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• WGS_of_Somatic_Mosaicism_of_BRCA1_Methylation_in_Malignant_and_Nonmalignant_Breast_Tissue

  WGS of Somatic Mosaicism of BRCA1 Methylation in Malignant and Nonmalignant Breast Tissue

  Study EGAS00001008235

• EMseq_of_Somatic_Mosaicism_of_BRCA1_Methylation_in_Malignant_and_Nonmalignant_Breast_Tissue

  EMseq of Somatic Mosaicism of BRCA1 Methylation in Malignant and Nonmalignant Breast Tissue

  Study EGAS00001008236

• Methylation profiles in blood (breast cancer cases)

  Raw methylation data from blood samples in breast cancer cases.

  Dataset EGAD00010002470

• Aneuploidy_and_human_development

  We will investigate the transcriptomic consequences of copy number changes in human development.

  Study EGAS00001005267

• 46 VCF files of glioma patient 2021

  the source data in VCF format of 46 patients primary malignant glioma cohort in Chinese population

  Dataset EGAD00001008115

• STAG1 and STAG2-ChIP-seq in RAD21-mutant adult acute myeloid leukemia

  STAG1 and STAG2-ChIP-seq in RAD21-mutant adult acute myeloid leukemia

  Dataset EGAD00001015361

• Array data for oesophageal and related samples - aks_paper_methyl_barretts_release

  Array data for oesophageal and related samples - aks_paper_methyl_barretts_release

  Dataset EGAD00010001972

• BMI EWAS summary stats

  Summary statistics for a multi-cohort epigenome-wide association study. This includes summary statistics (effect-size, standard error, p-value) for 470,000 methylation markers.

  Dataset EGAD00010001029

• An evaluation of different strategies for large-scale pooled sequencing study design.

  An evaluation of different strategies for large-scale pooled sequencing study design.

  Dataset EGAD00001000037

• Validation_for_human_early_embryonic_substitutions_

  PCR and MiSeq validation for early embryonic substitution candidates from 400 Breast cancer patients

  Study EGAS00001001218

• PACA-CA Whole Genome Sequence bam files

  Merged bam files for PACA-CA Whole Genome Sequencing, for DCC release 25

  Dataset EGAD00001003591

• Acute myeloid leukemia sequencing data

  This study contains tumor DNA and RNA sequencing data for 1 AML patient

  Study EGAS00001006354

• Glioma sequencing data

  This study contains sequencing data for various glioma subtypes (astrocytoma, glioblastoma, diffuse midline glioma).

  Study EGAS00001006355

• DATA FILES FOR SJCPC-WGS

  DATA FILES FOR SJCPC-WGS

  Dataset EGAD00001001065

• Exome Sequencing

  Exome sequencing of for 10 patients: 10 tumors, 10 cell lines and 7 blood samples (for 3 patients blood was not available)

  Dataset EGAD00001002690

• Dataset for "Intratumoral Heterogeneity and Clonal Evolution Induced by HPV Integration" (pacBio)

  Dataset for "Intratumoral Heterogeneity and Clonal Evolution Induced by HPV Integration" (pacBio)

  Dataset EGAD00001009631

• RNA-Seq for academic use only

  RNA-Seq transcriptome data is only for academic use.

  Dataset EGAD00001009675

• Dataset for "Intratumoral Heterogeneity and Clonal Evolution Induced by HPV Integration" (ONT)

  Dataset for "Intratumoral Heterogeneity and Clonal Evolution Induced by HPV Integration" (ONT)

  Dataset EGAD00001009632

• Dataset for iAMP21 scRNA-seq

  10x Genomics 5' library scRNA-seq data for 4 iAMP21 patients

  Dataset EGAD00001009504

• Whole exome sequencing data for paired non-serous endometrial and ovarian carcinomas from 27 patients with concurrent tumours.

  Dataset for Synchronous Endometrial and Ovarian Cancer

  Dataset EGAD00001015680

• Analysis of genes related to the oncogenesis, progression or effectiveness of drug therapies of urological tumors .

  To clarify the oncogenesis and the progression mechanism of urological tumors, we continuously collect tumor samples of our patients with high quality. Then we used them to comprehensive analyses such as genome sequencing or epi-genome sequencing. Through these analyses, we aim for elucidating the oncogenesis or for developing newly treatment strategies of each cancer.

  Study JGAS000737

• Analysis of genes related to the oncogenesis, progression or effectiveness of drug therapies of urological tumors .

  To clarify the oncogenesis and the progression mechanism of urological tumors, we continuously collect tumor samples of our patients with high quality. Then we used them to comprehensive analyses such as genome sequencing or epi-genome sequencing. Through these analyses, we aim for elucidating the oncogenesis or for developing newly treatment strategies of each cancer.

  Study JGAS000303

• Analysis of genes related to the oncogenesis, progression or effectiveness of drug therapies of urological tumors .

  To clarify the oncogenesis and the progression mechanism of urological tumors, we continuously collect tumor samples of our patients with high quality. Then we used them to comprehensive analyses such as genome sequencing or epi-genome sequencing. Through these analyses, we aim for elucidating the oncogenesis or for developing newly treatment strategies of each cancer.

  Study JGAS000564

• SECRETO Oral metagenome study

  The main goal of the project is to study the associations between the oral metagenome and young-onset cryptogenic ischemic stroke (CIS). The dataset includes information for n=329 participants who underwent saliva sampling. Participants for the SECRETO Oral study were enrolled between December 2013 and November 2019. Shotgun metagenomic sequencing was performed using the Illumina NovaSeq 6000 platform.

  Study EGAS00001007505

• Labcorp® Plasma Detect™ assay: whole genome sequencing analyses of plasma cfDNA, white blood cells and FFPE tumor tissue

  The dataset "Labcorp® Plasma Detect™ assay: whole genome sequencing analyses of plasma cfDNA, white blood cells and FFPE tumor tissue" includes CRAM and CRAI files derived from WGS of 555x plasma cfDNA, 209x white blood cells (normal DNA) and 209x FFPE tumor tissue (tumor DNA) samples for 209 stage III colorectal cancer patients. WGS (150bp PE) was performed on a NovaSeq 6000 with a target depth of coverage of 80x for tumor DNA, 40x for normal DNA and 30x for cfDNA. Reads were aligned to GRCh37 (plasma cfDNA) or GRCh38 (tumor/normal DNA).

  Dataset EGAD50000001180