دورية أكاديمية

RNDClone: Tumor subclone reconstruction based on integrating DNA and RNA sequence data

التفاصيل البيبلوغرافية
العنوان: RNDClone: Tumor subclone reconstruction based on integrating DNA and RNA sequence data
المؤلفون: Zhou, Tianjian, Sengupta, Subhajit, Müller, Peter, Ji, Yuan
بيانات النشر: The Institute of Mathematical Statistics
سنة النشر: 2020
المجموعة: Project Euclid (Cornell University Library)
مصطلحات موضوعية: Copy number, gene expression, high-throughput sequencing, intra-tumor heterogeneity, latent factor model, somatic mutation
الوصف: Tumor cell population consists of genetically heterogeneous subpopulations, known as subclones. Bulk sequencing data using high-throughput sequencing technology provide total and variant DNA and RNA read counts for many nucleotide loci as a mixture of signals from different subclones. We present RNDClone as a tool to deconvolute the mixture and reconstruct the subclones with distinct DNA genotypes and RNA expression profiles. In particular, we infer the number and population frequencies of subclones as well as subclonal copy numbers, variant allele numbers and gene expression levels by jointly modeling DNA and RNA read counts from the same tumor samples based on generalized latent factor models. Incorporating data at the RNA level provides new insights into intra-tumor heterogeneity in addition to the existing DNA-based inference. Performance of RNDClone is assessed using simulated and real-world datasets, including an analysis of three samples from a lung cancer patient in The Cancer Genome Atlas (TCGA). A potential fatal subclone is identified from the primary tumor which could explain the rapid prognosis and sudden death of the patient despite a promising diagnosis by conventional standards. The R package $\mathtt{RNDClone}$ is available in the Supplementary Material (Zhou et al. (2020)) and online at https://github.com/tianjianzhou/RNDCloneTest.
نوع الوثيقة: text
وصف الملف: application/pdf
اللغة: English
تدمد: 1932-6157
1941-7330
العلاقة: https://projecteuclid.org/euclid.aoas/1608346902Test; Ann. Appl. Stat. 14, no. 4 (2020), 1856-1877
DOI: 10.1214/20-AOAS1368
الإتاحة: https://doi.org/10.1214/20-AOAS1368Test
https://projecteuclid.org/euclid.aoas/1608346902Test
حقوق: Copyright 2020 Institute of Mathematical Statistics
رقم الانضمام: edsbas.4A45E27
قاعدة البيانات: BASE
الوصف
تدمد:19326157
19417330
DOI:10.1214/20-AOAS1368