This website outlines the key tools and software packages developed from my research:

• FASTQ+: This format enhances the standard FASTQ file by integrating barcode information directly into the read name. This modification facilitates the harmonization of single-cell sequencing data across various platforms. FASTQ+ can be generated with PISA.
• PISA: A suite of programs specifically designed for preprocessing data from single-cell sequencing and spatial transcriptomics. It efficiently processes FASTQ+, BAM, and BED files, and generates various feature counts and annotations.
• Yano: An R package that employs the spatial dissimilarity test method as its core algorithm. Yano is tailored for exploring various biological events in single-cell and spatial transcriptomics data, including alternative splicing, allele-specific gene expression, somatic variants and more, providing comprehensive insights into cellular dynamics.

Workflows and Short Cases for scRNA-seq and Spatial Transcriptome

• From raw reads to gene counts (PISA)
• Annotate various features for alignment (PISA)
• Alternative splicing analysis for scRNA-seq (Yano)
• Allele-specific gene expression analysis for scRNA-seq (Yano)
• Annotating and prioritizing genetic variants for scRNA-seq (Yano)
• Perform alternative splicing analysis for multiple Visium samples (Yano)
• Select cells from reduction maps and spatial locations (Yano)
• Perform alternative splicing analysis for cell trajectory and user-defined embeddings (Yano)