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Liu, J.-F.

Publications and source records attributed to Liu, J.-F..

2 recordsLinked to original sources

Efficient Multivariate Analysis Algorithms for Longitudinal Genome-wide Association Studies

MotivationCurrent dynamic phenotyping system introduces time as an extra dimension to genome-wide association studies (GWAS), which helps to explore the mechanism of dynamical genetic control for complex longitudinal traits. However, existing methods for longitudinal GWAS either ignore the covariance among observations of different time points or encounter computational efficiency issues.\n\nResultsWe herein developed efficient genome-wide multivariate association algorithms (GMA) for longitudinal data. In contrast to existing univariate linear mixed model analyses, the proposed new method has improved statistic power for association detection and computational speed. In addition, the new method can analyze unbalanced longitudinal data with thousands of individuals and more than ten thousand records within a few hours. The corresponding time for balanced longitudinal data is just a few minutes.\n\nAvailability and ImplementationWe wrote a software package to implement the efficient algorithm named GMA (https://github.com/chaoning/GMA), which is available freely for interested users in relevant fields.

bioinformatics

Mining unknown porcine protein isoforms by tissue-based map of proteome enhances the pig genome annotation

A lack of the complete pig proteome has left a gap in our knowledge of the pig genome and has restricted the feasibility of using pigs as a biomedical model. We developed the tissue-based proteome maps using 34 major normal pig tissues. A total of 7,319 unknown protein isoforms were identified and systematically characterized, including 3,703 novel protein isoforms, 669 protein isoforms from 460 genes symbolized beginning with LOC, and 2,947 protein isoforms without clear NCBI annotation in current pig reference genome. These newly identified protein isoforms were functionally annotated through profiling the pig transcriptome with high-throughput RNA sequencing (RNA-seq) of the same pig tissues, further improving the genome annotation of corresponding protein coding genes. Combining the well-annotated genes that having parallel expression pattern and subcellular witness, we predicted the tissue related subcellular components and potential function for these unknown proteins. Finally, we mined 3,656 orthologous genes for 49.95% of unknown protein isoforms across multiple species, referring to 65 KEGG pathways and 25 disease signaling pathways. These findings provided valuable insights and a rich resource for enhancing studies of pig genomics and biology as well as biomedical model application to human medicine.

genomics