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• Sequencing data of the CTSC gene after WGS of samples from individuals with PLS

  The sequencing data of the CTSC gene after whole genome sequencing of blood samples from two individuals with Papillon-Lèfevre Syndrome.

  Dataset EGAD00001006961

• Mesothelioma of the peritoneum and Pseudomyxoma peritonei

  Mesothelioma of the peritoneum (n=21) and Pseudomyxoma peritonei/mucinous adenocarcinoma of the appendix (n=11)

  Dataset EGAD00001008826

• PacBio WGS based analysis of complex chromosomal rearrangements

  The dataset consists of a single sample whereby the genomic DNA was analysed using PacBio WGS at 30x coverage to assess the breakpoint sites of complex chromosomal rearrangements.

  Dataset EGAD00001015593

• Nanopore whole-genome sequencing of sample RK067 and variant-call data (SNVs and intermediate-sized deletions) of 174 Japanese samples.

  We performed whole-genome sequencing of a human samples using Oxford Nanopore MinION sequencer, so as to be able to establish methods to detect and identify structural variations in Japanese individuals. Intermediate-sized deletions were identified from 174 Japanese samples��� short-reads whole-genome sequencing data. Variant call information of these intermediate-sized deletions were joined with SNVs identified in a previous study (Fujimoto, A et al., Nat Genet, 2016) to create a reference panel for use in imputation.

  Study JGAS000180

• Circulating tumour DNA abundance and potential utility in de novo metastatic prostate cancer

  Several systemic therapeutic options exist for metastatic castration sensitive prostate cancer (mCSPC). Circulating tumour DNA can profile metastatic castration resistant prostate cancer and influence treatment decisions, but remains untested in mCSPC. We set out to determine ctDNA abundance at de novo mCSPC diagnosis and whether ctDNA provides complementary clinically relevant information to a prostate biopsy. We collected and sequenced 77 plasma cell-free DNA samples from 53 newly diagnosed patients with mCSPC. Targeted sequencing was also performed on DNA from 48 diagnostic prostate tissue samples.

  Study EGAS00001003351

• Pediatric tumor in a single child of three large nuclear families

  We identify three nuclear families in which a pediatric tumor had been diagnosed in a single child and neither parent had been diagnosed with cancer. These families had 4, 5, and 7 children, respectively. Diagnoses included Wilms tumor, low-grade astrocytoma, and Burkitt’s lymphoma, respectively. We used whole-genome sequencing to profile normal cells from each family member and a linked-read technology for genomic phasing, which enabled us to identify compound-heterozygous and de novo variants in addition to simple-heterozygous and homozygous-alternate variants.

  Study EGAS00001005321

• Single Cell Genome Sequence for DLP+ library A95618B

  Single Cell Genome Sequence for Triple negative breast cancer patient-derived xenograft SA609 passage 3 on DLP+ library A95618B

  Dataset EGAD00001009316

• Single Cell Genome Sequence for DLP+ library A95628A

  Single Cell Genome Sequence for triple negative breast cancer patient SA1162SB on DLP+ library A95628A

  Dataset EGAD00001009319

• Single Cell Genome Sequence for DLP+ library A95629B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1051D passage 1 on DLP+ library A95629B

  Dataset EGAD00001009320

• Single Cell Genome Sequence for DLP+ library A95632A

  Single Cell Genome Sequence for immortalized breast epithelium - BRCA1-/- Tp53-/- cell line 184-hTERT-22 L9 83.86 on DLP+ library A95632A

  Dataset EGAD00001009321

• Single Cell Genome Sequence for DLP+ library A95632C

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA609 passage 6 on DLP+ library A95632C

  Dataset EGAD00001009322

• Single Cell Genome Sequence for DLP+ library A95634A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1091A passage 1 on DLP+ library A95634A

  Dataset EGAD00001009323

• Single Cell Genome Sequence for DLP+ library A95635A

  Single Cell Genome Sequence for immortalized breast epithelium - BRCA2-/-; Tp53-/- cell line 184-hTERT-22 L9 116.126 on DLP+ library A95635A

  Dataset EGAD00001009324

• Single Cell Genome Sequence for DLP+ library A95650A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1052J passage 1 on DLP+ library A95650A

  Dataset EGAD00001009325

• Single Cell Genome Sequence for DLP+ library A95652A

  Single Cell Genome Sequence for immortalized breast epithelium BRCA2+/- Tp53-/- cell line 184-hTert L9 116.66 on DLP+ library A95652A

  Dataset EGAD00001009326

• Single Cell Genome Sequence for DLP+ library A95652B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1049A passage 1 on DLP+ library A95652B

  Dataset EGAD00001009327

• 10x Genomics Single Cell Gene Expression for TOV2295(R)

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma cell line TOV2295(R)

