Gavin Ha edited this page Nov 12, 2017 · 7 revisions

ichorCNA

ichorCNA is a tool for estimating the fraction of tumor in cell-free DNA from ultra-low-pass whole genome sequencing (ULP-WGS, 0.1x coverage).

Description

ichorCNA uses a probabilistic model, implemented as a hidden Markov model (HMM), to simultaneously segment the genome, predict large-scale copy number alterations, and estimate the tumor fraction of a ultra-low-pass whole genome sequencing sample (ULP-WGS). ichorCNA is optimized for low coverage (~0.1x) sequencing of samples and has been benchmarked using patient and healthy donor cfDNA samples.

Uses

ichorCNA can be used to inform the presence or absence of tumor-derived DNA and to guide the decision to perform whole exome or deeper whole genome sequencing. Furthermore, the quantitative estimate of tumor fraction can we used to calibrate the desired depth of sequencing to reach statistical power for identifying mutations in cell-free DNA. Finally, ichorCNA can be use to detect large-scale copy number alterations from large cohorts by taking advantage of the cost-effective approach of ultra-low-pass sequencing.

Publication

The methodology and probabilistic model are described in:
Adalsteinsson, Ha, Freeman, et al. Scalable whole-exome sequencing of cell-free DNA reveals high concordance with metastatic tumors. (2017) Nature Communications Nov 6;8(1):1324. doi: 10.1038/s41467-017-00965-y

You can’t perform that action at this time.
You signed in with another tab or window. Reload to refresh your session. You signed out in another tab or window. Reload to refresh your session.
Press h to open a hovercard with more details.