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• CRISPR iPSC methods paper

  This submission is of the sequencing data used in the CRISPR iPSC methods paper. Specifically it is 3 fastq files that each represent a replicate of an experiment to transduce the Toronto KnockOut CRISPR Library - Version 3 (TKOv3) into inferred pluripotent stem cell (iPSC) derived macrophages. The sequencing is of the guide RNAs from the TKOv3 having been extracted from the transduced iPSC derived macrophages.

  Dataset EGAD00001007020

• PIAMA nasal RNAseq dataset

  This study included nasal gene expression data collected from nasal brushes of adolescents in PIAMA birth cohort, which is used in the project Nasal DNA methylation at three CpG sites predicts childhood allergic disease. 186 samples were included in this analysis, and phenotypes (age and sex) were provided together with a gene expression count table. Gene expression was measured by the Illumina HiSeq2500 sequencer.

  Dataset EGAD00001008767

• Human and rat skeletal muscle multiomic profiling sequencing data

  Illumina sequencing data (fastq files) representing single-nucleus (sn) ATAC-seq, snRNA-seq, bulk ATAC-seq, and snATACseq+snRNAseq multiomics data from human and rat skeletal muscle samples (19 libraries total). Includes a README file that describes the relationship between libraries, samples, and files.

  Dataset EGAD00001008323

• Sequence-based gene expression in uterine and ovarian carcinosarcomas

  Gynecologic carcinosarcomas (CS), including more generally uterine (endometrial) and less frequently ovarian localization, are histologically defined as biphasic neoplasms composed of carcinomatous (C) epithelial and sarcomatous (S) malignant components. We report a comprehensive analysis of 20 patients of macro-dissected samples of C and S components through RNA sequencing.

  Dataset EGAD00001009099

• ctDNA whole exome genome sequencing dataset

  Dataset contains all available exome sequencing paired-end fastq files from our study "A generalizable machine learning framework for classifying DNA repair defects using ctDNA exomes"

  Dataset EGAD00001010069

• RNA sequencing of high-risk paediatric cancers for identifying T-cell infiltration signatures

  Transcriptome profiling of 121 high-risk paediatric cancer samples for identifying T-cell infiltration signatures using poly-A capture by Truseq and sequenced on NextSeq 500

  Dataset EGAD00001010920

• Targeted DNA sequencing on bulk bone marrow and peripheral blood

  Targeted DNA sequencing was performed on 195 bone marrow samples to identify cases of clonal haematopoiesis, and on 99 paired peripheral blood samples. The SeqCap EZ HyperCap protocol was followed, and targeted capture performed against a panel of 97 genes recurrently mutated in myeloid malignancies and clonal hematopoiesis. One BAM file (mapped to the hg38 reference genome) is provided per sample.

  Dataset EGAD00001011083

• 47 urothelial cancer patients WES and 38 RNAseq

  We performed a global mutational landscape analysis using tumor samples from the 47 urothelial cancer patients included in MATCH-R or MOSCATO studies, with advanced metastatic disease and WES available (RNAseq is included for 38 patient samples).

  Dataset EGAD00001011063

• Exome Atlas in HCC tumors

  The atlas provides a comprehensive exploration of genetic and transcriptomic landscapes within HCC, offering insights into key genomic alterations and gene expression patterns. The integration of exome sequencing and RNAseq data enhances our understanding of the molecular complexity underlying HCC, potentially paving the way for targeted therapeutic strategies and biomarker discovery in the context of hepatocellular carcinoma.

  Dataset EGAD00001015342

• WGS dataset for Unraveling mutagenic processes influencing the tumor mutational patterns of individuals with Constitutional Mismatch Repair Deficiency

  Molecular characterization of 41 tumors from 17 individuals with CMMRD to gain a better understandig of mutational processes driving subsequent tumor development. The molecular characterization includes the investigation of tumor mutational load and mutational signatures.

  Dataset EGAD00001015157