Other skills

PowerX CRUD DTO 规则（输入输出分离、分页、校验）。

The English summary is being prepared. Showing the original description.

PowerX Nuxt i18n 词条与目录规范。

The English summary is being prepared. Showing the original description.

PowerX CRUD gRPC 开发规范（proto、server、拦截器、错误映射）。

The English summary is being prepared. Showing the original description.

PowerX STS ruleset（当前源可为空，保留占位）。

The English summary is being prepared. Showing the original description.

网感口播精剪（v3.4）：口播视频加动效，自动剪成"网感口播精剪风格"竖版/横版样片，交付渲染成片+分层工程包（装了剪映引擎则再出剪映分层草稿，音效放草稿；没装则音效混进成片）。当用户给了口播粗剪(+B-roll/截图/录屏)并想要"口播动效/加卡片弹字/剪成短视频/做动效样片/网感口播精剪"时用。自循环:预检→素材理解→找真证据→编排→HyperFrames构建→硬门+两两对比自迭代(≤3版)→配音效→交付→用户终审。不做:纯字幕/纯配音/纯生图/BGM。

The English summary is being prepared. Showing the original description.

Best practices for single-cell RNA-seq cell type annotation including marker-based, reference-based, and automated classification approaches.

The English summary is being prepared. Showing the original description.

GWAS and population genetics tool. Processes PLINK (.bed/.bim/.fam), VCF, and BGEN; runs QC (MAF, HWE, missingness), IBD estimation, PCA, and linear/logistic regression GWAS. Outputs Manhattan-ready summary stats. Use regenie or SAIGE for biobanks (>100k samples) needing mixed models.

The English summary is being prepared. Showing the original description.

Ultra-fast RNA-seq transcript/gene quantification via quasi-mapping (no BAM). Builds a k-mer index from transcriptome FASTA, quantifies in minutes. Outputs TPM/count tables (quant.sf) with optional GC- and sequence-bias correction. Integrates with tximeta/tximport for DESeq2/edgeR. Use STAR when a genome-aligned BAM is needed.

The English summary is being prepared. Showing the original description.

Aggregates QC from 150+ bioinformatics tools into one interactive HTML report. Scans FastQC, samtools, STAR, HISAT2, Trim Galore, featureCounts, Kallisto, Salmon, Picard, GATK logs; merges per-sample stats with plots. For NGS pipeline-wide QC. Use FastQC directly for single-sample; MultiQC for multi-sample reporting.

The English summary is being prepared. Showing the original description.

Genomic interval ops on BED/BAM/GFF/VCF. Find overlaps, merge intervals, compute coverage, extract FASTA, find nearest features. Core for ChIP-seq peak annotation, region filtering, genome arithmetic. Use tabix for indexed single-region queries; use deeptools for normalized bigWig coverage.

The English summary is being prepared. Showing the original description.

scRNA-seq with Scanpy: QC, normalization, HVG selection, PCA, neighborhood graph, UMAP/t-SNE, Leiden clustering, markers, cell annotation, trajectory inference. Standard scRNA-seq exploration.

The English summary is being prepared. Showing the original description.

Annotate prokaryotic genomes (bacteria, archaea, viruses) via Prokka's BLAST/HMM pipeline. Identifies CDS, rRNA, tRNA, tmRNA, signal peptides against Pfam, TIGRFAMs, RefSeq. Outputs GFF3, GenBank, FASTA, TSV. Use PGAP for NCBI GenBank submission; Bakta for faster NCBI-compatible annotation.

The English summary is being prepared. Showing the original description.

All-in-one FASTQ QC and adapter trimming. Auto-detects Illumina adapters, filters low-quality reads, corrects paired-end overlaps, emits HTML+JSON QC in one pass. 3-10x faster than Trim Galore/Trimmomatic. First step before STAR, BWA-MEM2, or Salmon.

The English summary is being prepared. Showing the original description.

Automated scRNA-seq cell type annotation via pre-trained logistic regression. 45+ models: immune, gut, lung, brain, fetal, cancer microenvironments. Input normalized AnnData; outputs per-cell labels, majority-vote cluster labels, confidence scores. Use for fast, reference-backed annotation without manual marker inspection; read cell-type-annotation first.

The English summary is being prepared. Showing the original description.

Structure-activity relationship (SAR) analysis guide for drug discovery including molecular descriptor analysis, scaffold analysis, and activity cliff detection.

The English summary is being prepared. Showing the original description.

Fast short-read DNA aligner for WGS/WES/ChIP-seq. 2× faster BWA-MEM successor; outputs SAM/BAM with read group headers for GATK. Primary plus supplementary records for chimeric reads. Use STAR for RNA-seq splice-aware alignment; Bowtie2 is a comparable alternative.

The English summary is being prepared. Showing the original description.

Diffusion-based docking that predicts protein-ligand poses without a predefined site. Use for blind docking, when traditional docking fails, or exploring multiple binding modes. Pipeline: prep protein (PDB) and ligand (SMILES/SDF), run inference, analyze confidence-ranked poses.

The English summary is being prepared. Showing the original description.

Analyze MD trajectories from GROMACS, AMBER, NAMD, CHARMM, LAMMPS. Reads topology/trajectory into Universe objects; supports RMSD, RMSF, radius of gyration, contact maps, H-bonds, PCA, and custom distance/angle calculations. Use for post-simulation structural analysis; use OpenMM/GROMACS for running simulations.

The English summary is being prepared. Showing the original description.

Graph and network analysis toolkit. Four graph types (directed, undirected, multi-edge), centrality, shortest paths, community detection, generators, I/O (GraphML, GML, edge list), matplotlib viz. For large graphs (100K+ nodes) use igraph or graph-tool; for GNNs use PyG.

The English summary is being prepared. Showing the original description.

Auto-annotate plasmids with features (promoters, terminators, resistance, origins, tags, fluorescent proteins) via BLAST against curated DBs (Addgene, fpbase, SnapGene). FASTA or raw sequence in; annotated GenBank, interactive HTML maps, CSV tables out. Handles circular topology. Use to verify synthetic constructs, prep Addgene submissions, share maps, or batch-annotate cloning libraries.

The English summary is being prepared. Showing the original description.

Poisson-model peak caller for ChIP-seq/ATAC-seq BAMs. MACS3 callpeak finds enriched regions (TF sites or histone marks) vs input/IgG; outputs BED narrowPeak/broadPeak for motif analysis, annotation, and differential binding. Use narrow peaks for TF ChIP-seq and ATAC-seq; broad for H3K27me3, H3K9me3, and other broad marks.

The English summary is being prepared. Showing the original description.

De novo and known TF motif enrichment in ChIP-seq/ATAC-seq peaks via HOMER. findMotifsGenome.pl finds over-represented patterns vs background; annotatePeaks.pl assigns context (TSS distance, gene, repeat). Use after MACS3 to identify enriched TFs, annotate peaks with nearest genes, and validate ChIP-seq via the target motif.

The English summary is being prepared. Showing the original description.

GRN inference from expression via GRNBoost2 (gradient boosting) or GENIE3 (Random Forest). Load matrix, filter by TFs, infer TF-target-importance links, save network. Dask-parallelized to single-cell scale. Core SCENIC component.

The English summary is being prepared. Showing the original description.

MS spectral matching and metabolite ID with matchms. Import spectra (mzML, MGF, MSP, JSON), filter/normalize peaks, score similarity (cosine, modified cosine, fingerprint), build reproducible pipelines, identify unknowns vs spectral libraries. Use pyopenms for full LC-MS/MS proteomics.

The English summary is being prepared. Showing the original description.