10 bam files from whole exome sequencing of tumor and matched normal DNA for 5 individuals with small cell lung cancer.

  Dataset EGAD00001009860

• Genomic profiling of subcutaneous patient derived xenograft models of solid childhood cancer

  The pediatric cancer cohort in this study included 70 PDX models from 65 different individuals. This cohort included a total of 16 different pediatric solid tumor subtypes, including fourteen Wilms tumors, thirteen hepatoblastomas, thirteen osteosarcomas, ten germ cell tumors, four neuroblastomas, three clear cell sarcomas, two adrenal cortical carcinomas, two leydig cell tumors, two medulloblastomas, one embryonal rhabdomyosarcoma (ERMS), one Ewing sarcoma, one pleomorphic sarcoma, one adenocarcinoma, one glioblastoma, one mesothelioma and one ovarian tumor. Notably, we have five samples with multiple PDX models from same patient, including two cases with duplicates (564 and 564-Dup, 1796 and 1796-Dup), one case with two different metastasis (560-SM, 560-LM), one case with two blocks from same tumor (1939 and 1939-Dup), and one case with different primary tumor from same patient (2264 and 1932). We have a total of 353 sequencing data, including 82 RNA sequencing data (RNA-seq), 138 whole-exome sequencing (WES) and 135 low-pass whole-genome sequencing (WGS). For RNA-seq data, we have 61 PDXs and 21 PTs; for WES, we have 67 PDXs, 30 PTs and 40 matched normal germlines; for WGS, we have 64 PDXs, 30 PTs and 40 matched normal germlines. Of which, 19 PT-PDX paired RNA-seq, 28 paired PT-PDX paired WES and WGS were included.

  Dataset EGAD00001009863

• Prostate cancer m6A epitranscriptome

  Using meRIP-sequencing, we profiled N-6 methyladenosine (m6A) in a cohort of 148 primary prostate cancer samples as part of the Canadian Prostate Cancer Genome Network project (CPC-GENE). Paired-end sequencing of 150 bp reads were mapped to GRCh38.p13 using annotations from gencode.v34.chr_patch_hapl_scaff.annotation.gtf. Peaks were called using MeTPeak, joint peaks were identified and IP reads were quantitated, normalized and adjusted using Input reads to obtain estimates of m6A abundance.

  Dataset EGAD00001009869

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 3)

  Whole genome sequencing data of 9 high-grade serous carcinoma (HGSC) patients (55 samples) sequenced with HiSeq X Ten.

  Dataset EGAD00001009888

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 2)

  Whole genome sequencing data of 8 High-grade serous carcinoma (HGSC) patients (20 samples) sequenced with HiSeq X Ten.

  Dataset EGAD00001009791

• HGSOC-celllines-SmartSeq3

  Smart-seq3 scRNA-seq of cells from primary (OV2295) and metastatic (OV2295R2) high-grade serous ovarian cancer cell-line

  Dataset EGAD00001009798

• Distinct embryonic phylogenies and driver events of infant Wilms tumor - DNA

  Cancers of adults typically arise through progressive rounds of clonal diversification and intratumoral selective sweeps which generate a long mutational trunk with shorter subclonal branches. Here, we investigated whether tumors of young children exhibit the same phylogenetic configuration. We studied three infants, including two newborns, with the childhood kidney cancer, Wilms tumour, through whole genome sequencing of bulk tissues, of single cell derived organoids, and of microdissections. All three cancers exhibited unusual driver events, with tumours of newborns harbouring FOXR2 rearrangements, delineating a distinct variant of Wilms tumour. Phylogenetic analyses suggest that tumors were seeded in an early, possibly confined window of development. Unusually, following seeding there was extensive polyclonal diversification with little evidence of clonal sweeps, leading to a distinct phylogenetic configuration more reminiscent of normal tissues rather than of adult cancers. These findings indicate that some childhood cancers may diversify via unorthodox phylogenetic pathways.

