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• Systematic comparative analysis of single-nucleotide variant detection methods from single-cell RNA sequencing data

  In this study, we performed systematic comparative analysis of seven widely-used SNV-calling methods, including SAMtools, the GATK Best Practices pipeline, CTAT, FreeBayes, MuTect2, Strelka2 and VarScan2, on both simulated and real single-cell RNA-seq datasets. We generated SMART-seq2 data for 70 CD45- single cells, which were derived from two colorectal cancer patients (P0411 and P0413). The average sequencing depths of these cells were 1.4 million reads per cell. We also generated tumor and adjacent normal bulk WES data, as well as tumor bulk RNA-seq data for these patients.

  Dataset EGAD00001005373

• Three large nuclear families in which a single child per family was diagnosed with cancer

  We collected saliva samples from three nuclear families having 4, 5, and 7 children, respectively. One child in each nfamily had been diagnosed with a pediatric tumor, and neither parent had been diagnosed with cancer. Diagnoses included Wilms tumor, low-grade astrocytoma, and Burkitt’s lymphoma, respectively. We used whole-genome sequencing to profile normal cells from each family member and a linked-read technology.

  Dataset EGAD00001007709

• Tumor and normal exomes for 95 PMBCL cases

  Whole-exome sequencing for 95 PMBCL cases (including 21 with matching normal DNA) was performed using a targeted capture approach with the SureSelect Human All Exon V6+UTR bait (Agilent Technologies) followed by massively parallel sequencing of enriched fragments on the HiSeq2500 platform (Illumina). Five libraries were pooled per lane and a 125bp paired-end mode was used. Tumor and normal DNA samples were sequenced to an average of 115X (SD 24X). All reads were aligned to the human reference genome (hg19) using bwa-mem version 0.7.5a29 with optical and PCR duplicates removed using the Picard tool.

  Dataset EGAD00001005780

• AVENIO Expanded ctDNA panel sequence alignments (BAMs) from plasma DNA of BC, CRC and NSCLC patients

  The AVENIO ctDNA Expanded Kit is a next-generation sequencing (NGS) liquid biopsy assay with a 77 gene panel (192 kb) containing genes in U.S. National Comprehensive Cancer Network (NCCN) Guidelines and emerging cancer biomarkers. This pan-cancer assay was applied to 48 plasma samples from patients with breast, colorectal and non-small cell lung cancer. After sequencing 150bp paired-end, reads were aligned to the hg38 genome with the AVENIO Oncology Analysis Software (version 2.0). These files are the deduplicated alignments generated by the analysis software used for subsequent variant, indel and CNV calling.

  Dataset EGAD00001006301

• Paired RNA-Seq of 32 samples of chemo-naïve and post-chemotherapy PDAC tumors

  Paired RNA-Seq of 32 samples of chemo-naïve and post-chemotherapy PDAC tumors (HIPO_015) to define the molecular and cellular impact of neoadjuvant chemotherapy. Transcriptome analysis combined with high resolution mapping of whole tissue sections identified GATA6 (Classical), KRT17 (Basal-like) and Cytochrome P450 3A (CYP3A) co-expressing cells that were preferentially enriched in post-CTX resected samples. The sequencing was done on HiSeq2000/HiSeq2500 using the Takara_SMARTer_Ultra_Low_Input_RNA_and_NEBNext_ChIP-Seq Kit.

  Dataset EGAD00001010884

• Chordoma Sequencing Project Whole Genome

  This is a continuation of the Chordoma Sequencing Project. All cancers arise due to somatically acquired abnormalities in DNA sequence. Systematic sequencing of cancer genomes allows acquisition of complete catalogues of all classes of somatic mutation present in cancer. These mutation catalogues will allow identification of the somatically mutated cancer genes that are operative and characterise patterns of somatic mutation that may reflect previous exogenous and endogenous mutagenic exposures. In this application, we aim to perform whole genome sequencing on 10 chordoma matched genome pairs. RNA Sequencing/Methylation and SNP6 and an additional sequencing of three cancer cell lines will be added to this work.

  Dataset EGAD00001000721

• Detection of clinically relevant genetic and transcriptomic landscape in DLBCL uniformly treated by R-CHOP

  Recent studies using next-generation sequencing strategies have described the landscape of genetic alterations in diffuse large B-cell lymphoma (DLBCL). However, little is known about the clinical relevance of recurrent mutations and copy number alterations and their transcriptional footprints. This study examines the frequency, interaction and clinical impact of recurrent genetic aberrations in DLBCL using high-resolution technologies in a large population-based cohort.

  Dataset EGAD00001003783

• PRDM9 loss of function follow up from Born-in-Bradford Autozygosity sequencing

  In the autozygosity exome sequencing of Born-in-Bradford samples of Pakistani origin there is a mother who is homozygous for an apparent truncating stop codon in PRDM9, the gene responsible for localising recombination during meiosis. We plan to deep sequence mother and child with X10, and physically phase the mother with PacBio sequencing. We will use this data to identify recombination locations, and test whether these are consistent with the known fine scale recombination map. Data Access is controlled by the Wellcome Trust Sanger Institute DAC and the Born In Bradford Executive Group.

  Dataset EGAD00001001686

• Epi2Diag

  Genomic DNA was extracted from whole blood and bisulfite converted using the EZ DNA Methylation Lightning Kit (Zymo research). DNA methylation profile was then derived using Illumina’s Infinium EPIC array v2.0. in accordance with the manufacturer’s protocol at the ASGARD-Rouen genomic platform (Inserm U1245, University of Rouen and Rouen University Hospital, Rouen France) on an Illumina NextSeq550 scanner.

  Study EGAS00001008070

• scRNA-Seq & scATAC-Seq Feature-counting Results Derived from 10X Cellrange-arc-count pipeline

  The feature-counting outputs from Cellrange-arc-count pipeline contain information at the single cell level, jointly for both scRNA-Seq and scATAT-Seq on 103 DLBCL samples and 3 normal controls (Please note that sc-40 only has scRNA-Seq data without scATAC-Seq). These files can be used as the input files for further downstream analysis software (e.g. Seurat Package). Moreover, a matrix of single-cell barcodes and associated cell biological types (used in the study) is also provided for users’ reference. This dataset is large and split into two parts to facilitate downloads.

  Dataset EGAD50000002490