Noise-Tolerant Codebooks for Semi-Quantitative Group Testing: Application to Spatial Genomics
<|reference_start|>Noise-Tolerant Codebooks for Semi-Quantitative Group Testing: Application to Spatial Genomics: Motivated by applications in spatial genomics, we revisit group testing (Dorfman~1943) and propose the class of $\lambda$-{\sf ADD}-codes, studying such codes with certain distance $d$ and codelength $n$. When $d$ is constant, we provide explicit code constructions with rates close to $1/2$. When $d$ is proportional to $n$, we provide a GV-type lower bound whose rates are efficiently computable. Upper bounds for such codes are also studied.<|reference_end|>
@article{chen2024noise-tolerant,
    title={Noise-Tolerant Codebooks for Semi-Quantitative Group Testing:
  Application to Spatial Genomics},
    author={Kok Hao Chen, Duc Tu Dao, Han Mao Kiah, Van Long Phuoc Pham, Eitan
  Yaakobi},
    journal={arXiv preprint arXiv:2405.06870},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.06870},
    primaryClass={cs.IT math.IT}
}