4955 results for "*oma"

in 53.08 milliseconds.

• H3K27ac/H3K27me3 landscape of medulloblastoma

  We profiled 111 patient medulloblastoma primary tumor samples by bulk RNA-seq (19 samples), 27ac (98 samples) / 27me3 (61 samples) ChIP-Seq, WGS (4 samples) and 27ac hichip (8 samples). Submitted data consists of data generated from previously unpublished tumors as well as complementary data for data sets already published for identical medulloblastoma tumors (ex: 27me3 ChIP-Seq and RNA-Seq data submitted for a tumor with publicly available WGS data). The raw fastqs and hg19 aligned RNA-Seq bams are provided.

  Dataset EGAD00001009709

• Healthy controls of Iberian Roma population

  Paired end FASTQ files of 119 Iberian Roma whole exome sequence data (Illumina sequencing)

  Dataset EGAD00001009722

• Paired RNA-Seq of four patients with advanced Parathyroid carcinoma (PC)

  Paired RNA-Seq of four patients with advanced Parathyroid carcinoma (PC). The library was prepared using the Illumina TruSeq stranded mRNA Kit, the sequencing was done either on an Illumina HiSeq 4000 or on Illumina NovaSeq 6000.

  Dataset EGAD00001009730

• Paired WGS data of four patients with advanced Parathyroid carcinoma (PC)

  Paired WGS data of four patients with advanced Parathyroid carcinoma (PC). There are tumor/control pairs (buffy coat control). The library was prepared with Illumina TruSeq Nano DNA, the sequencing was done with HiSeq X Ten.

  Dataset EGAD00001009731

• Longitudinal evaluation of serum microRNAs as biomarkers for neuroblastoma burden and therapeutic p53 reactivation

  Small RNA sequencing data (TruSeq small RNA library preparation kit v2) from serum samples and tumor tissue of orthotopically injected mice (SH-SY5Y cell line) and unengrafted mice, treated with idasanutlin, temsirolimus and vehicle control.

  Dataset EGAD00001009625

• Whole genome sequencing and somatic mutation profiles and whole genome transcription files of pediatric medulloblastoma

  Fastq, Mutect (SNVs), Platypus (indels), and InfoGenomeR (SVs and CNAs) calls from whole genome sequencing data and fastq files of whole genome transcription data of five patients with pediatric medulloblastoma.

  Dataset EGAD00001009507

• Long-read sequencing for cell-free DNA analysis (human pacbio)

  8 pregnant women at the 3rd trimesters, 4 hepatitis B carriers, and 4 patients with hepatocellular carcinoma

  Dataset EGAD00001009427

• Single Cell Genome Sequence for DLP+ library A108765A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1181A passage 1 on DLP library A108765A

  Dataset EGAD00001009428

• Single Cell Genome Sequence for DLP+ library A108847B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1182E passage 1 on DLP+ library A108847B

  Dataset EGAD00001009429

• Single Cell Genome Sequence for DLP+ library A96207B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1052B passage 1 on DLP+ library A96207B

  Dataset EGAD00001009474

• Single Cell Genome Sequence for DLP+ library A96210B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient SA1047B on DLP+ library A96210B

  Dataset EGAD00001009475

• Single Cell Genome Sequence for DLP+ library A96222A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient SA1105, patient SA1103, patient SA1106, patient SA1104 on DLP+ library A96222A

  Dataset EGAD00001009478

• Single Cell Genome Sequence for DLP+ library A98243B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient SA1096A, patient-derived xenograft SA1052D passage 1 on DLP+ library A98243B

  Dataset EGAD00001009481

• Tracking the evolution of esophageal squamous cell carcinoma under dynamic immune selection by multi-omics sequencing

