Search Results - EGA European Genome-Phenome Archive

Whole genome sequencing and whole exome sequencing of DIPG tumors and matched normal tissue

Diffuse Intrinsic Pontine Glioma (DIPG) is a fatal brain cancer that arises in the brainstem of children with no effective treatment. To understand what drives DIPGs we integrated whole-genome-sequencing with methylation, expression and copy-number profiling.

Study EGAS00001000575

2018_ETO_WGS

This study includes 12 paired samples of Korean AML-ETO paitients.12 AML-ETO tumor samples are paired with each normal(Saliva or BM derived) sequencing data.The results of this WGS study were analyzed by Mutect and GATK for ranking germline variants and cancer variants to make mutational profile matrix.

Study EGAS00001002804

DKFZ-HIPO Project H021/NCT MASTER

Clinical genome and transcriptome sequencing in younger adults with advanced-stage cancer across all histologies: DKFZ-HIPO Project H021 (http://www.hipo-heidelberg.org/hipo2/index.php/menu-item-2/32-021-prospective-genetic-characterization-of-tumors-from-individual-patients-of-special-interest) / NCT MASTER (http://www.nct-heidelberg.de/forschung/nct-master.html)

Study EGAS00001000948

Cancer-Associated Mutations in Endometriosis without Cancer

Endometriosis, defined as the presence of ectopic endometrial stroma and epithelium, affects approximately 10% of reproductive-age women and can cause pelvic pain and infertility. Endometriotic lesions are considered to be benign inflammatory lesions but have cancerlike features such as local invasion and resistance to apoptosis

Study EGAS00001003576

2015_AML_ETO

This study includes 10 paired samples of 2015 Korean AML-ETO paitients.10 AML-ETO tumor samples are paired with each normal(Saliva or BM derived) sequencing data.The results of this WGS study were analyzed by Mutect and GATK for ranking germline variants and cancer variants to make mutational profile matrix.

Study EGAS00001002897

2015_AML_ETO_WGS_additional

This study includes 2 paired samples of 2015 Korean AML-ETO paitients. 2 AML-ETO tumor samples are paired with each normal(Saliva or BM derived) sequencing data.The results of this WGS study were analyzed by Mutect and GATK for ranking germline variants and cancer variants to make mutational profile matrix.

Study EGAS00001002898

Somatic mutation and clonal evolution in the human bladder Novaseq (2020-05-05)

In this study, we aim to characterise the landscape of mutation and clonal selection in the human bladder. The data in this study will be generated by whole-genome sequencing of laser-dissected microbiopsies from the bladder. The samples utilised in this study will include urothelium from transplant donors with no history of bladder cancer and cystectomy specimens from patients with bladder cancer. . This dataset contains all the data available for this study on 2020-05-05.

Dataset EGAD00001006116

Early breast cancer (WES)

Whole-exome sequencing of 30 early breast cancer samples.

Dataset EGAD00001007057

Somatic mutation and clonal evolution in the human bladder_WES (2020-05-05)

In this study, we aim to characterise the landscape of mutation and clonal selection in the human bladder. The data in this study will be generated by whole-exome sequencing of laser-dissected microbiopsies from the bladder. The samples utilised in this study will include urothelium from transplant donors with no history of bladder cancer and cystectomy specimens from patients with bladder cancer. . This dataset contains all the data available for this study on 2020-05-05.

Dataset EGAD00001006115

MutWP5: CRUK Mutographs of Cancer: Breast: Reduction Mammoplasty (WG)

Sequencing of LCM-derived microbiopsies from 10 women who underwent reduction mammoplasty. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this portion of the study will be compared to women who had breast cancer and those who are BRCA 1/2 carriers. This dataset contains all the data available for this study on 2023-03-08.

