Identifying differentially methylated sites in samples with varying tumor purity
Author(s) -
Antti Häkkinen,
Amjad Alkodsi,
Chiara Facciotto,
Kaiyang Zhang,
Katja Kaipio,
Sirpa Leppä,
Olli Carpén,
Seija Grénman,
Johanna Hynninen,
Sakari Hietanen,
Rainer Lehtonen,
Sampsa Hautaniemi
Publication year - 2018
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/bty310
Subject(s) - computer science , software , computational biology , chemistry , chromatography , biology , programming language
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.
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