Description

With the advances of high-throughput DNA and RNA sequencing platforms, sequencing data opens an unprecedented opportunity for genomic variant analysis at genome-wide scale or in single-cell resolution. To date, many algorithms have been designed to detect different types of variants such as single nucleotide polymorphisms (SNPs), small insertions and deletions (indels), and large structural variants (SVs). Wide adoption of these algorithms and tools is expected to facilitate discovery and explicate the genetic causes of complex conditions and cancers.

We invite investigators to contribute Original Research on computational methods of genome reconstruction, detecting and phasing variants. Potential topics include but are not limited to the following:

Computational mathematical or machine learning models for genomic variants detection from short-read, linked-read and long-read sequencing data.
Novel methods for variant quality recalibration for downstream analysis.
Novel methods for refinement of variants from up-stream variant callers
Algorithms for variant phasing in different types of sequencing data
Genome assembly on human genome and metagenome
New algorithms or tools to analyze copy number variations (CNVs) on single-cell RNA-seq data, single-cell DNA-seq data, spatial transcriptomics data, or other types of single cell data
Computational tools for integration of different types of sequencing data for characterizing variants
Algorithms to integrate variants (e.g., CNVs) from single-cell or bulk sequencing data to assist down-stream analysis in cancer studies Applications of advanced algorithms and sequencing technologies across a wide array of diseases

Important Dates (Tentative)

~~Oct. 10~~ Oct. 30, 2022: Due date for full workshop paper submission
~~Nov. 5~~ Nov. 15, 2022: Notification of paper acceptance to authors
~~Nov. 21~~ Nov. 22, 2022: Camera-ready of accepted papers
Dec. 6-7, 2022: Workshops

Program Chairs

Xin Maizie Zhou, Department of Biomedical Engineering and Computer Science, Vanderbilt University
Eric Lu Zhang, Department of Computer Science, Hong Kong Baptist University
Ryan Matthew Layer, Department of Computer Science, University of Colorado Boulder
Zechen Chong, Department of Genetics, University of Alabama at Birmingham
Xian Fan Mallory, Department of Computer Science, Florida State University

Program Committee Members

Yan Li, BGI Research
Zhengmiao Zhang, Hong Kong Baptist University
Yong Fei Wang, The University of Hong Kong
Wenjun Shen, Shantou University
Zheng Hu, University of Chinese Academy of Sciences
Huaming Chen, University of Sydney

Workshop Submission Requirement

Please submit a full-length paper (up to 8 page IEEE 2-column format ) through the online submission system (you can download the format instruction here. Electronic submissions (in PDF or Postscript format) are required. Selected participants will be asked to submit their revised papers in a format to be specified at the time of acceptance.

Workshop Online Submission:

Submit a paper Click here

Registration

At least one author of an accepted paper needs to register as one full registration in order to have the paper published in the conference proceedings.

Workshop schedule

The workshop will be held on Tuesday, December 7, 2022 (based on USA PST Time), Caesars Palace(Room: Pisa), Las Vegas, USA

time	title	Presenter/Author
2:00pm-2:20pm	High-resolution sample size enrichment of single-cell multi-modal low-throughput Patch-seq datasets	Lorenzo Martini, Roberta Bardini, Alessandro Savino, and Stefano Di Carlo
2:20pm-2:40pm	Haplotype-phasing of long-read HiFi data to enhance structural variant detection through a Skip-Gram model	Can Luo, Parth Datar, Yichen Henry Liu, and Xin Zhou
2:40pm-3:00pm	Reliable tumor evolution estimates using bulk sequencing data	Jared Huzar, Madelyn Shenoy, Maxwell Sanderford, Sudhir Kumar, and Sayaka Miura
3:00pm-3:20pm	Targeted Next generation Sequencing Reveals the Genetic Mechanism of Chinese Marfan syndrome Cohort with Ocular Manifestation	Dongming Han, Wei Li, Ziwei Wang, Sicheng Guo, Jiayu Gao, and Jiankang Li