Browsing by Author "Pinto, José P."
Now showing 1 - 2 of 2
Results Per Page
Sort Options
- Parallel clustering of single cell transcriptomic data with split-merge sampling on Dirichlet process mixturesPublication . Duan, Tiehang; Pinto, José P.; Xie, XiaohuiMotivation: With the development of droplet based systems, massive single cell transcriptome data has become available, which enables analysis of cellular and molecular processes at single cell resolution and is instrumental to understanding many biological processes. While state-of-the-art clustering methods have been applied to the data, they face challenges in the following aspects: (1) the clustering quality still needs to be improved; (2) most models need prior knowledge on number of clusters, which is not always available; (3) there is a demand for faster computational speed. Results: We propose to tackle these challenges with Parallel Split Merge Sampling on Dirichlet Process Mixture Model (the Para-DPMM model). Unlike classic DPMM methods that perform sampling on each single data point, the split merge mechanism samples on the cluster level, which significantly improves convergence and optimality of the result. The model is highly parallelized and can utilize the computing power of high performance computing (HPC) clusters, enabling massive clustering on huge datasets. Experiment results show the model outperforms current widely used models in both clustering quality and computational speed. Availability: Source code is publicly available on https://github.com/tiehangd/Para_DPMM/tree/master/Para_DPMM_package
- Parallel Genome-wide Profiling of Coding and Non-coding RNAs to Identify Novel Regulatory Elements in Embryonic and Maturated HeartPublication . Sabour, Davood; Machado, Rui; Pinto, José P.; Rohani, Susan; Sahito, Raja G. A.; Hescheler, Jurgen; Futschik, Matthias; Sachinidis, AgapiosHeart development is a complex process, tightly regulated by numerous molecular mechanisms. Key components of the regulatory network underlying heart development are transcription factors (TFs) and microRNAs (miRNAs), yet limited investigation of the role of miRNAs in heart development has taken place. Here, we report the first parallel genome-wide profiling of polyadenylated RNAs and miRNAs in a developing murine heart. These data enable us to identify dynamic activation or repression of numerous biological processes and signaling pathways. More than 200 miRNAs and 25 long non-coding RNAs were differentially expressed during embryonic heart development compared to the mature heart; most of these had not been previously associated with cardiogenesis. Integrative analysis of expression data and potential regulatory interactions suggested 28 miRNAs as novel regulators of embryonic heart development, representing a considerable expansion of the current repertoire of known cardiac miRNAs. To facilitate follow-up investigations, we constructed HeartMiR (http://heartmir.sysbiolab.eu), an open access database and interactive visualization tool for the study of gene regulation by miRNAs during heart development.