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• This study generated Oxford Nanopore long read sequencing data of cancer cell line mixtures for validating long-read variant calls in cancer genomics

  Long-read sequencing (LRS) improves genome alignment and facilitates resolving variants in complex genomic regions, making it a promising approach for cancer variant detection and biomarker discovery. Here, we evaluate the performance of LRS to detect somatic variants across different tumour purities and sequencing depths by comparing to somatic variants from short-read sequencing. We generated experimental mixtures of cancer cell lines and matched normal cell lines to simulate 10 tumour purities (ranging from 0 to 100% tumour content). This resulted in 22 samples which were sequenced using whole genome LRS to a targeted depth of 60x and somatic variants were identified. We downsampled sequencing data to explore the optimal read depth for somatic variant detection. Our results show that long-read variant calling tools achieve recall rates comparable to short-read gold standards. While a tumour sequencing depth of 30x to 60× is generally sufficient for detecting common variants, particularly structural variants (SVs), sequencing the matched normal sample at adequate depth is crucial for accuracy. Notably, we found variants unique to LRS that may represent real and previously undetected events. This study highlights key factors for optimising cancer genome sequencing with LRS and provides a comprehensive dataset of cell line mixtures for future research and tool development.

  Study EGAS00001008107

• SNP_array

  33 ETMR samples were genotyped using Illumina HumanOmni2.5M array. Hybridization and scanning was done according to the manufacturer's instructions (Illumina). Copy number (Log R) and B allele frequency estimates were obtained sing the Genotyping module (v1.9.4) in GenomeStudio v2011.1 (Illumina). Normalized and log2-transformed copy number measurements were imported from genomestudio and analysed using R package CopyNumber to identify segments with similar copy number.

  Dataset EGAD00010001667

• NSCCG_CRC_GWAS

  Genotype data of 7,281 individuals with colorectal cancer from the National Study of Colorectal Cancer Genetics (NSCCG) study. Individuals genotyped on the Illumina OncoArray. Data provided in plink format and has not been quality controlled. Control samples used were obtained from the PRACTICAL and BCAC consortia, and are available through the respective Data Access Coordination Committees (http://practical.icr.ac.uk and http://bcac.ccge.medschl.cam.ac.uk/)

  Dataset EGAD00010002184

• DNA sequences from adolescent and young adult patients with melanoma treated with immunotherapy

  Sequencing libraries were prepared and barcoded using the unique molecular identifier and index tagging following the VariantPlex Somatic Protocol (ArcherDx). Pool-library was loaded at 1.2 pM concentration with 20% PhiX and paired-end sequencing was performed using the NextSeq 500 Illumina sequencer using 300 cycle high output reagent kit.

  Dataset EGAD50000000353

• Etiology of congenital thyroid dysfunction in Down Syndrome: a multi-omics investigation

  The goal of this study was to investigate dfiferences in the thyroid DNA methylome and transcriptome between fetuses with Down syndrome and fetuses with no genetic/developmental abnormality.

  Study EGAS50000000264

• TallFlow - multi-omics

  Single-cell Immune profiling 10X genomics protocol. This data includes 5' mRNA sequencing, TCR sequencing, and 204 AB sequencing. In total 15 pediatric T-ALL samples and 4 pediatric Thymus samples.

  Study EGAS50000000358

• Deciphering novel TCF4-driven mechanisms underlying a common triplet repeat expansion-mediated disease

  short and long read data generated from cultured corneal endothelial cells (CECs) of unaffected controls, expansion positive Fuchs Endothelial Corneal Dystrophy (FECD) and expansion negative FECD individuals.

  Study EGAS50000000303

• Single-cell RNA-sequencing on malignant and benign tissue samples

  Single-cell RNA-sequencing on malignant and benign tissue samples from untreated donors with colorectal adenocarcinoma and liver metastasis was performed in order to deduce tissue adaptive expression patterns of the disease. Matching tissue from five donors with untreated CRC and liver metastasis were sampled.

  Dataset EGAD50000001203

• DAC of "Gene expression adaptation of metastases to their host tissue"

  The DAC consists of Prof. Axel Hillmer, University of Cologne, Faculty of Medicine and University Hospital Cologne, Institute of Pathology, Cologne, Germany, e-mail: ahillmer@uni-koeln.de and Prof. Andreas Beyer, University of Cologne, Faculty of Mathematics and Natural Sciences, Cologne Excellence Cluster for Aging and Aging-Associated Diseases (CECAD), Cologne, Germany, e-mail: andreas.beyer@uni-koeln.de

  Dac EGAC50000000514

• Scalable ultra-high-throughput multiplexed single-cell chromatin and RNA profiling reveals gene regulatory dynamics during stimulation time courses and CRISPR perturbation screens

  Data for 1) hiPSC-derived macrophages across a polarization time course from the naive M0-state to the M1- and M2-states, 2) Primary T-cells differentiated to helper subtypes, and 3) spontaneous differentiation of hiPSCs upon perturbation of GATA2, NR4A2 or SOX17

  Dac EGAC50000000485