Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
X
X
poster

Amplicon design algorithm for single cell targeted DNA sequencing using machine learning


Shu Wang
AACR (2020)

High throughput single cell DNA targeted sequencing enables the detection of rare mutations in cells and the identification of subclones defined by co-occurrence of mutations. The big challenge with multiplex sequencing at the single cell level is the non-uniform amplification of targeted regions during PCR. This results in an inadequate coverage of mutations of interest in the panel and hence makes genotyping challenging. To address this challenge, a machine learning engine was developed to optimize amplicon design for uniform amplification by making reliable performance prediction.


VIEW
poster
Improvements in variant calling sensitivity and specificity in single-cell DNA sequencing using deep learning
Manimozhi Manivannan
AACR (2020)
poster
Powerful insights with single-cell multi-omics: Co-detecting both genotype and phenotype from the same cell
James Flynn, PhD
AGBT (2020)
poster
Subclonal identification of driver mutations and copy number variations from single-cell DNA sequencing of tumors
James Flynn, PhD
ABRF (2020)
poster
Single-cell multi-omics for simultaneous detection of SNVs, CNVs, and proteins using the Tapestri Platform
Aik Ooi, PhD
AMP (2019)
REQUEST QUOTE