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1,174 results for “cancer genomics”
Mitochondrial genome sequencing of marine leukemias reveals cancer contagion between clam species in the Seas of Southern Europe
<p>Clonally transmissible cancers are tumour lineages that are transmitted between individuals via the transfer of living cancer cells. In marine bivalves, leukemia-like transmissible cancers, called hemic neoplasias, have demonstrated the ability to infect individuals from different species. We performed whole-genome sequencing in eight <i>V. verrucosa</i> clams that were diagnosed with hemic neoplasia, from two sampling points located more than 1,000 nautical miles away in the Atlantic Ocean and the Mediterranean Sea Coasts of Spain. Mitochondrial genome sequencing of tumour tissues from neoplastic animals revealed the coexistence of haplotypes from two different clam species. Phylogenies estimated from mitochondrial and nuclear markers confirmed this leukemia originated in <i>C. gallina </i>(or a closely related taxa) and was later transmitted to <i>V. verrucosa</i>, in which it survived as a contagious cancer. The analysis of mitochondrial and nuclear gene sequences supports all the studied tumours belonging to a single neoplastic <i>C. gallina </i>lineage that spread in the Seas of Southern Europe.</p>
Substitution mutational signatures in whole-genome-sequenced cancers in the UK population, Mutational Signatures Data
<p>This uploads contains the mutational signature data from the article <strong>Substitution mutational signatures in whole-genome-sequenced cancers in the UK population</strong>,<strong> </strong><em>Science</em>, doi:10.1126/science.abl9283, 2022.</p>
Data and Code for "Genomic mechanisms of resistance to tyrosine kinase inhibitors in HER2 amplified breast cancer"; Parsons et al. 2024
<p>Data and code for the manuscript <em>Genomic mechanisms of resistance to tyrosine kinase inhibitors in HER2 amplified breast cancer</em> (Parsons et al. 2024).</p> <p>Data: `parsons_her2_tki_data.tar.gz`</p> <p>Code: `parsons_her2_tki_code.tar.gz`</p> <p>The code may also be obtained from our GitHub repository:<br>https://github.com/getzlab/parsons_her2_tki_manuscript<br><br><br></p>
Breast cancer dataset used in: Biologically informed NeuralODEs for genome-wide regulatory dynamics
<p> The original data set comes from a cross-sectional breast cancer study (GEO accession GSE7390) consisting of microarray expression values for 22000 genes from 198 breast cancer patients, that we sorted along a pseudotime axis. We noted that the same data set was also used in the PROB paper (Sun, X., et al 2021, Inferring latent temporal progression and regulatory networks from cross-sectional transcriptomic data of cancer samples). <br><br>PROB is a GRN inference method that infers a random-walk-based pseudotime to sort cross-sectional samples and reconstruct the GRN. For consistency and convenience in pseudotime inference, we obtained the same version of this data that was already preprocessed and sorted by PROB. This was shared with us by the authors of PROB. We have uploaded the shared files here, as well as the versions obtained after pre-processing to apply PHOENIX. </p>
Data from: Pilot study demonstrating potential association between breast cancer image-based risk phenotypes and genomic biomarkers.
<p>Genotype data from</p> <p>Li H, Giger ML, Sun C, Ponsukcharoen U, Huo D, Lan L, Olopade OI, Jamieson AR, Brown JB, Di Rienzo A. (2014) Pilot study demonstrating potential association between breast cancer image-based risk phenotypes and genomic biomarkers. Med Phys. 41(3)</p>
Transcripts Demonstrating the Application of ChatGPT in the Composition of the Manuscript "Deciphering Cancer Genomes with GenomeSpy: A Grammar-Based Visualization Toolkit" by Lavikka, et al.
Open the record for dataset details and reuse information.