  Intratumoral heterogeneity (ITH) has been linked to decreased efficacy of clinical treatments. However, although genomic ITH has been characterized in genetic, transcriptomic and epigenetic alterations are hallmarks of esophageal squamous cell carcinoma (ESCC), the extent to which these are heterogeneous in ESCC has not been explored in a unified framework. Further, the extent to which tumor-infiltrated T lymphocytes (TILs) are directed against cancer cells, but how the immune infiltration acts as a selective force to shape the clonal evolution of ESCC is unclear. In this study, we perform multi-omic sequencing on 186 samples from 36 primary ESCC patients. Through multi-omics analyses, it is discovered that genomic, epigenomic, and transcriptomic ITH are underpinned by ongoing chromosomal instability. Based on the RNA-seq data, we observe diverse levels of immune infiltrate across different tumor sites from the same tumor. We reveal genetic mechanisms of neoantigen evasion under distinct selection pressure from the diverse immune microenvironment. Overall, our work offers an avenue of dissecting the complex contribution of the multi-omics level to the ITH in ESCC and thereby enhances the development of clinical therapy.

  Dataset EGAD00001009482

• Single Cell Genome Sequence for DLP+ library A98279A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1050A passage 1, patient SA1234 on DLP+ library A98279A

  Dataset EGAD00001009486

• Single Cell Genome Sequence for DLP+ library A95717B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1050D passage 1 on DLP+ library A95717B

  Dataset EGAD00001009489

• Oxford Nanopore Technologies (ONT) long-read sequencing in a paired diagnostic and post- therapy medulloblastoma

  Oxford Nanopore Technologies (ONT) long-read sequencing in a paired diagnostic and post- therapy medulloblastoma (2 samples). One sequencing was done on GridION, the other one on a P2 Solo. In both cases the SQK LSK-109 Kit was used for preparation.

  Dataset EGAD00001009490

• Paired-end RNA-seq analysis of the 3D evolution of glioma cell populations. Part 2.

  Dataset contains paired-end RNA-seq sequencing data from 221 glioma samples.

  Dataset EGAD00001009497

• Paired-end Whole Exome-seq analysis of the 3D evolution of glioma cell populations. Part 2.

  Dataset contains paired-end Whole Exome sequencing data from 257 glioma samples from 28 patients. 26 normal blood samples are also included.

  Dataset EGAD00001009496

• Myeloid-specific KDM6B inhibition sensitizes Glioblastoma to PD1 blockade

  This data set include FASTQ files for five experiments: Human scRNA-Seq data (6 samples), Human Visium spatial transcriptomic data (3 samples), Mouse scRNA-seq data (4 samples), Mouse scATAC-seq data (2 samples), Mouse ChIP-seq data (8 samples). For the mouse scATAC-seq data (2 samples), there are originally three FASTQ files, R1, R2 and R3 files. The R1 and R2 FASTQ files were merged into one larger file ("R1R2") per sample for submission as paired-end sequencing setting to follow the EGA guidelines. They can be split into individual R1 and R2 files in order to be processed by Cell Ranger software. The files with IC1 suffix are CHIP-seq Input control for anti-KDM6B antibody pull down experiments and the files with IC2 suffix are CHIP-seq Input control for anti-H3K27ME3 antibody pull down experiments in murine model.

  Dataset EGAD00001010073

• An IL-1β driven neutrophil-stromal cell axis fosters a BAFF-rich microenvironment in multiple myeloma

  This depository contains data from two bulk RNA sequencing experiments: 1) Bulk RNA sequencing data of peripheral blood neutrophils from healthy donors cultured with a) human adipose-derived stromal cells (ADSC) as a model for mesenchymal stromal cells (MSC), and b) IL-1β stimulated ADSC as a model for inflammatory MSC as found in multiple myeloma (MM). 2) Bulk RNA sequencing data from ADSCs cultured a) without stimuli, b) with recombinant human IL-1β, c) with supernatant from iMSC-like cells, d) with neutrophils previously cultured with MSC, e) with neutrophils previously cultured with iMSC, f) with neutrophils previously cultured with iMSC in the presence of anti-human IL-1β or g) with neutrophils previously cultured with iMSC in the presence of an isotype control.

