Robust estimation of cancer and immune cell-type proportions from bulk tumor ATAC-Seq data
bioRxiv (Cold Spring Harbor Laboratory)(2024)
摘要
Assay for Transposase-Accessible Chromatin sequencing (ATAC-Seq) is a widely used technique to explore gene regulatory mechanisms. For most ATAC-Seq data from healthy and diseased tissues such as tumors, chromatin accessibility measurement represents a mixed signal from multiple cell types. In this work, we derive reliable chromatin accessibility marker peaks and reference profiles for all major cancer-relevant cell types. We then capitalize on the EPIC deconvolution framework (Racle et al. 2017) previously shown to accurately predict cell-type composition in tumor bulk RNA-Seq data and integrate our markers and reference profiles to EPIC to quantify cell-type heterogeneity in bulk ATAC-Seq data. Our EPIC-ATAC tool accurately predicts non-malignant and malignant cell fractions in tumor samples. When applied to a breast cancer cohort, EPIC-ATAC accurately infers the immune contexture of the main breast cancer subtypes.
### Competing Interest Statement
The authors have declared no competing interest.
* ATAC
: Assay for Transposase-Accessible chromatin
CBP(s)
: chromatin binding protein(s)
ChIP-seq
: chromatin immunoprecipitation followed by sequencing
DC
: dendritic cells
NK
: natural killer cells
PCA
: principal component analysis
RMSE
: root mean squared error
TCGA
: The Cancer Genome Atlas
TF(s)
: transcription factor(s)
TSS
: transcription start site
UMAP
: Uniform Manifold Approximation
更多查看译文
关键词
robust estimation,cancer,cell-type,atac-seq
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要