Pan-cancer inference of intra-tumor heterogeneity reveals associations with different forms of genomic instability
<p>"Pan-cancer inference of intra-tumor heterogeneity reveals associations with different forms of genomic instability", F. Raynaud, M. Mina, D. Tavernari and G. Ciriello</p> <p>These files are necessary to generate the supplementary table containing:</p> <p>#Sample_name #Cancer_type #Cancer_subtype #Mean_reads_per_mutations #Number_of_mutations #Number_of_altered_segments #Number_of_clones #TreeScore #Number_of_mutations_first_clone #Number_of_mutations_other_clones</p> <p>REQUIREMENTS</p> <p>Phylogenies generated by PhyloWGS (PhyloWGS: Reconstructing subclonal composition and evolution from whole-genome sequencing of tumors](<a href="http://genomebiology.com/2015/16/1/35">http://genomebiology.com/2015/16/1/35</a>), Deshwar et al.)</p> <p>Output files from PhyloWGS for each sample:</p> <ul> <li> <p>top_k_trees which contains the best phylogenies (50 by default) with the label of each clone, the population frequency of each clone, the number of children of each clone, number of mutations in the clone, the labels of the mutations</p> </li> <li> <p>top_k_trees1, top_k_trees2, ... , top_k_treesN output file for the best k trees (50 by default)</p> </li> </ul> <p>FILES</p> <p>*Molecular data for the tumor types: CESC, UCEC, UVM, THCA, KICH, BRCA, SKCM, ACC, CRC, STAD, BLCA, LUAD, KIRP, PRAD, LIHC; has been collected in July 2015 *Molecular data for the tumor types: SARC, PAAD, MESO, LGG, GBM, DLBC, UCS, THYM, TGCT, PCPG, OV, LUSC, LAML, KIRC, HNSC, ESCA, CHOL; has been collected in 2018</p> <p>from the FireHose (<a href="https://gdac.broadinstitute.org/">https://gdac.broadinstitute.org/</a>) and cBioPortal (Cerami et al., 2012) (<a href="http://www.cbioportal.org/">http://www.cbioportal.org/</a>) data repositories for The Cancer Genome Atlas (TCGA). Only TCGA datasets publicly available at that time were used in our study.</p> <p>-Mutation files (MAF format): combined_2015_2018_MAF.maf.bz2</p> <p>-Copy number segmentation files: combined_seg_2015_2018.seg.bz2</p> <p>-analyze_public.py: Python file to generate the Supplementary Table run: python2.7 analyze_public.py</p> <p>- All input data and results from PhyloWGS: PhyloWGS_input_output.tar.bz2 </p>
Genomic Alterations of the Metabolic Pathways Across 32 Cancer Types and Their Clinical Significance
<p>Supplementary Information for the thesis chapter: Genomic Alterations of the Metabolic Pathways Across 32 Cancer Types and Their Clinical Significance </p>
Association between Galectin-1 gene expression and acute myeloid leukemia patient survival in The Cancer Genome Atlas
Open the record for dataset details and reuse information.
Genome Alignment of Cancer Sequencing Data
<p>Part of the GTN Cancer Analysis learning Pathway based on the Bioinformatics.ca Cancer Workshop</p>
Engagement of American Indians of Southwestern Tribal Nations in Cancer Genome Sequencing
ClinicalTrials.gov study NCT06207864. IPD Sharing: UNDECIDED. Countries: 1. Publications: 9.
OFS in Premenopausal Node+ Breast Cancer With Low Genomic Risk
ClinicalTrials.gov study NCT05333328. IPD Sharing: NO. Countries: 1. Publications: 1.
Genomic and Transcriptomic Predictors of Sequential SG Sensitivity After T-DXd in ER+/HER2-Low Metastatic Breast Cancer
ClinicalTrials.gov study NCT06665178. IPD Sharing: NO. Countries: 1. Publications: 3.
Real-world Clinical Effectiveness of Whole Genome and Transcriptome Analysis to Guide Advanced Cancer Care
ClinicalTrials.gov study NCT04141397. IPD Sharing: NO. Countries: 0. Publications: 1.
An Ancillary Pilot Trial Using Whole Genome Sequencing In Patients With Advance Refractory Cancer
ClinicalTrials.gov study NCT01443390. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Genomic Imprinting Testing for Diagnosis of Bladder Cancer
ClinicalTrials.gov study NCT03563443. IPD Sharing: NO. Countries: 1. Publications: 4.
Achieving Equity in Genomic Testing for Breast Cancer Through Partner-Led Strategies and Policies
ClinicalTrials.gov study NCT05916378. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Evaluating Genomic Testing in Human Cancer & Outcomes of Targeted Therapies
ClinicalTrials.gov study NCT03089554. IPD Sharing: NO. Countries: 1. Publications: 1.
SAFIR02_Breast - Efficacy of Genome Analysis as a Therapeutic Decision Tool for Patients With Metastatic Breast Cancer
ClinicalTrials.gov study NCT02299999. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Proseq Cancer: Genomic Profiling in Patients With Incurable Cancer in Search for Targeted Treatment
ClinicalTrials.gov study NCT05695638. IPD Sharing: NO. Countries: 1. Publications: 2.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.