  Dataset EGAD00001010080

• Single-cell RNA and DNA sequencing data obtained after genome-and-transcriptome separation.

  This dataset contains single-cell RNA and DNA sequencing data (fastq, n=928) obtained after genome-and-transcriptome separation. The RNA-seq data was obtained by Smart-seq2 amplification and Nextera XT library preparation. The DNA-seq data was obtained either by Gtag library preparation and amplification or by PicoPlex whole-genome amplification followed by Nextera XT library preparation. The single cells originate from a human PDX melanoma model and from HCC38 and HCC38 BL cell lines. The sequencing libraries were sequenced with Illumina instruments.

  Dataset EGAD00001010096

• VRK3 depletion in Pontine Diffuse Midline Glioma DMG-K27 altered cells

  In order to investigate possible mechanisms underlying the phenotype of cell fitness decline observed following decrease of VRK3 in pontine DMG-K27 altered cells 7, we examined differences in global gene expression. RNA-seq was performed 44h and 60h post-transduction with two distinct shRNAs targeting VRK3 to be able to evaluate the early impact of VRK3 knock-down (KD) in four independent in vitro models of DMG

  Dataset EGAD00001010097

• Whole genome, exome and RNA sequencing of TFCP2-rearranged rhabdomyosarcoma

  Whole genome, exome and RNA sequencing of TFCP2-rearranged rhabdomyosarcoma, 86 samples of paired fastq files, sequenced on: Illumina HiSeq 2500 using Agilent SureSelect WGS, Illumina HiSeq 2500 using Illumina TruSeq RNA, Illumina HiSeq 2500 using Agilent SureSelect v5 WES (+UTRs), Illumina HiSeq 4000 using Agilent SureSelect WGS, Illumina HiSeq 4000 using Illumina TruSeq stranded mRNA Kit, Illumina HiSeq 4000 using Agilent SureSelect v5 WES stranded mRNA Kit, Illumina NovaSeq 6000 using Illumina TruSeq Stranded mRNA, Illumina NovaSeq 6000 using Illumina TruSeq Nano DNA, Illumina HiSeq X Ten using TruSeq Nano DNA.

  Dataset EGAD00001010108

• Genomics of acral lentiginous melanoma

  Melanoma is the most aggressive type of skin cancer, causing about 75% of dermatological cancer deaths. Acral lentiginous melanoma (ALM) is the most common subtype of melanoma in admixed Latin American populations, but very few tumour genomes and exomes, all from European-descent individuals, have been analysed across several studies. Because of this, the genomic landscape of ALM is mostly unknown. Our aim in this project is to define this landscape and identify driver somatic alterations by whole-exome sequencing a collection of ALM germline/tumour paired FFPE samples from the National Cancer Institute of Mexico. . This dataset contains all the data available for this study on 2023-03-09.

  Dataset EGAD00001010126

• Whole Genome Sequencing of Head and Neck Angiosarcoma

  This dataset contains 55 Whole Genome Sequencing of the study titled Spatial transcriptomics reveal topological immune landscapes of Asian head and neck angiosarcoma.

  Dataset EGAD00001010140

• Differential methylation positions

  This dataset includes an analyzed DMP file that provide the information about differential methylation positions based on Illumina Infinium MethylationEPIC BeadChip. All samples (5 lung cancer cases vs. 5 benign lung disease controls) were obtained from bronchial washings at the site of the lesion under bronchoscopy manipulation. Of the five lung cancer cases, 3 are adenocarcinoma and 2 are squamous carcinoma.

