The dataset consists of sequenced cell free DNA (cfDNA) samples from colorectal cancer patients. The samples were sequenced on an Illumina MiSeq machine using a custom amplicon sequencing approach. These amplicons were designed to cover the most common mutation hotspots in colorectal cancer. The data include 138 cfDNA samples from 34 different patients. For each patient several samples are available derived from blood drawn at different time points during treatment. In addition the data include samples from 22 histology slides and 30 samples derived from HT29/HCT116 cell lines that were used as controls.
Genomic libraries will be generated from total genomic DNA derived from 4000 samples with Acute Myeloid Leukaemia. Libraries will be enriched for a selected panel of genes using a bespoke pulldown protocol. 64 Samples will be individually barcoded and subjected to up to one lanes of Illumina HiSeq. Paired reads will be mapped to build 37 of the human reference genome to facilitate the characterisation of known gene mutations in cancer as well as the validation of potentially novel variants identified by prior exome sequencing.
RNA-sequencing (RNA-seq) was performed with RNA extracted from fresh-frozen human tumor tissue samples. cDNA libraries were prepared from poly-A selected RNA applying the Illumina TruSeq protocol for mRNA. The libraries were then sequenced with a 2 x 100bp paired-end protocol to a minimum mean coverage of 30x of the annotated transcriptome.
Whole Genome Sequencing Illumina HiSeq data from 20 men with prostate cancer. 20 samples were taken from primary tissue obtained at prostatectomy (target sequencing depth 50X) with matched blood control (target sequencing depth 30X). These were submitted for use in the ICGC Pan-Cancer Analysis of Whole Genomes project. Same raw data submitted in EGAD00001001116. As of September 2020, some of the studies using these data include: Wedge et al, Nature Genetics 2018 (PMID: 29662167) Pan-Cancer Analysis of Whole Genomes, Nature 2020 (PMID: 32025007)
Genomic libraries will be generated from total genomic DNA derived from 200+ patients with childhood Transient Myeloproliferative Disorder (TMD) and or Acute Megakaryocytic Leukemia (AMKL) as well some matched constitutional samples (n < 50). Libraries will be enriched for a selected panel of genes using a bespoke pulldown protocol. 96 Samples will be individually barcoded and subjected to up to two lanes of Illumina HiSeq. Paired reads will be mapped to build 37 of the human reference genome to facilitate the characterisation of known gene mutations in cancer as well as the validation of potentially novel variants identified by prior exome sequencing.
In this study, we aimed to identify somatic structural variation of T-cell acute lymphoblastic leukemias (T-ALLs_ from patient-derived xenografts (PDX) at the single-cell level. For this purpose, we performed strand-specific single-cell sequencing of PDX-derived T-ALL relapse samples from two juvenile patients (P1, P33). To validate structural variation detected via scTRIP, we profiled whole exome sequencing (WES) data from P33 (samples taken during initial disease, remission, relapse), and mate-pair sequencing data from P1 (relapse).
DEEP (German Epigenome Project) sequence data of following samples (Sequencing Types: Chip-Seq, WGBS-Seq, RNA-Seq, sncRNA-Seq, NOMe-Se, DNase-Seq): 41_Hf01_LiHe_Ct, 41_Hf02_LiHe_Ct, 41_Hf03_LiHe_Ct, 01_HepG2_LiHG_Ct1, 01_HepG2_LiHG_Ct2, 01_HepaRG_LiHR_D31, 01_HepaRG_LiHR_D32, 01_HepaRG_LiHR_D33, 43_Hm01_BlMo_Ct, 43_Hm03_BlMo_Ct, 43_Hm05_BlMo_Ct, 43_Hm03_BlMa_Ct, 43_Hm05_BlMa_Ct, 43_Hm03_BlMa_TO, 43_Hm05_BlMa_TO, 43_Hm03_BlMa_TE, 43_Hm05_BlMa_TE, 51_Hf01_BlCM_Ct, 51_Hf03_BlCM_Ct, 51_Hf04_BlCM_Ct, 51_Hf02_BlCM_Ct, 51_Hf05_BlCM_Ct, 51_Hf06_BlCM_Ct, 51_Hf06_BlCM_T1, 51_Hf06_BlCM_T2, 51_Hf03_BlEM_Ct, 51_Hf04_BlEM_Ct, 51_Hf02_BlEM_Ct, 51_Hf05_BlEM_Ct, 51_Hf06_BlEM_Ct, 51_Hf06_BlEM_T1, 51_Hf06_BlEM_T2, 51_Hf03_BlTN_Ct, 51_Hf04_BlTN_Ct, 51_Hf02_BlTN_Ct, 51_Hf05_BlTN_Ct, 51_Hf06_BlTN_Ct, 51_Hf06_BlTN_T1, 51_Hf06_BlTN_T2, 51_Hf07_BmTM4_Ct, 51_Hf08_BlTM4_Ct, 51_Hf08_BmTM4_SP1, 51_Hf08_BmTM4_SP2, 51_Hf05_BlTA_Ct, 44_Mm01_WEAd_C2, 44_Mm03_WEAd_C2, 44_Mm02_WEAd_C2, 44_Mm07_WEAd_C2, 44_Mm04_WEAd_C1, 44_Mm05_WEAd_C1
In this study a next-generation sequencing based method was applied to comprehensively screen for recurrent, disease-relevant copy number aberrations in a cohort of Hungarian patients. Diagnostic bone marrow samples from 260 children with B-cell acute lymphoblastic leukemia as well as 72 control samples and were investigated by digital multiplex ligation-dependent probe amplification using the disease-specific D007 probemix. Whole chromosome gains and losses, as well as subchromosomal copy number aberrations were simultaneously profiled.
Whole exome, RNA sequencing and TCR sequencing of organoid samples derived from TRACERx patients. The dataset also includes whole exome sequencing from the tumour samples from which the organoids were generated, as well as whole exome sequencing from PDX derived from said tumours.
Single cell sequencing will be carried out by multiome profiling (RNAseq and ATACseq). Additonal modalities may be examined. Spatial profiling may involve Visium, Curio and other technologies. This data set will feed into a larger analysis of the human lungs over development, that aims to detail all the cell types of the human lungs and airways and will extend current knowledge by providing chromatin accessibility data that will allow us to link GWAS data and identify regulatory networks and then compare these against fetal and adult data sets . This dataset contains all the data available for this study on 2025-10-02.
