Article

Optimized data representation and convolutional neural network model for predicting tumor purity

2019-10-17

Abstract excerpt

Here we present a machine learning model, Deep Purity (DePuty) that leverages convolutional neural networks to accurately predict tumor purity from next-generation sequencing data from clinical samples without matched normals. As input, our model utilizes SNP-based copy number and minor allele frequency data formulated as a scatterplot image. With a representation matching that used by expert human annotators, we...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 240303b7-5281-564a-b899-9056c6e4cac6
DOI: 10.1101/805135

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Optimized data representation and convolutional neural network model for predicting tumor purityDOI 10.1101/805135Read

PurityEst: estimating purity of human tumor samples using next-generation sequencing data.Semantic proximity Read

Weakly-Supervised Tumor Purity Prediction From Frozen H&E Stained SlidesSemantic proximity Read

PUREE: accurate pan-cancer tumor purity estimation from gene expression dataSemantic proximity Read

Deriving tumor purity from cancer next generation sequencing data: applications for quantitative ERBB2 (HER2) copy number analysis and germline inference of BRCA1 and BRCA2 mutations.Semantic proximity Read

Accurity: accurate tumor purity and ploidy inference from tumor-normal WGS data by jointly modelling somatic copy number alterations and heterozygous germline single-nucleotide-variantsSemantic proximity Read

GBMPurity: A machine learning tool for estimating glioblastoma tumor purity from bulk RNA-sequencing dataSemantic proximity Read

All-FIT: Allele-Frequency-based Imputation of Tumor Purity from High-Depth Sequencing DataSemantic proximity Read

All-FIT: allele-frequency-based imputation of tumor purity from high-depth sequencing data.Semantic proximity Read

STIC: Predicting Single Nucleotide Variants and Tumor Purity in Cancer Genome.Semantic proximity Read

TPES: tumor purity estimation from SNVsSemantic proximity Read

Tumour purity assessment with deep learning in colorectal cancer and impact on molecular analysisSemantic proximity Read

CANCAN: high-resolution copy number and mutation heterogeneity analysis of DNA sequence data for clinical applicationsSemantic proximity Read