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• Multi-region RNA sequencing of tumour regions and tumour-adjacent normal lung 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).

  Study EGAS00001006517

• Tracing early predictors of glioma evolution under therapy

  Clonal evolution drives cancer progression and therapeutic resistance. Recent studies revealed divergent longitudinal trajectories in gliomas, but early molecular traits steering post-treatment cancer evolution remain unclear. We analyzed sequencing data of 544 initial-recurrent adult diffuse glioma pairs to identify genomic and transcriptomic early predictors of tumor evolution in each molecular subtype.

  Study EGAS00001006894

• Oesophageal_Adenocarcinoma_Organoid_PacBio

  PacBio Sequencing of 6 patient derived organoid cell models. Each model was derived from a piece of patient tumour taken following surgical resection of the tumour. All model derivations took place with the CGaP facility in Sanger. This PacBio data will be combined with other sequencing data in order to generate accurate reference cancer genomes.

  Study EGAS00001007163

• Relapse series of two Pediatric ALL patients

  In this proof of principle study, we performed whole genome sequencing of two cases with multiple relapses in order to investigate whether groups of mutations separated in time show distinct mutational signatures. In patient 1, who experienced two relapses, the analysis unraveled a continuous interplay of aberrant AID/APOBEC-associated activities. Patient 2 had three relapses. We identified episodic mutational processes at diagnosis and first relapse leading to mutations resembling UV light-driven DNA damage, and thiopurine-associated damage at first relapse.

  Dataset EGAD00001006948

• Ither NB in Organoids RNA-Seq dataset - Exploring high-throughput drug sensitivity testing in neuroblastoma cell lines and patient-derived tumor organoids in the era of precision medicine

  Ither NB in Organoids RNA-Seq dataset - We aimed to launch an online repository integrating genomics and transcriptomics with high-throughput drug screening (HTS) of nineteen commonly used neuroblastoma cell lines and fourteen generated neuroblastoma patient-derived organoids (NBL-PDOs) to improve identification of molecularly matched therapies and support clinical uptake.

  Dataset EGAD00001010283

• Transcriptomic Analysis of HIV-Infected Cells

  Defining the attributes of rare CD4 T cells that harbor latent HIV under therapy with anti-retroviral agents has been challenging due to difficulties in identifying and isolating these cells. These cells represent an important barrier to cure, and characterizing them would aid the design and development of novel HIV cure strategies. In this study, we addressed this challenge using a custom microfluidic technology named Focused Interrogation of cells by Nucleic acid Detection and Sequencing (FIND-seq) that isolates HIV-infected cell transcriptomes, based on HIV DNA detection. We applied this method to HIV DNA+ memory CD4 T cells isolated from blood from five persons with HIV who were receiving anti-retroviral agents. After curating samples based on data quality, we proceeded with bioinformatics analysis from three persons. This analysis identified six transcriptomic pathways that were inhibited in HIV DNA+ cells compared to HIV DNA- cells. These included death receptor signaling, necroptosis signaling, and anti-proliferative G-alpha12/13 signaling. Furthermore, we identified two gene clusters, including 60 and 85 genes, that were significantly associated with HIV DNA+ cells identified by co-expression network analysis. These genes included negative regulators of HIV transcription that were higher in HIV DNA+ cells, positive regulators of HIV transcription that were lower in HIV DNA+ cells, and other genes involved in the negative regulation of mRNA translation, additional RNA processing functions, and the regulation of cellular state and fate. We further examined these signatures in transcriptomic data from CD4 T cell subsets sorted by flow cytometry from nine persons with HIV. We found a partial similarity between the smaller cluster of genes and the signature of CCR6- peripheral TFH cells. Raw sequencing data from all eleven human participant samples included in the study are available. These include samples from two participants who were studied only by FIND-seq, three participants who were studied by both FIND-seq and flow cytometry and six participants who were studied only by flow cytometry.

  Study phs003095

• Genetic variation in Kuusamo

  Genetic variation in Kuusamo

  Dataset EGAD00001000055

• Targeted re-sequencing of 97 genes in T-ALL

  Targeted re-sequencing of 97 genes in T-ALL

  Dataset EGAD00001000150

• BAP1_sequence_of_uveal_melanoma_cell_lines

  Detection of BAP1 mutations in DNA from 3 uveal melanoma cell lines.

  Study EGAS00001001520

• Somatic_mutation_in_edited_cholangiocyte_organoids_WGS

  Characterisation of mutation rates and patterns in edited human cholangiocyte organoids (WGS)

  Study EGAS00001006326

• McGill EMC Release 4 in tissue "kidney"

  McGill EMC Release 4 in tissue "kidney"

  Dataset EGAD00001001287

• FUNGAL INFECTION IN NEURAL TISSUE FROM AMYOTROPHIC LATERAL SCLEROSIS

  Sequence data from fungal infection isolated from neural tissue in ALS patients.

  Dataset EGAD00001003341

• Framome cancer samples

  Cancer samples for neo-open reading frame peptides that comprise the tumor framome are a rich source of neoantigens for cancer immunotherapy.

  Dataset EGAD50000000420

• Central Africa whole genome sequencing (rainforest hunter-gatherers and neighboring populations)

  High-coverage (>30X) whole genome data (FASTQ) for 29 central African rainforest hunter-gatherer individuals (from five populations) and for 20 central African rainforest hunter-gatherer neighbor individuals (from four populations).