  Dataset EGAD00001010147

• Pharmacogenomic profiling reveals molecular features of chemotherapy resistance in IDH wild type primary glioblastoma

  We stratified 69 primary IDH-wt GBM patients into TMZ-resistant (n = 29) and sensitive (n = 40) groups, using TMZ screening of the corresponding patient-derived glioma stem-like cells (GSCs). Genomic and transcriptomic features were then examined to identify TMZ-associated molecular alterations. Subsequently, we developed a machine learning (ML) model to predict TMZ response from combined signatures. Moreover, TMZ response in multisector samples (52 tumor sectors from 18 cases) was evaluated to validate findings and investigate the impact of intra-tumoral heterogeneity on TMZ efficacy.

  Dataset EGAD00001010156

• Multiple myeloma follow-up Dataset

  77 samples collected from 35 multiple myeloma patients. Each patient provided one healthy sample and one primary tumor sample and, in some cases, also samples collected after the progression of the disease.

  Dataset EGAD00001010161

• Patient-derived GBM cultures TMZ+BMP4 treated

  Batch RNA sequencing of passages 5-7 of three patient-derived monolayer glioblastoma cultures in which TMZ and BMP4 synergize. 3 biological replicates, either untreated, only temozolomide, only BMP4 or temozolomide + BMP4

  Dataset EGAD00001010163

• WES and RNA-seq data of 11 cancer patients with multiple cancer types

  This dataset includes WES and RNAseq from 11 patients with metastatic melanoma, lung, kidney, and stomach cancers, enrolled in phase I clinical trials of TIL ACT (NCT03475134 & NCT04643574). WES was performed on matched cancer and healthy samples, whereas RNAseq was performed on cancer tissues, using Illumina HiSeq 2500/4000 and Illumina NextSeq 550 systems. Paired-end reads are provided in fastq format.

  Dataset EGAD00001010169

• Single cell epigenomic study of H3-K27M mutant diffuse midline glioma across age and location

  This dataset contains the open chromatin profiles of 8 patient H3-K27M mutant DMGs utilizing the single-cell/nucleus assay for transposase-accessible chromatin using sequencing (snATAC-seq)

  Dataset EGAD00001010170

• Paired RNA-Seq was performed on 125 samples of low grade pediatric glioma

  Paired RNA-Seq was performed on 125 samples of low grade pediatric glioma. The sequencing was done with Illumina Novaseq 6000 and the Illumina TruSeq stranded mRNA kit.

  Dataset EGAD00001010171

• Paired RNA seq of wild type VDH15 cells (3 replicates) - a cell line of oral squamous cell carcinoma (OSCC)

  Paired RNA seq of wild type VDH15 cells (3 replicates) - a cell line of oral squamous cell carcinoma (OSCC). RNA was extracted and sequencing libraries were prepared using TruSeq Stranded mRNA Library Prep Kit following manufacturer's protocol. The sequencing was done using Illumina Novaseq 6000.

  Dataset EGAD00001010172

• Platelets contain a repertoire of DNA fragments that map over the human nuclear genome, including tumour-derived DNA in patients with active malignancy.

  This dataset consists of WGS from six patients with a recent diagnosis of gastrointestinal adenocarcinoma. DNA-Seq libraries were prepared from platelet DNA (pDNA) and plasma cfDNA obtained from the same peripheral blood sample. pDNA was size selected into 2 groups (small, s-pDNA: less than 600 bp and long, b-pDNA: greater than 600 bp). The short fragments were further cleaned to remove <100 bp fragments and large platelet fragments were fragmented via sonication. Libraries were then prepared using the NEBNext Ultra II DNA Sample Preparation Kit for Illumina according to the manufacturer’s protocol and sequenced on an Illumina NextSeq 500 (300 cycle PE) at low-pass (0.1X) for all samples, and 10X for the cfDNA and s-pDNA, using four lanes in each sample.

