Metadata record for the manuscript: Panels and models for accurate prediction of tumor mutation burden in tumor samples

<b>Summary</b><br> This metadata record provides details of the data supporting the claims of the related manuscript: “Panels and models for accurate prediction of tumor mutation burden in tumor samples”. The related study presents a bioinformatics-based method to select panels and mathematical models for accurate tumor mutation burden (TMB) prediction and propose cancer-specific panels for 14 malignancies which can offer reliable, clinically relevant estimates of TMBs. Type of data: tumour mutation burden as data for R language (.Rdata) and R script (.R) Subject of data: whole genome (WGS) and whole exon sequencing (WES) datasets of the Cosmic version 84 (Cosmic_v84) for human grch38 assembly Sample size: 24,726 samples of 42 cancer types for the training dataset <b>Data access</b> The datasets and code generated and/or analysed during the current study are available as part of this data record, and also via https://gitlab.com/bioinformatics-fil/predict_tmb. A list of the files underlying the figures, tables and supplementary tables of the related manuscript is available as part of this figshare record in the file ‘Martinez-Perez_et_al_underlying_data_list.xlsx’. For details about the software used, see the supplementary methods of the related publication. <b>Corresponding author(s) for this study</b> Cristina Marino-Buslje. Fundacion Instituto Leloir. Avda. Patricias Argentinas, 435. C1405BWE. Ciudad Autonoma de Buenos Aires, Argentina. E-mail: [e-mail]. Tel: [phone]. Miguel Ángel Molina-Vila, Laboratorio de Oncología/Pangaea Oncology, Hospital Universitario Quirón Dexeus, C. Sabino Arana 5, 08203 Barcelona, Spain. E-mail: [e-mail]; Tel: [phone]. <br> <b>Study approval </b> Not applicable