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• DAC for DNA methylation data (iMED, BCG prime, and 500FG)

  Dac EGAC00001003534

• human biopsies

  DAC for human samples derived from biopsies from patients with hydrocephaly.

  Dac EGAC50000000625

• CoV2 challenge data

  Repository containing the transcriptomic data for the CoV2 challenge study

  Dac EGAC50000000391

• H3N2 challenge data

  Repository containing the transcriptomic data for the H3N3 challenge study

  Dac EGAC50000000379

• Validation of cfDNA fragmentome analyses for early detection of liver cancer

  Study EGAS00001008111

• Exome

  Exome Seq for EGAS00001001845

  Dataset EGAD00001002160

• The Genomic Landscape of Interval Colorectal Cancers

  Interval colorectal cancers (CRC), cancers diagnosed after a screening/surveillance exam in which no cancer is detected, and before the date of the next recommended exam, reflect an unprecedented challenge in CRC detection and prevention. To better understand this poorly characterized CRC variant, we examined the clinical and mutational characteristics of interval CRCs in comparison to screen-detected CRCs. We used data from the Prostate, Lung, Colorectal and Ovarian (PLCO) cancer randomized controlled trial (RCT) of flexible sigmoidoscopy (FS) screening, which enrolled 154,900 men and women aged 55 to 74 years between 1993 and 2001. Whole Exome Sequencing (WES) was performed on 323 samples from 168 participants (data available through dbGaP). We found colorectal cancers diagnosed between screening exams (interval cancers) had significantly increased risk of death than screen detected cancers although no significant molecular differences were observed between screen-detected and interval CRC at the whole exome sequencing level.

  Study phs003093

• Using NGS to Sequence Whole Genomes to Identify Genes Underlying ALS

  Our ALS Consortium - a partnership of clinicians, basic scientists, geneticists, and computational biologists from 48 institutions (4 of which are industry partners) across 5 countries - establishes a framework to apply whole genome sequencing (WGS) and functional genomics to the study of amyotrophic lateral sclerosis (ALS). Because ALS-causing mutations tend to be of moderate impact and are relatively rare in the population (reviewed in Al-Chalabi et al., 2017, PMID: 27982040), identification of new mutations require several thousand samples, which need to be obtained from multiple sites (even the busiest ALS clinics see only 200-400 patients per year). ALS Consortium is using genomics technologies to study the causes and mechanisms underlying neurodegenerative disease, and the contribution of various cell types within the brain and spinal cord. Much of this work is done and continues to be done in collaboration with the members of the NYGC ALS Consortium.

  Study phs003067

• Somatic_mutation_and_clonal_evolution_normal_breast_tissue_WGS

  Cancer is a genetic disease caused by an accumulation of mutations, however many of these mutations have been identified in pathologically normal tissue. We aim to use laser-capture microscopy (LCM) to sample individual clones from breast tissue to identify whether cancer-associated mutations appear in this normal tissue, assess the mutational burden present, and identify the mutational processes causing these mutations. We will sample from a wide age range of individuals (<20 to >70 years old) to determine whether these processes differ in pre- and post-menopausal women. We will also be comparing the tissue from healthy individuals (samples from breast reduction surgery) to those at elevated risk of breast cancer (mastectomy from BRCA1/2 patients) and those who have breast cancer (adjacent normal, distal normal, and tumour tissue from mastectomy). This will allow us to determine how these processes are different between these groups of individuals, and gain insight into the earliest stages of tumour development.

  Study EGAS00001002857

• MutWP5__CRUK_Mutographs_of_Cancer__Breast__Reduction_Mammoplasty___WG__Novaseq_

  Cancer is a genetic disease caused by an accumulation of mutations, however many of these mutations have been identified in pathologically normal tissue. We aim to use laser-capture microscopy (LCM) to sample individual clones from breast tissue to identify whether cancer-associated mutations appear in this normal tissue, assess the mutational burden present, and identify the mutational processes causing these mutations. We will sample from a wide age range of individuals (<20 to >60 years old) to determine whether these processes differ in pre- and post-menopausal women. We will also be comparing the tissue from healthy individuals (samples from breast reduction surgery) to those at elevated risk of breast cancer (mastectomy from BRCA1/2 patients) and those who have breast cancer (adjacent normal, distal normal, and tumour tissue from mastectomy). This will allow us to determine how these processes are different between these groups of individuals, and gain insight into the earliest stages of tumor development.

  Study EGAS00001003524