  Dataset EGAD00001009856

• 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

• TK-EPN862 - Patient-derived xenograft model of Posterior Fossa A Ependymoma - RNAseq

  In Vivo Loss of Tumorigenicity in a Patient-Derived Orthotopic Xenograft Mouse Model of Ependymoma. Whitehouse et al. 2023 Frontiers in Oncology. We describe the establishment of a patient-derived orthotopic xenograft (PDOX) model of posterior fossa A (PFA) EPN, derived from a metastatic cranial lesion. Patient and PDOX tumors were analyzed using RNA sequencing. RNAseq data (paired end) provided here correspond to Primary tumour, two metastatic lesions (one spinal, one cranial), and a patient-derived xenograft derived from the patient.

  Dataset EGAD00001009870

• van Hijfte snRNA glioblastoma dataset

  van Hijfte snRNA glioblastoma dataset

  Dataset EGAD00001009871

• 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

• Bolleboom-Gao peri-tumoral snRNA-seq glioblastoma dataset 2022/A

  Bolleboom-Gao peri-tumoral snRNA-seq glioblastoma dataset 2022/A

  Dataset EGAD00001009964

• Genomic Analysis of a Metastatic Fusion-negative Embryonal Rhabdomyosarcoma

  Autopsy-derived, later snap-frozen tissue fragments from a 5-year-old female with recurrent metastatic fusion-negative embryonal rhabdomyosarcoma (RMS) primary tumor of the left thigh were analyzed. No quality matched tissue was available. Prior panel analysis identified 2 prominent genetic changes: NRAS Q61K, PIK3CA H1047R, CDKN2A/B loss, and ERBB3 overexpression.

  Dataset EGAD00001009973

• TK-EP862 - Patient-derived xenograft model of Posterior Fossa A Ependymoma - WSG data

  In Vivo Loss of Tumorigenicity in a Patient-Derived Orthotopic Xenograft Mouse Model of Ependymoma. Whitehouse et al. 2023 Frontiers in Oncology. We describe the establishment of a patient-derived orthotopic xenograft (PDOX) model of posterior fossa A (PFA) EPN, derived from a metastatic cranial lesion. Patient and PDOX tumors were analyzed using RNA sequencing. WSG data (paired end) provided here correspond to germline DNA, Surgical sample 4 (described in the above manuscript as a cranial metastasis of PFA ependymoma), and a patient-derived xenograft derived from the patient.

  Dataset EGAD00001010008

• RNA-sequencing data from vitamin C experiment

  Fasq-files from 3 unaffected TET2 mutation carriers, 2 mutation carriers diagnosed with lymphoma and 3 family members without TET2 mutation. Time series data collected from 0, 6 and 12 months after daily dose of 1g vitamin C.

  Dataset EGAD00001010009

• Human CCO+ liver mtDNA sequencing

  BAM files containing paired-end mtDNA sequencing data from morphologically normal human liver. CCO-proficient hepatocytes acquired from human livers in which clonal CCO-deficient hepatocyte patches had been previously identified. Individual BAM files are named according to their patch, line and sample location, where PT denotes tissue near to the portal triad (PT), central hepatic vein (CV) and midway between these two structures (Mid). "Stroma" control samples were used for identifying germ-line variants. Sequenced on NextSeq 500 platform.

  Dataset EGAD00001010016

• WGS data for HGSC patient derived organoids and matching tumor and normal samples (Wennerberg)

  Sequencing data of 10 high-grade serous carcinoma (HGSC) patients (58 samples including blood derived normal samples as germline controls, fresh frozen tissue samples as tissue controls and organoids) sequenced with HiSeq X Ten / BGISEQ-500 / MGISEQ-2000.