  Dataset EGAD00001009812

• Distinct embryonic phylogenies and driver events of infant Wilms tumor - RNA

  Cancers of adults typically arise through progressive rounds of clonal diversification and intratumoral selective sweeps which generate a long mutational trunk with shorter subclonal branches. Here, we investigated whether tumors of young children exhibit the same phylogenetic configuration. We studied three infants, including two newborns, with the childhood kidney cancer, Wilms tumour, through whole genome sequencing of bulk tissues, of single cell derived organoids, and of microdissections. All three cancers exhibited unusual driver events, with tumours of newborns harbouring FOXR2 rearrangements, delineating a distinct variant of Wilms tumour. Phylogenetic analyses suggest that tumors were seeded in an early, possibly confined window of development. Unusually, following seeding there was extensive polyclonal diversification with little evidence of clonal sweeps, leading to a distinct phylogenetic configuration more reminiscent of normal tissues rather than of adult cancers. These findings indicate that some childhood cancers may diversify via unorthodox phylogenetic pathways.

  Dataset EGAD00001009813

• Concatenated long-read single-cell RNA sequencing of momentum biopsies of ovarian cancer patients

  Concatenated long-read single-cell RNA sequencing samples prepared using 10X and the HIT-scIsoSeq protocol. The sequencing was performed on Sequel II Pacbio machine. 3 ovarian cancer patients, 5 omentum biopsies samples: 3 metastasis samples (one per patient), 2 healthy samples (one per patient except Patient2). 4 bam files per metastasis sample, 2 bam files per healthy sample.

  Dataset EGAD00001009814

• Illumina single-cell RNA sequencing of omentum biopsies of ovarian cancer patients

  Illumina Novaseq paired-end single-cell RNA sequencing samples prepared using 10X Genomics platform. 3 ovarian cancer patients, 5 omentum biopsies samples: 3 HGSOC metastasis samples (one per patient), 2 healthy samples (one per patient except Patient2). 4 paired fastq files per sample.

  Dataset EGAD00001009815

• Tumor/Normal WXS and RNASeq from patients dosed with neoTCR T-cell therapy

  Sixteen patients with refractory solid cancers received up to three distinct neoTCR-transgenic cell products, each expressing a patient-specific neoTCR, in a cell dose-escalation, first-in-human phase 1 clinical trial (NCT03970382). Included are the tumor and normal WXS and tumor RNAseq for dosed patients.

  Dataset EGAD00001009830

• GELATO clinical trial RNA-Seq data (primary tumors and local recurrences)

  RNA-Seq data of 10 lobular breast cancer primary tumors and 3 local recurrences obtained from 11 unique patients from GELATO clinical trial. The included raw transcriptome sequencing data in fastq format was generated using Illumina NovaSeq 6000 from archived FFPE material.

  Dataset EGAD00001009835

• GELATO clinical trial RNA-Seq data (metastatic lesions)

  RNA-Seq data of 46 matched lobular breast cancer metastatic samples obtained from 21 unique patients from GELATO clinical trial assayed at three timepoints: at baseline (directly after patient randomization), pre-atezolizumab (after induction treatment with carboplatin for two weeks) and on atezolizumab (after two cycles of atezolizumab combined with carboplatin). The included raw transcriptome sequencing data in fastq format was generated using Illumina NovaSeq 6000 from fresh frozen material.

  Dataset EGAD00001009834

• GELATO clinical trial whole exome sequencing data (primary tumors and local recurrences)

  Paired-end whole exome sequencing of 10 lobular breast cancer primary tumors, 3 local recurrences and matched normal samples obtained from 10 unique patients from the GELATO clinical trial. The included raw sequencing data in fastq format was generated using Illumina NovaSeq 6000 from archived FFPE material (tumor data) and fresh frozen material (matched normal data).

