cancer

Yutong Qiu awarded SCS Cancer Research Fellowship

CPCB Ph.D. student Yutong Qiu has been awarded an SCS Cancer Research Fellowship. Yutong works on computational methods for understanding the human genome, including methods to identify variants within single genomes and populations of genomes. Her recent work is focused on construction and use of genome graphs for applications in cancer, especially more accurate subtyping of cancers from genomic features. Congratulations! More details here

VariantStore: A Large-Scale Genomic Variant Search Index

The ability to efficiently query genomic variation data from thousands of samples is critical to achieve the full potential of many medical and scientific applications such as personalized medicine. We present VariantStore, a system for efficiently …

Estimating mutual information under measurement error

Mutual information is widely used to characterize dependence between biological signals, such as co-expression between genes or co-evolution between amino acids. However, measurement error of the biological signals is rarely considered in estimating …

Detecting, categorizing, and correcting coverage anomalies of RNA-seq quantification

Due to incomplete reference transcriptomes, incomplete sequencing bias models, or other modeling defects, algorithms to infer isoform expression from RNA-seq sometimes do not accurately model expression. We present a computational method to detect …

Detecting Transcriptomic Structural Variants in Heterogeneous Contexts via the Multiple Compatible Arrangements Problem

Transcriptomic structural variants (TSVs) --- structural variants that affect expressed regions --- are common, especially in cancer. Detecting TSVs is a challenging computational problem. Sample heterogeneity (including differences between alleles …

Analysis of the structural variability of topologically associated domains as revealed by Hi-C

Three-dimensional chromosome structure plays an integral role in gene expression and regulation, replication timing, and other cellular processes. Topologically associated domains (TADs), building blocks of chromosome structure, are genomic regions …

Topological data analysis reveals principles of chromosome structure throughout cellular differentiation

Topological data analysis (TDA) is a mathematically well-founded set of methods to derive robust information about the structure and topology of data. It has been applied successfully in several biological contexts. Derived primarily from algebraic …

Kourami: graph-guided assembly for novel human leukocyte antigen allele discovery

Quantifying the similarity of topological domains across normal and cancer human cell types

Selected as one of the “(https://www.iscb.org/recomb-regsysgen2019-submissions/recomb-regsysgen2019-reading)[Top 10 Reading Papers]” at RECOMB/ISCB Regulatory & Systems Genomics 2019.

SQUID: transcriptomic structural variation detection from RNA-seq