  Dataset EGAD00001010019

• scRNA-seq of total bone marrow and T cells from multiple myeloma long-term survivors

  scRNA This dataset contains 50 scRNA-seq samples from bone marrow aspirates of 11 multiple myeloma patients experiencing long-term survival and 3 healthy donors. For each donor, total bone marrow and CD3+ T cells were sequenced. For multiple myeloma patients, paired samples were collected at initial diagnosis and between 7-17 years after first-line therapy. Bone marrow mononuclear cells were isolated by Ficoll density gradient centrifugation. For sorting of total bone marrow cells singlet, live cells were gated and sorted, for sorting of T cells CD45+, CD3+ cells were gated and sorted on either FACSAria Fusion or FACSAria II. Single-cell RNA sequencing were generated using 10x Genomics single-cell RNAseq technology (Chromium Single Cell 3’ Solution v2) according to the manufacturer’s protocol and sequenced on an Illumina HiSeq4000 (paired end, 26 and 74 bp). Bulk RNA Singlet, live CD3+CD4- CXCR3+CD8+ and CD3+CD4- CXCR3-CD8+ cells were sorted from 7 bone marrow and 3 peripheral blood samples of 7 multiple myeloma patients using a FACSAria Fusion machine. Bulk-RNA sequencing libraries were generated using the SMART Seq Stranded Total RNA-Seq kit (Takara) and sequenced using the Illumina NovaSeq 6000 platform (2 x 100 bp).

  Dataset EGAD00001010025

• Gut microbiome from melanoma patients

  Metagenomics shotgun sequencing was conducted on fecal samples from the Australian patients enrolled in the OpACIN-neo clinical trial (n = 38). Metagenomic shotgun sequencing was performed utilizing the same DNA from the same preparations as for the 16S rRNA gene analysis. Individual libraries were prepared using Nextera XT, and sequencing was performed on the Illumina NovaSeq 6000 S1 (2 x 150bp; Xp workflow).

  Dataset EGAD00001010028

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 5)

  Whole genome sequencing data of 19 high-grade serous carcinoma (HGSC) patients (47 samples) sequenced with HiSeq X Ten.

  Dataset EGAD00001010029

• Neuroblastoma WGS dataset

  Dataset with whole-genome sequencing tumor and normal samples from 14 neuroblastoma patients.

  Dataset EGAD00001010030

• Germline variants in childhood melanoma

  Whole-exome sequencing was performed on DNA extracted from blood samples of 50 children diagnosed with cutaneous melanoma prior to 18 years of age. Patients were all diagnosed in Queensland, Australia, and self-reported as of European descent. Sequencing was done the Illumina platform using SureSelct V7 Post capture kits.

  Dataset EGAD00001010039

• Neuroblastoma deep-sequencing dataset part2

  Dataset including paired tumor-normal whole-genome deep-sequenced samples from 18 neuroblastoma patients (part 2 of a total of 36 patients).

  Dataset EGAD00001010063

• NEC

  This multi-centre, non-randomized, open-label, phase II trial (NCT03016338), assessed niraparib monotherapy (cohort 1, C1), or niraparib and dostarlimab (cohort 2, C2) in patients with recurrent serous or endometrioid endometrial carcinoma. The primary endpoint was clinical benefit rate (CBR). Secondary outcomes were safety and objective response rate (ORR). Translational research was an exploratory outcome. Potential biomarkers were evaluated in archival tissue by immunohistochemistry and next generation sequencing panel. Feasibility of liquid biopsy by ctDNA was assessed.

  Dataset EGAD00001010056

• Whole genome, RNA-seq and single-cell Multiome profile of multiple myeloma

  We analyzed multiple myeloma samples from two patients included in the observational prospective cohort MYRACLE before talquetamab treatment and after relapse. Five other myelomas from the same cohort were included for comparison. Normal plasma cells were also retrieved. All samples were analyzed by whole genome sequencing and single-nucleus Multiome, except one that could only be analyzed by bulk RNA sequencing.

  Dataset EGAD00001010057

• Neuroblastoma deep-sequencing dataset part 1

  Dataset including paired tumor-normal whole-genome deep-sequenced samples from 18 neuroblastoma patients (part1 of a total of 36 patients).

