I develop and maintain freely-available, open-source software packages in R/Bioconductor/CRAN/GitHub to analyze high-throughput genomics data. They are available through R cran, Bioconductor or GitHub.

• DSS Usage Stats
  (Dispersion Shrinakge for Sequencing): differential analysis for count-based sequencing data. It detectes differentially expressed genes (DEGs) from RNA-seq, and differentially methylated regions (DMRs) from bisulfite sequencing (BS-seq) data. Available on Bioconductor.

• NeuCA Usage Stats
  (Neural-network based Cell type Annotation): R/Bioconductor package for single-cell RNA-seq data cell type annotation, using neural-network approaches. NeuCA is flexible and adjust the classification method it will adopt, depending on cell types’ correlation level. Currently available on Bioconductor.

• ISLET Usage Stats
  ISLET (Individual-Specific ceLl typE referencing Tool) can deconvolute mixture samples and obtain the individual-specific and cell-type-specific reference panels, for repeatedly measured subjects’ bulk data. Available on Bioconductor.

• magpie Usage Stats
  magpie (m6A genome-wide power inference) can perform statistical power analysis for the RNA methylation (m6A MeRIP-seq) study. It evaluates FDR, FDC, power, and precision under various study design parameters, including sample size, sequencing depth, and testing method. It can also produce power evaluation results into .xlsx files and generate power figures. Available on Bioconductor.

• InfiniumPurify
  R CRAN package for the estimation and adjustment for tumor purity in cancer methylation data analysis, available on R CRAN.

• cfDNAmethy
  Reference-free and reference-based models for disease prediction by cell-free DNA methylation, available on GitHub.