  Dataset EGAD00001009836

• GELATO clinical trial whole exome sequencing data (metastatic lesions)

  Paired-end whole exome sequencing of 19 lobular breast cancer metastatic tumors and matched normal samples obtained from 19 unique patients from the GELATO clinical trial. The included raw sequencing data in fastq format was generated using Illumina NovaSeq 6000 from fresh frozen material.

  Dataset EGAD00001009837

• 15 Healthy controls, 25 conlonrectal cancer patients without liver metastasis and 24 conlonrectal cancer patients with liver metastasis (target capture)

  15 Healthy controls, 25 conlonrectal cancer patients without liver metastasis and 24 conlonrectal cancer patients with liver metastasis (target capture)

  Dataset EGAD00001009838

• 18 plasma samples and their paired 18 urinary cfDNA samples without cancer

  18 plasma samples and their paired 18 urinary cfDNA samples without cancer

  Dataset EGAD00001009839

• whole genome sequence of liver cancer

  There are six samples with three blood samples and three organids

  Dataset EGAD00001009841

• ChIPseq sequence of liver cancer

  There are 61 samples

  Dataset EGAD00001009842

• Tumour sample for patient SA1058

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1058

  Dataset EGAD00001009673

• Tumour sample for patient SA998

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA998

  Dataset EGAD00001009674

• Variants from germline WES data of pediatric cancer patients

  This dataset contains germline variants (in .vcf format) from six pediatric cancer patients (sample IDs D1 - D6). WES data of the children and their parents was mapped to hg38. A consensus of four variant callers was used to obtain germline variants of the children.

  Dataset EGAD00001009678

• META-PRISM

  A pan-cancer cohort of 1031 patients resistant to systemic therapies or with no approved therapeutic options. It includes whole-exome sequencing of 571 tumor and matched-normal samples, and transcriptome sequencing of 947 tumor samples. Biopsies were taken at entry into precision medicine trials, often after diagnosed resistance. Comprehensive clinical information is available for all patients and include patient age at biospy, tumor primary site and histological subtype, biopsy site, treatments received prior to biopsy, blood assessment results at biopsy, metastatic sites at biopsy, and survival time from the biopsy date.

  Dataset EGAD00001009684

• CRUK Accelerator: Pancreatic neuroendocrine tumours (panNETs) whole exome and RNAseq raw sequencing data

  Whole exome and RNASeq raw sequencing data for an individual with multiple pancreatic neuroendocrine tumours (panNETs). Age at diagnosis was 51. Tumour tissue and PBMCs were used for sequencing. This data was generated as part of a study funded by a Cancer Research UK Centres Network Accelerator Award Grant (A21998).

  Dataset EGAD00001009685

• TRACERx Reduced-representation bisulfite sequencing (RRBS)

  RRBS data from TRACERx non-small cell lung cancer (NSCLC) tumours and matched normal adjacent tissue. TRACERx (TRAcking Cancer Evolution through therapy (Rx)) is a prospective cohort study designed to investigate intratumor heterogeneity (ITH) in relation to clinical outcome, and to determine the clonal nature of driver events and evolutionary processes in early stage non-small cell lung cancer (NSCLC).

  Dataset EGAD00001009707

• Human primary and metastatic colorectal cancer (CRC) samples

  Bank of human both primary and metastastic colorectal cancer sample RNAseq

  Dataset EGAD00001009712

• pan-cancer plasma cfRNA

  Dataset contains mRNA capture sequencing data from plasma of 266 different human donors. The first, pan-cancer, cohort covers 25 high-grade to metastatic cancer types (8 cancer patients per type) and a control group (8 healthy donors). The validation cohort comprises additional plasma samples from ovarian, prostate and uterine cancer patients (12 per type) as well as additional samples from controls (22 new and 8 repeated). Samples were sequenced on a NovaSeq 6000 and are provided in FASTQ format.