  Dataset EGAD00001009158

• 10x Genomics Single Cell Gene Expression for SA1035X7XB03502

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 7

  Dataset EGAD00001009151

• 10x Genomics Single Cell Gene Expression for SA535X4XB02498

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 4

  Dataset EGAD00001009152

• 10x Genomics Single Cell Gene Expression for SA1035X5XB03021

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 5

  Dataset EGAD00001009153

• 10x Genomics Single Cell Gene Expression for SA1035X6XB03216

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 6

  Dataset EGAD00001009154

• 10x Genomics Single Cell Gene Expression for SA535X5XB02891

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 5

  Dataset EGAD00001009155

• 10x Genomics Single Cell Gene Expression for SA535X5XB02895

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 5

  Dataset EGAD00001009156

• 10x Genomics Single Cell Gene Expression for SA535X9XB03617

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 9

  Dataset EGAD00001009157

• 10x Genomics Single Cell Gene Expression for SA604X9XB02425

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA604 passage 9

  Dataset EGAD00001009159

• 10x Genomics Single Cell Gene Expression for SA610X3XB03802

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA610 passage 3

  Dataset EGAD00001009160

• cfDNA sWGS BAM — NSCLC stage I–III

  Plasma cfDNA sWGS for NSCLC patients (stage I–III), blood drawn pre-operatively, CHU Montpellier/LUNGDOC study. Libraries: DSP as recorded. Sequencing provider IntegraGen (2022–2024). Alignment to GRCh38 (hg38 canonical), BWA-MEM; BAMs sorted/indexed; only primary mapped reads retained (analysis pages list -F/MAPQ). Controlled access.

  Dataset EGAD50000001878

• WGS from 9 MPNSTs from 2 individuals, including relapses and metastasis. Data from Ortega-Bertran et. al.

  WGS from 2 individuals with MPNSTs. Multiple MPNSTs (independent tumor, relapses and metastasis) from each individual. Data from "Personalized Medicine Strategy for MPNSTs: Using Precision Oncology on PDOX Models to Inform Tumor Boards" by Ortega-Bertran et.al.

  Dataset EGAD50000002171

• Shallow Whole Genome Sequencing (sWGS) of pancreatic ductal adenocarcinoma

  Associated with CNA differences between RNA-based subtypes of PDAC. Shallow Whole Genome Sequencing (sWGS) generated 47 .bam files from 37 patients. sWGS was used for Copy number aberrations (CNA) determination.

  Dataset EGAD50000001732

• SMPaeds PanelSeq of tumour tissue

  Deep sequencing of a targeted panel of 92 paediatric cancer related genes or 233 pan-cancer related genes for both relapse/archival disgnostic tumour tissue and germline DNA from whole blood cell pellet. Tumour tissue was sequenced to approximately 400X coverage and germline DNA was sequences to aproximately 100X coverage.

  Dataset EGAD50000000783

• ATAC_TPO3_2023

  Human engineered CRC organoids (APC KO; KRAS G12D; TP53 KO) were grown in glucose, lactate or with DCA . Samples were collected and processed for bulk ATAC-seq.

  Dataset EGAD50000000088

• CITE-seq raw count matrix

  Raw count matrix for CITE-seq data of PBMC collected from 113 patients.

  Dataset EGAD50000000141

• Raw count matrix scRNA-seq

  Raw count matrix for scRNA-seq data of PBMC collected from 113 patients.

  Dataset EGAD50000000142

• H3K27ac HiChIP Dataset for 19 T-ALL patients and one normal control sample

  19 H3K27ac HICHIP from T-ALL patient samples and one healthy normal control sample. Reads were aligned to HG38 reference.

  Dataset EGAD50000000023

• Sequencing data for oesophageal and related samples - OACs release 3 (RNA)

  Dataset EGAD00001003900

• Single-cell RNA sequencing on 12346 single T cells from 14 non-small cell lung cancer (NSCLC) patients

  Deep single-cell RNA sequencing data for 12346 T cells from tumour, adjacent normal tissue and peripheral blood of treatment-naïve NSCLC patients

  Dataset EGAD00001003999

• Vγ9Vδ2-T cells in chronic lymphocytic leukemia patients and healthy controls

  RNA sequencing data from Vγ9Vδ2-T cells from chronic lymphocytic leukemia patients and age-mnatched healthy controls. Matched Vγ9Vδ2-T cell samples before and after expansion with autologous monocyte-derived dendritic cells for each donor are included.

  Dataset EGAD00001004325

• Sequencing data for CLL patients

  Single-cell RNA-sequencing and other genome-wide approaches were applied to a cohort of CLL patients receiving Venetoclax treatment to study mechanisms of resistance.

