Jianye Ge, Ph.D.
Permanent URI for this communityhttps://hdl.handle.net/20.500.12503/31748
Associate Professor, Microbiology, Immunology & Genetics
Email: Jianye.Ge@unthsc.edu
Browse
Browsing Jianye Ge, Ph.D. by Subject "Computational Biology"
Now showing 1 - 2 of 2
- Results Per Page
- Sort Options
Item skater: an R package for SNP-based kinship analysis, testing, and evaluation(F1000 Research Ltd., 2022-01-07) Turner, Stephen D.; Nagraj, V. P.; Scholz, Matthew; Jessa, Shakeel; Acevedo, Carlos; Ge, Jianye; Woerner, August E.; Budowle, BruceMotivation: SNP-based kinship analysis with genome-wide relationship estimation and IBD segment analysis methods produces results that often require further downstream process- ing and manipulation. A dedicated software package that consistently and intuitively imple- ments this analysis functionality is needed. Results: Here we present the skater R package for SNP-based kinship analysis, testing, and evaluation with R. The skater package contains a suite of well-documented tools for importing, parsing, and analyzing pedigree data, performing relationship degree inference, benchmarking relationship degree classification, and summarizing IBD segment data. Availability: The skater package is implemented as an R package and is released under the MIT license at https://github.com/signaturescience/skater. Documentation is available at https://signaturescience.github.io/skater.Item USAT: a bioinformatic toolkit to facilitate interpretation and comparative visualization of tandem repeat sequences(BioMed Central Ltd., 2022-11-20) Wang, Xuewen; Budowle, Bruce; Ge, JianyeBACKGROUND: Tandem repeats (TR), highly variable genomic variants, are widely used in individual identification, disease diagnostics, and evolutionary studies. The recent advances in sequencing technologies and bioinformatic tools facilitate calling TR haplotypes genome widely. Both length-based and sequence-based TR alleles are used in different applications. However, sequence-based TR alleles could provide the highest precision in characterizing TR haplotypes. The need to identify the differences at the single nucleotide level between or among TR haplotypes with an easy-use bioinformatic tool is essential. RESULTS: In this study, we developed a Universal STR Allele Toolkit (USAT) for TR haplotype analysis, which takes TR haplotype output from existing tools to perform allele size conversion, sequence comparison of haplotypes, figure plotting, comparison for allele distribution, and interactive visualization. An exemplary application of USAT for analysis of the CODIS core STR loci for DNA forensics with benchmarking human individuals demonstrated the capabilities of USAT. USAT has user-friendly graphic interfaces and runs fast in major computing operating systems with parallel computing enabled. CONCLUSION: USAT is a user-friendly bioinformatics software for interpretation, visualization, and comparisons of TRs.