Yeongjun Jang

This study characterizes somatic mutations in urine-derived iPSCs, showing they reflect age-related genomic changes and can trace developmental lineages non-invasively.

The paper uses single-cell DNA sequencing to analyze somatic mosaicism in postmortem lung and colon tissues, revealing mutation heterogeneity, chromosomal abnormalities, and cellular ancestry.

This study uses single-cell whole genome amplification to link somatic mutations to cell identity and ancestry in a live donor.

The paper traces germline origin in humans using post-zygotic mutations, finding a balanced 50:50 lineage allocation from the first two blastomeres across generations.

The paper shows that clonally selected CRISPR-edited cell lines acquire many culture-specific mutations, making them non-isogenic, and recommends comparing multiple edited and unedited line mixes.

DeepMosaic detects mosaic single nucleotide variants without control samples using deep convolutional neural networks, achieving high accuracy and uncovering many variants missed by existing methods.

All2 filters mosaic mutations from multi-cell comparisons by classifying variants as germline, mosaic, or false positive, improving sensitivity and reducing false positives in whole genome and exome analysis.

The paper evaluates brain somatic mosaicism in the adult human to identify rules governing cellular distribution during embryogenesis.

The paper models ASD in organoids and finds transcriptomic imbalances in excitatory cortical neuron subtypes during early neurogenesis in ASD probands.

This study identifies somatic SNVs in non-cancerous human brain tissues and establishes best practices for detecting low-frequency variants.

The paper tracks cell lineages in humans using post-zygotic mutations and finds lineage imbalance and correlations with developmental axes.