MOTIVATION: Cell-to-cell variation has uncovered associations between cellular phenotypes. However, it remains challenging to address the cellular diversity of such associations. RESULTS: Here, we do not rely on the conventional assumption that the same association holds throughout the entire cell population. Instead, we assume that associations may exist in a certain subset of the cells. We developed CEllular Niche Association (CENA) to reliably predict pairwise associations together with the cell subsets in which the associations are detected. CENA does not rely on predefined subsets but only requires that the cells of each predicted subset would share a certain characteristic state. CENA may therefore reveal dynamic modulation of dependencies along cellular trajectories of temporally evolving states. Using simulated data, we show the advantage of CENA over existing methods and its scalability to a large number of cells. Application of CENA to real biological data demonstrates dynamic changes in associations that would be otherwise masked. AVAILABILITY AND IMPLEMENTATION: CENA is available as an R package at Github: https://github.com/mayalevy/CENA and is accompanied by a complete set of documentations and instructions. CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Mutually uncorrelated (MU) codes are a class of codes in which no proper prefix of one codeword is a suffix of another codeword. These codes were originally studied for synchronization purposes and recently, Yazdi et al. showed their applicability to enable random access in DNA storage. In this paper,we follow the research of Yazdi et al. and study MU codes along with their extensions to correct errors and balanced codes. We first review a well-known construction of MU codes and study the asymptotic behavior of its cardinality. This task is accomplished by studying a special class of run-length limited codes that impose the longest run of zeros to be at most some function of the codewords length. We also present an efficient algorithm for this class of constrained codes and show how to use this analysis for MU codes. Next, we extend the results on the run-length limited codes in order to study (dh, dm)-MU codes that impose a minimum Hamming distance of dh between different codewords and dmbetween prefixes and suffixes. In particular, we show an efficient construction of these codes with nearly optimal redundancy. We also provide similar results for the edit distance and balanced MU codes. Last, we draw connections to the problems of comma-free and prefix synchronized codes.

Mutually Uncorrelated (MU) codes are a class of codes in which no proper prefix of one codeword is a suffix of another codeword. These codes were originally studied for synchronization purposes and recently, Yazdi et al. showed their applicability to enable random access in DNA storage. In this work we follow the research of Yazdi et al. and study MU codes along with their extensions to correct errors and balanced codes. We first review a well known construction of MU codes and study the asymptotic behavior of its cardinality. Then, we present an efficient algorithm for MU codes with linear encoding and decoding complexity. Next, we extend these results for (dh, dm)-MU codes that impose a minimum Hamming distance of dh between different codewords and dmbetween prefixes and suffixes. Particularly we show an efficient construction of these codes with nearly optimal redundancy and draw connections to the problem of comma-free and prefix synchronized codes. Lastly, we provide similar results for the edit distance and balanced MU codes.