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- Title
Identifying differentially methylated sites in samples with varying tumor purity.
- Authors
Häkkinen, Antti; Alkodsi, Amjad; Facciotto, Chiara; Zhang, Kaiyang; Kaipio, Katja; Leppä, Sirpa; Carpén, Olli; Grénman, Seija; Hynninen, Johanna; Hietanen, Sakari
- Abstract
Motivation DNA methylation aberrations are common in many cancer types. A major challenge hindering comparison of patient-derived samples is that they comprise of heterogeneous collection of cancer and microenvironment cells. We present a computational method that allows comparing cancer methylomes in two or more heterogeneous tumor samples featuring differing, unknown fraction of cancer cells. The method is unique in that it allows comparison also in the absence of normal cell control samples and without prior tumor purity estimates, as these are often unavailable or unreliable in clinical samples. Results We use simulations and next-generation methylome, RNA and whole-genome sequencing data from two cancer types to demonstrate that the method is accurate and outperforms alternatives. The results show that our method adapts well to various cancer types and to a wide range of tumor content, and works robustly without a control or with controls derived from various sources. Availability and implementation The method is freely available at https://bitbucket.org/anthakki/dmml. Supplementary information Supplementary data are available at Bioinformatics online.
- Subjects
DNA methylation; RNA sequencing; NUCLEOTIDE sequencing; TUMORS; BIOINFORMATICS
- Publication
Bioinformatics, 2018, Vol 34, Issue 18, p3078
- ISSN
1367-4803
- Publication type
Article
- DOI
10.1093/bioinformatics/bty310