  Dataset EGAD00001010059

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 4)

  Whole genome sequencing data of 7 high-grade serous carcinoma (HGSC) patients (32 samples) sequenced with HiSeq X Ten.

  Dataset EGAD00001010066

• Colonbiome shot-gun metagenomics

  156 samples of shot-gun gut metagenomics, corresponding to 51 patients with CRCm 54 patients with adenoma, and 51 healthy controls

  Dataset EGAD00001010068

• RNASeq read files of glioblastoma PDX samples

  This dataset contains 46 fastq files of paired-end RNA sequencing of an Illumina®️ TrueSeq stranded mRNA library of 23 glioblasoma PDX samples.

  Dataset EGAD00001010196

• RCRF release 1

  exome data from leiomyosarcoma, large cell neuroendocrine carcinoma, and clear cell sarcoma

  Dataset EGAD00001010197

• RCRF release 1

  Transcriptome sequencing from the Rare Cancer Research Foundation: leiomyosarcoma, large cell neuroendocrine carcinoma, clear cell carcinoma

  Dataset EGAD00001010198

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0168_003

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0168_003 for Follicular lymphoma patient sample TFRI_Cont_3

  Dataset EGAD00001010205

• RCRF release 1

  Rare Cancer Research Foundation: leiomyosarcoma, large cell neuroendorcrine carcinoma, clear cell carcinoma

  Dataset EGAD00001010199

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 6)

  Whole genome sequencing data of 31 high-grade serous carcinoma (HGSC) patients (101 samples) sequenced with HiSeq X Ten and BGISEQ-500

  Dataset EGAD00001010202

• Spatial TCR sequencing in breast cancer

  Spatial characterization by TCR sequencing in tumor core and matched stroma in seven cases of triple negative breast cancer.

  Dataset EGAD00001010203

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0170_003

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0170_003 for Follicular lymphoma patient sample TFRI_Cont_5

  Dataset EGAD00001010207

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0167_003

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0167_003 for Follicular lymphoma patient sample TFRI_Cont_2

  Dataset EGAD00001010204

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0169_003

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0169_003 for Follicular lymphoma patient sample TFRI_Cont_4

  Dataset EGAD00001010206

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0171_003A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0171_003A for Follicular lymphoma patient sample TFRI_Cont_6

  Dataset EGAD00001010208

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0178_003A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0178_003A for Follicular lymphoma patient sample TFRI_Cont_8

  Dataset EGAD00001010209

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0183_003A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0183_003A for Follicular lymphoma patient sample TFRI_Cont_9

  Dataset EGAD00001010210

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0187_003A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0187_003A for Follicular lymphoma patient sample TFRI_Cont_10

  Dataset EGAD00001010211

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0188_003A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0188_003A for Follicular lymphoma patient sample TFRI_Cont_11

  Dataset EGAD00001010212

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0197_003A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0197_003A for Follicular lymphoma patient sample TFRI_Cont_12

  Dataset EGAD00001010213

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0198_003A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0198_003A for Follicular lymphoma patient sample TFRI_Cont_13

  Dataset EGAD00001010214

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0167_001

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0167_001 for Follicular lymphoma patient sample TFRIPAIR2_FL

  Dataset EGAD00001010215

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0168_001

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0168_001 for Follicular lymphoma patient sample TFRIPAIR3_FL

  Dataset EGAD00001010216

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0169_001

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0169_001 for Follicular lymphoma patient sample TFRIPAIR4_FL

  Dataset EGAD00001010217

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0170_001A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0170_001A for Follicular lymphoma patient sample TFRIPAIR5_FL

  Dataset EGAD00001010218

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0171_001A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0171_001A for Follicular lymphoma patient sample TFRI_Pair_6_FL

  Dataset EGAD00001010219

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0178_001A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0178_001A for Follicular lymphoma patient sample TFRIPAIR8_FL

  Dataset EGAD00001010220

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0183_001A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0183_001A for Follicular lymphoma patient sample TFRIPAIR9_FL

