[PMID:27088313] [Nature Methods]

Monovar: single-nucleotide variant detection in single cells

“Monovar, a statistical method for detecting and genotyping single-nucleotide variants in single-cell data.” “These variant callers, designed for bulk tissue samples, make many assumptions regarding the underlying properties of the data. This is problematic for SCS data, which, on account of extensive whole-genome amplification (WGA), have unique properties and error profiles, including nonuniform coverage depth, allelic dropout (ADO) events, false-positive (FP) errors and false-negative (FN) errors, making it difficult to call SNVs accurately. Consequently, these studies have been challenged by a large number of FP and FN variant calls, and they require extensive orthogonal validation.’


Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out /  Change )

Google+ photo

You are commenting using your Google+ account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )


Connecting to %s