  Dataset EGAD50000001560

• Single Cell Genome Sequence for DLP+ library A95670B

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA501 passage 6 on DLP+ library A95670B

  Dataset EGAD00001009449

• A98168B

  Whole genome sequencing for single cells for library A98168B 1290 cells; filetype=bam

  Dataset EGAD00001007625

• A98256B

  Whole genome sequencing for single cells for library A98256B 1437 cells; filetype=bam

  Dataset EGAD00001007125

• A95703A

  Whole genome sequencing for single cells for library A95703A 740 cells; filetype=bam

  Dataset EGAD00001007612

• 10x Genomics Single Cell Gene Expression for SA535X6XB03099

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 6

  Dataset EGAD00001009116

• 10x Genomics Single Cell Gene Expression for SA535X4XB05462

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 4

  Dataset EGAD00001009115

• A95653B

  Whole genome sequencing for single cells for library A95653B 1342 cells; filetype=bam

  Dataset EGAD00001007107

• 10x Genomics Single Cell Gene Expression for SA535X6XB03101

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 6

  Dataset EGAD00001009149

• 10x Genomics Single Cell Gene Expression for SA535X5XB02891

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 5

  Dataset EGAD00001009155

• 10x Genomics Single Cell Gene Expression for SA535X5XB02895

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 5

  Dataset EGAD00001009156

• 10x Genomics Single Cell Gene Expression for SA604X9XB02425

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA604 passage 9

  Dataset EGAD00001009159

• 10x Genomics Single Cell Gene Expression for SA535X4XB02498

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 4

  Dataset EGAD00001009152

• A96179B

  Whole genome sequencing for single cells for library A96179B 1396 samples; filetype=bam

  Dataset EGAD00001008245

• A96180B

  Whole genome sequencing for single cells for library A96180B 1189 samples; filetype=bam

  Dataset EGAD00001008246

• A118833A

  Whole genome sequencing for single cells for library A118833A 919 cells; filetype=bam

  Dataset EGAD00001007096

• A118833B

  Whole genome sequencing for single cells for library A118833B 1147 cells; filetype=bam

  Dataset EGAD00001007097

• 10x Genomics Single Cell Gene Expression for SA1053EX1XB01608

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1053 passage 1

  Dataset EGAD00001009123

• Hospital for Sick Children 2020 Pediatric Low-Grade Glioma RNA and Targeted DNA Sequencing

  Whole transcriptome and targeted dna sequencing (Ampliseq) of pediatric low-grade glioma samples at the Hospital for Sick Children

  Dataset EGAD00001005987

• A118862B

  Whole genome sequencing for single cells for library A118862B 1152 cells; filetype=bam

  Dataset EGAD00001007606

• A98271A

  Whole genome sequencing for single cells for library A98271A 1190 cells; filetype=bam

  Dataset EGAD00001007633

• Dataset for transcriptome sequencing of forebrain organoids from Lissencephaly patients

  This dataset contains transcriptome sequencing for 16 samples of forebrain organoids from Lissencephaly patients. The sequencing was performed on Illumina NextSeq 6000 . The sequencing was always paired.

  Dataset EGAD00001015688

• RNA-seq data from paired tumour and germline samples from mesothelioma patients for study EGAS00001005196

  RNA-seq data from paired tumour and germline samples from mesothelioma patients for study EGAS00001005196

  Dataset EGAD00001007874

• 10x Genomics Single Cell Gene Expression for SA1053BX1XB01603

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1053 passage 1

  Dataset EGAD00001009131

• 10x Genomics Single Cell Gene Expression for SA1047BX1XB01022

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1047 passage 1

  Dataset EGAD00001009146

• 10x Genomics Single Cell Gene Expression for SA1056

  10x Genomics Single Cell Gene Expression for Telomerase immortalized breast epithelium cell line 184-hTERT-22 L9 116.126

  Dataset EGAD00001009112

• 10x Genomics Single Cell Gene Expression for SA604X6XB01979

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA604 passage 6

  Dataset EGAD00001009117

• 10x Genomics Single Cell Gene Expression for SA604X7XB02089

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA604 passage 7

  Dataset EGAD00001009119

• 10x Genomics Single Cell Gene Expression for SA609X6XB01899

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA609 passage 6

  Dataset EGAD00001009120

• 10x Genomics Single Cell Gene Expression for SA1050DX1XB01437

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1050 passage 1

  Dataset EGAD00001009126

• 10x Genomics Single Cell Gene Expression for SA1181AX1XB02700

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1181 passage 1

  Dataset EGAD00001009135

• 10x Genomics Single Cell Gene Expression for SA1162BX1XB03004

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1162 passage 1

  Dataset EGAD00001009138

• 10x Genomics Single Cell Gene Expression for SA605X3XB01966

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA605 passage 3

  Dataset EGAD00001009142

• 10x Genomics Single Cell Gene Expression for SA1035X7XB03502

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 7

  Dataset EGAD00001009151

• 10x Genomics Single Cell Gene Expression for SA610X3XB03802

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA610 passage 3

  Dataset EGAD00001009160

• 10x Genomics Single Cell Gene Expression for SA1050EX1XB01442

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1050 passage 1

  Dataset EGAD00001009141

• 10x Genomics Single Cell Gene Expression for SA1035X6XB03216

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 6

  Dataset EGAD00001009154