  Dataset EGAD00001010221

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0187_001A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0187_001A for Follicular lymphoma patient sample TFRIPAIR10_FL

  Dataset EGAD00001010222

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0188_001A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0188_001A for Follicular lymphoma patient sample TFRIPAIR11_FL

  Dataset EGAD00001010223

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0197_001A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0197_001A for Follicular lymphoma patient sample TFRIPAIR12_FL

  Dataset EGAD00001010224

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0198_001A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0198_001A for Follicular lymphoma patient sample TFRI_Pair_13_FL

  Dataset EGAD00001010225

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0167_002

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0167_002 for Diffuse large B-cell lymphoma patient sample TFRIPAIR2_DLBCL

  Dataset EGAD00001010226

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0168_002

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0168_002 for Diffuse large B-cell lymphoma patient sample TFRIPAIR3_DLBCL

  Dataset EGAD00001010227

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0169_002

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0169_002 for Diffuse large B-cell lymphoma patient sample TFRIPAIR4_DLBCL

  Dataset EGAD00001010228

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0170_002A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0170_002A for Diffuse large B-cell lymphoma patient sample TFRIPAIR5_DLBCL

  Dataset EGAD00001010229

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0171_002A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0171_002A for Diffuse large B-cell lymphoma patient sample TFRI_Pair_6_DLBCL

  Dataset EGAD00001010230

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0178_002A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0178_002A for Diffuse large B-cell lymphoma patient sample TFRIPAIR8_DLBCL

  Dataset EGAD00001010231

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0183_002A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0183_002A for Diffuse large B-cell lymphoma patient sample TFRI_Pair_9_DLBCL

  Dataset EGAD00001010232

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0187_002A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0187_002A for Diffuse large B-cell lymphoma patient sample TFRIPAIR10_DLBCL

  Dataset EGAD00001010233

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0188_002A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0188_002A for Diffuse large B-cell lymphoma patient sample TFRIPAIR11_DLBCL

  Dataset EGAD00001010234

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0197_002A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0197_002A for Diffuse large B-cell lymphoma patient sample TFRIPAIR12_DLBCL_rel

  Dataset EGAD00001010235

• 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 EGAD00001010316

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

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

  Dataset EGAD00001010317

• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

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

  Dataset EGAD00001010318

• Processed bam files for the whole exome sequencing of primary lung adenocarcinoma samples

  We performed single cell RNA sequencing (scRNA-seq) for 208,506 cells derived from 58 lung adenocarcinomas from 44 patients, which covers primary tumour, lymph node and brain metastases, and pleural effusion in addition to normal lung tissues and lymph nodes. The extensive single cell profiles depicted a complex cellular atlas and dynamics during lung adenocarcinoma progression which includes cancer, stromal, and immune cells in the surrounding tumor microenvironments.

  Dataset EGAD00001010320

• Paired diagnostic and relapse medulloblastoma sequencing

  Paired diagnostic and relapse medulloblastoma sequencing. Targetted panel sequencing (n=8 relapse, n=7 matched diagnostic). Whole exome sequencing (n=23 relapse, n=18 matched diagnostic). Capture using Agilent SureSelect.

  Dataset EGAD00001010321

• Whole exome and RNA sequencing data from urothelial bladder cancer patients treated with anti-PD-(L)1

  We have generated and analyzed genomic data from a cohort of metastatic urothelial carcinoma patients treated with ICI such as anti-PD-(L)1 monoclonal antibodies. The dataset contains whole exome sequencing data of 27 whole blood samples and 27 FFPE tumor samples. Further, it includes RNA sequencing data from 21 tumor samples. Following the RECIST criteria, 10 patients were classified as non-responders to the treatment, and 17 were responders. The dataset also contains a merged vcf file containing somatic mutations called by Strelka2 and Mutect2 following the gatk best practice pipeline.

  Dataset EGAD00001010324