zongtingwei
Community@zongtingwei · Shenzhen
Studying Agent and AIVC.
Agent Skills by zongtingwei
Showing 66 vetted skills indexed across 1 GitHub repositories.
ehr-analysis
Automate end-to-end EHR predictive modeling workflows with PyHealth.
long-read-genomics
Process nanopore or PacBio long-read data into alignments, polished consensus, and variant summaries.
copy-number
Automate copy-number estimation, segmentation, annotation, and visualization from coverage data.
genome-assembly
Generate de novo genome assemblies from short and long reads with QC and contamination assessment.
variant-calling
Identify germline, somatic, and structural variants from BAM/CRAM sequencing data.
comparative-genomics
Generates orthologs, synteny blocks, and evolutionary summaries from genome assemblies and annotations.
phasing-imputation
Generates phased and imputed genotypes from VCF data using reference panels and Python tools.
systems-biology
Automate flux balance analysis and metabolic modeling with cobrapy for Python-based workflows.
multi-omics-integration
Integrate matched omics layers into shared latent factors for cross-modal analysis.
machine-learning-for-omics
Train supervised models on omics feature matrices and output metrics and explanations.
causal-genomics
Integrate GWAS and QTL summary statistics to identify shared causal signals.
pathway-analysis
Automate pathway enrichment and interpretation across multi-omics gene lists.
cell-communication
Infer ligand-receptor signaling from scRNA-seq or spatial data using pandas.
spatial-transcriptomics
Preprocess spatial transcriptomics data to identify domains and deconvolute cell types.
scrna-preprocessing-clustering
Preprocess single-cell RNA-seq data into analysis-ready AnnData objects.
cell-annotation
Annotate single-cell RNA-seq data with cell-type labels using marker review and reference transfer.
trajectory-lineage
Infer pseudotime, lineage branches, and state transitions from single-cell data using Scanpy.
multiome-scatac
Integrate single-cell RNA and ATAC data into unified multimodal embeddings.
alternative-splicing
Identify and quantify splice events and isoform usage from RNA-seq data.
rna-quantification
Quantify gene and transcript abundances from RNA-seq reads using salmon, kallisto, or featureCounts.
differential-expression
Perform count-based differential expression analysis on bulk RNA-seq data with PyDESeq2.
bulk-rna-expression
Normalize and quality-check bulk RNA-seq count matrices with Python.
ribo-seq
Automate ribosome profiling analysis from raw reads to translation efficiency insights.
small-rna-seq
Process small RNA FASTQ files into counts, differential results, and target summaries.