RT Journal Article
SR Electronic
T1 Identifying differentially methylated sites in samples with varying tumor purity
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 248781
DO 10.1101/248781
A1 Antti Häkkinen
A1 Amjad Alkodsi
A1 Chiara Facciotto
A1 Kaiyang Zhang
A1 Katja Kaipio
A1 Sirpa Leppä
A1 Olli Carpén
A1 Seija Grénman
A1 Johanna Hynninen
A1 Sakari Hietanen
A1 Rainer Lehtonen
A1 Sampsa Hautaniemi
YR 2018
UL http://biorxiv.org/content/early/2018/01/16/248781.abstract
AB 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. 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. The method is freely available at https://bitbucket.org/anthakki/dmml.