Dataset EGAD00001010109

February 2020 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

February 2020 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

Dataset EGAD00001006220

December 2016 data update (bam/fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

December 2016 data update (bam/fastq for WGBS on samples CEMT0062, CEMT0068, CEMT0072, CEMT0086, CEMT0087) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

Dataset EGAD00001003122

FFPE, buffycoat and cell free DNA from N. German esophagus cancer patients - 2021

28 patients. Cell-free DNA and leukocyte DNA, both from before any neoadjuvant treatment. Tumor FFPE tissue (plus metastasic tissue for some patients) from after any neoadjuvant treatment. Some cfDNA from follow-up time points (e.g. after neodj. treatment or in the clinical course). IDT xgen Pan-Cancer panel for hybridisation capture. Illumina TruSeq library prep for cfDNA and leukocyte DNA, Illumina DNA Prep for FFPE DNA. n=150 libraries in total.

Dataset EGAD00001010081

WGS and WES of 78 pairs Chinese gastric cancer

Gastric Cancer (GC) is a highly heterogeneous disease. To identify potential clinically actionable therapeutic targets that may inform individualized treatment strategies, we performed whole-exome sequencing on 78 GCs of differing histologies and anatomic locations, as well as whole-genome sequencing on two GC cases, each with 3 primary tumours and 2 matching lymph node metastases. The data showed two distinct GC subtypes with either high-clonality (HiC) or low-clonality (LoC).

Dataset EGAD00001001118

March 2016 update of Whole genome bisulfite sequencing assay data (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

March 2016 update of Whole genome bisulfite sequencing assay data (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

Dataset EGAD00001001957

March 2016 update of whole genome shotgun sequencing data (bam/fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

March 2016 update of whole genome shotgun sequencing data (bam/fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

Dataset EGAD00001001958

Somatic mutation and clonal evolution in the human bladder_WGS (2020-05-05)

In this study, we aim to characterise the landscape of mutation and clonal selection in the human bladder. The data in this study will be generated by whole-genome sequencing of laser-dissected microbiopsies from the bladder. The samples utilised in this study will include urothelium from transplant donors with no history of bladder cancer and cystectomy specimens from patients with bladder cancer. . This dataset contains all the data available for this study on 2020-05-05.

Dataset EGAD00001006113

How to encrypt files with Crypt4gh

File preparation Due to the processes used at the EGA for file archival the use of non-alphanumeric characters in a filename will cause issues in archival. By convention whitespaces in filenames are to be avoided and should be replaced with the underscore character (_). Before encrypting your files please make sure that any files that will be uploaded to EGA do not use special characters such as # ? ( ) [ ] / \ = + < > : ; " ' , * ^ | & Crypt4gh EGACryptor Files encrypted with Crypt4gh must be uploaded via INBOX Before uploading If you are not a registered EGA user, you will first need an EGA user account. Please note that it may take a few days for your account to be activated, as it needs to be vouched for by the EGA Helpdesk. Once your account is validated you will be able to request a submitter role. Meanwhile, you can create and add your public key to your EGA account profile. This option is not available for old submission accounts (e.g. ega-box-NNN). As soon as you have been granted a submitter role, you will be able to connect with your username and password to the EGA inbox using the SFTP protocol. If you have also registered a public key in your profile, you can also connect using this key. Encrypting your files Please note that you can also encrypt your files by uploading them directly to the "to-encrypt" folder in your upload area If your connection is unstable, please encrypt them using Crypt4gh The EGA encryption of this inbox is based on Crypt4GH. You can install a python implementation of it, with pip install crypt4gh or directly from the Github repository pip install git+https://github.com/EGA-archive/crypt4gh.git Save now the following Crypt4GH public key, into a file, say ingestion.pubkey. __EGA_INGESTION_PUBKEY__ Encrypt a given file with the following command: crypt4gh encrypt --recipient_pk ingestion.pubkey < file_to_encrypt > encrypted_file.c4gh The command reads the file from stdin (with < ) and output the encrypted version to stdout (with > ). Replace file_to_encrypt and encrypted_file.c4gh with the appropriate filenames but make sure to not use the same filename for both reading and writing because your SHELL would then truncate both files before you even read or write.

Documentation submission/data/file-preparation/crypt4gh

Ludwig Center for Cancer Genetics and Therapeutics at Johns Hopkins

Dac EGAC00001000507

Data access committee for study - The subclonal architecture of metastatic breast cancer: Results from a prospective community-based rapid autopsy program "CASCADE".

Dac EGAC00001000574

15041 results for "cancer studies using rna-seq"

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