  Dataset EGAD00001009713

• 2 paired WGS samples of peritumour regions of colorectal cancer

  2 paired WGS samples of peritumour regions of colorectal cancer (2 patients). The library was prepared using the Illumina TruSeq Nano FFPE kit and the sequencing was done on NovaSeq6000.

  Dataset EGAD00001009714

• PGDx elio™ plasma resolve assay: targeted sequencing analyses of WBC DNA

  The dataset "PGDx elio™ plasma resolve assay: targeted sequencing analyses of WBC DNA" includes paired end FASTQ reads of 49 white blood cell (WBC) genomic DNA samples from metastatic colorectal cancer patients. Sequencing was performed using a panel consisting of 33 genes, covering over 237,000 bp, targeting 25,000x depth across the targeted regions.

  Dataset EGAD00001009721

• PGDx elio plasma resolve analytical validation

  This dataset consists of 39 noncancerous donor and 62 cancer patient plasma samples (including 29 patients with CRC across a total of 13 tumor types) that were analyzed with the PGDx elio plasma resolve assay. The PGDx elio plasma resolve assay is a hybrid capture approach targeting 33 genes with sequencing performed using the Illumina NextSeq with 150bp paired-end reads. The bam files provided have been adapter masked and contain duplicate reads.

  Dataset EGAD00001009718

• PGDx elio™ plasma resolve assay: targeted sequencing analyses of plasma cfDNA

  The dataset "PGDx elio™ plasma resolve assay: targeted sequencing analyses of plasma cfDNA" includes paired end FASTQ reads of 183 cfDNA samples from metastatic colorectal cancer patients. Sequencing was performed using a panel consisting of 33 genes, covering over 237,000 bp, targeting 25,000x depth across the targeted regions.

  Dataset EGAD00001009719

• PGDx elio™ tissue complete assay: targeted sequencing analyses of tissue DNA

  The dataset "PGDx elio™ tissue complete assay: targeted sequencing analyses of tissue DNA" includes paired end FASTQ reads of 28 tissue samples from metastatic colorectal cancer patients. Sequencing was performed using a panel consisting of 505 genes, targeting 2,500x depth across the targeted regions.

  Dataset EGAD00001009720

• Normal sample for patient SA296

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA296

  Dataset EGAD00001009566

• Normal sample for patient SA399

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA399

  Dataset EGAD00001009567

• Normal sample for patient SA400

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA400

  Dataset EGAD00001009568

• Normal sample for patient SA409

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA409

  Dataset EGAD00001009569

• Normal sample for patient SA420

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA420

  Dataset EGAD00001009570

• Normal sample for patient SA533

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA533

  Dataset EGAD00001009571

• Normal sample for patient SA997

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

  Dataset EGAD00001009573

• Normal sample for patient SA998

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA998

  Dataset EGAD00001009574

• Tumour sample for patient SA416

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

  Dataset EGAD00001009575

• Normal sample for patient SA597

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA597

  Dataset EGAD00001009572

• Normal sample for patient SA095

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA095

  Dataset EGAD00001009600

• Tumour sample for patient SA400

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA400

  Dataset EGAD00001009576

• Tumour sample for patient SA290

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA290

  Dataset EGAD00001009577

• Tumour sample for patient SA288

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

  Dataset EGAD00001009578

• Tumour sample for patient SA299

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

  Dataset EGAD00001009579

• Tumour sample for patient SA095

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA095

  Dataset EGAD00001009580

• Tumour sample for patient SA415

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

  Dataset EGAD00001009581

• Normal sample for patient SA718

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA718

  Dataset EGAD00001009582

• Normal sample for patient SA720

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA720

  Dataset EGAD00001009583

• Tumour sample for patient SA718

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA718

  Dataset EGAD00001009584

• Tumour sample for patient SA720

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA720

  Dataset EGAD00001009585

• Normal sample for patient SA1017

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

  Dataset EGAD00001009586

• 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