  Study EGAS00001005815

• BLUEPRINT Methylome saturation and COMET analysis of monocyte samples

  Bisulfite-Seq of CD14-positive, CD16-negative classical monocyte samples for methylome saturation and COMET analysis

  Dataset EGAD00001001261

• Normal brain controls for ICGC PedBrain DNA methylation sequencing

  DNA methylation profiling of 8 control samples from adult (4) and fetal brain (4)

  Dataset EGAD00001000952

• Single-cell Transcriptome for glioblastoma intra-tumoral heterogeneity

  Single-Cell RNA Sequencing of 355 cells isolated from 7 tissue fragments of 3 patients corresponding to locally adjacent tumor, multifocal with recurrence and sections segregated by a marker of tumor cellularity (5-ALA).

  Dataset EGAD00001002249

• Sequencing data for oesophageal samples - Killcoyne, Gregson et al (sWGS)

  Data supporting: "Genomic copy number predicts esophageal cancer years before transformation." Killcoyne, Gregson et al. sWGS data 1000 samples BAM files

  Dataset EGAD00001006033

• Sequencing data for oesophageal and related samples - Ococks, Frankell, Masque Soler et al (ctDNA)

  Data supporting: “Longitudinal tracking of 97 esophageal adenocarcinomas (EAC) using liquid biopsy sampling.” Ococks, Frankell, Masque Soler et al. ctDNA (BAM files) 333 samples

  Dataset EGAD00001006373

• Exome sequencing of DLBCL samples with PMBL GE signature

  Tumor exomes for 15 DLBCL samples with PMBL GE signature, with 6 matching normal exomes and 1 pooled normal exome.

  Dataset EGAD00001007006

• HV31 - MGI single-tube long fragment read (stLFR) linked-read sequencing

  MGI single-tube long fragment read (stLFR) linked-read sequencing data for individual HV31 generated using DNA from CD14+ monocytes, to a sequencing depth of ~51×.

  Dataset EGAD00001007045

• Enhancer profiling to identify identifies epigenetic markers of endocrine resistance in metastatic castration resistant prostate cancer patients

  ChIP-seq and matched input data of AR, FOXA1 and H3K27ac for mCRPC patient samples taken prior to and after treatment with AR targeted therapy

  Dataset EGAD00001008688

• Stereotyped subset CLL RNA-seq from 100 patient with CLL

  RNA-sequencing data for 100 stereotypes CLL subset cases. Illumina based short-read sequencing data from a 100 samples from patients with CLL. Oxford Nanopore Technologies long-read sequencing data from 5 samples from patients with CLL.

  Dataset EGAD00001009729

• WGS and WTS data for manuscript titled: Pathologist-initiated whole genome and transcriptome sequencing demonstrates diagnostic utility in resolving difficult-to-diagnose tumors

  Illumina platform sequencing of whole genome libraries prepared from normal and cancer samples and whole transcriptome libraries from cancer samples from 45 donors

  Dataset EGAD00001015615

• WGS dataset of Hepatoblastoma tumoroid biobank as a key resource for tumour genetics

  WGS dataset of Hepatoblastoma tumoroid biobank with WGS of tumor and matched tumoroids

  Dataset EGAD00001015671

• Intra-tumor heterogeneity and clonal evolution of papillary renal cell carcinoma

  Limited knowledge of intratumor heterogeneity (ITH), and clonal evolution of papillary renal cell carcinoma (pRCC) and rare kidney tumor subtypes hinders understanding of tumorigenesis and therapeutic efficacy. We conducted an integrative genomic and epigenomic ITH analysis and studied clonal evolutionary history of pRCC and rare kidney tumor subtypes. We dissected multiple consecutive samples from the center of the tumor towards the tumor's periphery, a normal sample ~5 cm distant from the tumor, and, where feasible, metastatic regions in the adrenal gland. Specifically, we performed 60X multi-region whole-genome sequencing (mWGS), both genome-wide methylation and SNP array profiling, and deep targeted sequencing (average 500X coverage) of 254 cancer driver genes (PMID:24390350). The study population comprises 39 patients with kidney cancers, including 23 with papillary type 1 (pRCC1), 12 with papillary type 2 (pRCC2), one of which also had areas of clear cell, and one each with collecting duct tumor (cdRCC), renal fibrosarcoma rSRC, mixed pRCC1/pRCC2, and an unclassified renal cancer with mixed features of pRCC2 and cdRCC. Based on DNA sample availability, we conducted whole genome sequencing (WGS) on 124 samples from 29 subjects, deep targeted sequencing on 139 samples from 38 subjects, SNP array genotyping on 101 samples from 38 subjects, and genome-wide methylation profiling on 139 samples from 28 subjects. All assays were performed on tumor, metastasis and normal tissue samples, with the exception of the SNP array genotyping, which was conducted only on tumor samples.

  Study phs001573