Multi region samples are collected from patients, with consent, immediately after resection of the tumour. Samples are digested and sorted using FACS as single cells into lysis buffer. Cells are then stored until further processing for G&T-seq. After sequencing, we will explore intra-tumour heterogeneity using computational approaches to integrate RNA and DNA data onto the tumour phylogeny This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ .
This dataset contains the RNA and ChIP Sequencing data from the study Kalirin-RAC controls nucleokinetic migration in ADRN-type neuroblastoma. The data is organized in 7 experiments which are divided by both sequencing technology or the application of siRNA or drug interventions (or lack thereof) on neuroblastoma cell lines. The experiment names and the file names have been chosen in each respective experiment to guide future users of the data to replicate the analyses in the manuscript.
Shallow targeted sequencing with 462 mRNA and 97 antibodies of AML patient’s bone marrow mononuclear cells from iliac crest aspirations from. Please note raw and integrated gene expression data, cell type annotation, metadata and dimensionality reduction are available as Seurat v3 objects through figshare. Access link is https://doi.org/10.6084/m9.figshare.14780127.v1 AMLQ4_SMK1 AML314 male AMLQ1_SMK2 AML116 female AMLQ3_SMK3 AML127 female AMLQ6_SMK4 AML183 male AMLQ2_SMK5 AML327 female AMLQ5_SMK6 AML334 male APLQ5_SMK7 APL124 male APLQ3_SMK8 APL142 male APLQ6_SMK9 APL218 female APLQ4_SMK10 APL147 male APLQ2_SMK11 APL223 female APLQ1_SMK12 APL224 female
Paired tumor and normal WGS of primary neuroblastomas. This is an update of the „Berlin Neuroblastoma Dataset” (EGAS00001004022). This data was used for the analysis of circular RNA expression and regulation in neuroblastoma.
This is the dataset of 16S data from mucosal biopsies.
Clinical & biomarker data from IMagyn050: treatment arm, treatment approach, outcome of surgery, ECOG PS, PD-L1 status, race, age, disease stage, progression free survival (investigator assessed), overall survival, histology, tumor mutation burden and status, genomic loss of heterozygosity, microsatellite status, BRCA1/2 mutation status, tissue of origin. Mutation status based on FoundationOne NGS for the following genes is also being provided: TP53, BRCA1, CCNE1, MYC, NF1, PIK3CA, RAD21, TERC, PRKCI, KRAS, RB1, BRCA2, ARID1A, AKT2, PTEN, KDM5A, NOTCH3, FGF12, ERBB2, CDK12, EMSY, WHSC1L1, BCL2L1, CDKN2A, GNAS, ARFRP1, ZNF217, SOX2, CCND2, FGF6, FGF23, LYN, MUTYH, AURKA, FGFR1, MCL1, MLL2, MYCL1, ZNF703, BRAF, MAP2K4, CREBBP, TSC2
RRBS data from TRACERx non-small cell lung cancer (NSCLC) tumours and matched normal adjacent tissue. TRACERx (TRAcking Cancer Evolution through therapy (Rx)) is a prospective cohort study designed to investigate intratumor heterogeneity (ITH) in relation to clinical outcome, and to determine the clonal nature of driver events and evolutionary processes in early stage non-small cell lung cancer (NSCLC).
This dataset consists of 39 noncancerous donor and 62 cancer patient plasma samples (including 29 patients with CRC across a total of 13 tumor types) that were analyzed with the PGDx elio plasma resolve assay. The PGDx elio plasma resolve assay is a hybrid capture approach targeting 33 genes with sequencing performed using the Illumina NextSeq with 150bp paired-end reads. The bam files provided have been adapter masked and contain duplicate reads.
Single-cell whole transcriptome sequencing data for bone marrow samples from 9 cases with clonal hematopoiesis and 4 control samples. The TARGET-seq+ protocol was used to generate plate-based 3' transcriptome data. For details on cell sorting and the TARGET-seq+ protocol see the methods section of the manuscript. One FASTQ file is provided per cell. Cells are named with their plate and well IDs and the subject ID. Empty wells (no-cell controls) are named "blank". Corresponding genotyping files use the same naming without the "_transcriptome" suffix.
Cancer cells display heterogeneous and dynamic states in glioblastoma, but how these malignant states arise and whether they follow a tractable cellular trajectory across tumours is poorly understood. Here, we generate a deep single cell and spatial multi-region atlas of 12 isocitrate dehydrogenase wild-type (IDH-wt) primary glioblastomas that integrates transcriptomic, epigenomic and genomic analysis to comprehensively characterise their tumour heterogeneity. The datasets in this study include sequencing data from Visium spatial transcriptomic (10x Genomics) profiling of these tumours. Note: 2 new samples were added to the dataset on 2026-05-19.
