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• The evolutionary landscape of colorectal tumorigenesis

  The genetic events that cause colorectal adenomas to progress to carcinomas remain largely undetermined. Using multi-region genome/exome sequencing of 24 benign and malignant colorectal tumours, we probe the evolutionary fitness landscape occupied by these neoplasms. Unlike carcinomas, advanced adenomas frequently harbour sub-clonal driver mutations, hence lack selective sweeps, and have relatively high genetic heterogeneity. Carcinomas are distinguished from adenomas not by nucleotide-level mutations (drivers or burden), but by widespread aneusomies that are usually clonal and often accrue in a “punctuated” fashion. Adenomas evolve across an undulating fitness landscape, whereas carcinomas occupy a sharper fitness peak, probably owing to stabilising selection.

  Study EGAS00001003066

• Investigating genomic intratumor heterogeneity in colorectal carcinoma

  To investigateintertumor heterogeneity of colorecatal carcinoma, we profiled the genome and epigenome in multiple regions within each of nine colorectal tumors.

  Study JGAS000060

• Multiple Myeloma GWAS Meta-analysis

  Meta-analysis of Multiple Myeloma genome-wide association study datasets. Included are meta-analyses with and without the UK Biobank dataset.

  Study EGAS50000000292

• CIRCLE-seq of PDO

  CIRCLE-seq data of PDAC 1 patient-derived organoid (PDO) - Unmapped reads, libraries were sequenced using the Illumina NextSeq500 with the NextSeq 500/550 Mid Output Kit v2.5 (300 Cycles), generating around 10M paired end 150bp reads per sample

  Dataset EGAD50000000281

• COIN_CRC_GWAS

  Genotype data of 1,950 individuals from the COIN and COIN-B trials of advanced/metastatic colorectal cancer. Data provided in plink format, and has been quality controlled. Control data used was from the WTCCC2 project National Blood Donors (NBS) Cohort (EGAD00000000024).

  Dataset EGAD00010002186

• The genomic landscape of cutaneous squamous cell carcinoma based on 40 paired normal and tumour whole-exome sequencing samples

  40 paired normal and tumour whole-exome sequencing samples was used to investigate the genomic landscape of cutaneous squamous cell carcinoma

  Dataset EGAD00001003555

• Genomic variant calling of 32 Chinese SRCCs

  Whole Genome Sequencing has been applied in 32 SRCC patients and the raw data have been subjected to standard procedures. Files with genomic variant calling were obtain at the last step.

  Dataset EGAD00001004045

• ChIP-seq and Hodgkin lymphoma

  ChIP-seq data (H3K4Me3, H3K27Ac histone modifications) of Hodgkin lymphoma cell line L-428. Samples were processed as previously described (Sud et al., 2018). The files are in bam format, aligned to build 37 of the human genome.

  Dataset EGAD00001004322

• Dataset of CageKid Blood and Tumor DNA samples

  The data contains genome sequencing of clear cell renal cell carcinomas and normal kidney tissues. The samples were collected from patients from different European countries.

  Dataset EGAD00001002892

• RNA-Seq studies of Gene Expression in Cells and Networks in FI and ACC in Autism

  RNA-Seq studies of Gene Expression in Cells and Networks in FI (fronto-insular) and AC (anterior cingulate) cortex in Autism. We seek to understand the cellular bases of autism by using a new technology, RNA-Seq, to determine differences in gene expression in autopsy brains of subjects with well described autism versus age and sex matched neurotypical individuals. We have investigated two specific cortical areas involved in self-awareness and social reciprocity which are abnormal in autism and have found increased expression in a network of genes related to inflammation in autism group A, whereas the remaining cases, autism group B, have increased expression in a network of genes related to synapses. The current dbGaP study release includes RNA sequencing and phenotype data of n=27 subjects of African - American, Caucasian, or Hispanic origin.

  Study phs000609