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Claude Skills by David-Li0406
github.com/David-Li04065,064 skills17 installs250 views
- Bio Proteomics Peptide IdentificationPeptide-spectrum matching and protein identification from MS/MS data. Use when identifying peptides from tandem mass spectra. Covers database searching, spectral library matching, and FDR estimation using target-decoy approaches.Votes: 0GitHub stars: 2
- Bio Proteomics Protein InferenceProtein grouping and inference from peptide identifications. Use when resolving protein ambiguity from shared peptides. Handles protein groups and protein-level FDR control using parsimony and probabilistic approaches.Votes: 0GitHub stars: 2
- Bio Proteomics Proteomics QcQuality control and assessment for proteomics data. Use when evaluating proteomics data quality before downstream analysis. Covers sample metrics, missing value patterns, replicate correlation, batch effects, and intensity distributions.Votes: 0GitHub stars: 2
- Bio Proteomics Ptm AnalysisPost-translational modification analysis including phosphorylation, acetylation, and ubiquitination. Covers site localization, motif analysis, and quantitative PTM analysis. Use when analyzing phosphoproteomic data or other modification-enriched samples.Votes: 0GitHub stars: 2
- Bio Proteomics QuantificationProtein quantification from mass spectrometry data including label-free (LFQ, intensity-based), isobaric labeling (TMT, iTRAQ), and metabolic labeling (SILAC) approaches. Use when extracting protein abundances from MS data for differential analysis.Votes: 0GitHub stars: 2
- Bio Proteomics Spectral LibrariesBuild, manage, and search spectral libraries for proteomics. Use when creating or working with spectral libraries for DIA analysis. Covers DDA-based library generation, predicted libraries (Prosit, DeepLC), and library formats.Votes: 0GitHub stars: 2
- Bio Read Qc Quality ReportsGenerate and interpret quality reports from FASTQ files using FastQC and MultiQC. Assess per-base quality, adapter content, GC bias, duplication levels, and overrepresented sequences. Use when performing initial QC on raw sequencing data or validating preprocessing results.Votes: 0GitHub stars: 2
- Bio Read Qc Umi ProcessingExtract, process, and deduplicate reads using Unique Molecular Identifiers (UMIs) with umi_tools. Use when library prep includes UMIs and accurate molecule counting is needed, such as in single-cell RNA-seq, low-input RNA-seq, or targeted sequencing to distinguish PCR from biological duplicates.Votes: 0GitHub stars: 2
- Bio Read SequencesRead biological sequence files (FASTA, FASTQ, GenBank, EMBL, ABI, SFF) using Biopython Bio.SeqIO. Use when parsing sequence files, iterating multi-sequence files, random access to large files, or high-performance parsing.Votes: 0GitHub stars: 2
- Bio Reference OperationsGenerate consensus sequences and manage reference files using samtools. Use when creating consensus from alignments, indexing references, or creating sequence dictionaries.Votes: 0GitHub stars: 2
- Bio Reverse ComplementGenerate reverse complements and complements of DNA/RNA sequences using Biopython. Use when working with opposite strands, primer design, or converting between template and coding strands.Votes: 0GitHub stars: 2
- Bio Ribo Seq Orf DetectionDetect and quantify translated ORFs from Ribo-seq data including uORFs and novel ORFs using RiboCode and ORFquant. Use when identifying translated regions beyond annotated coding sequences or quantifying ORF-level translation.Votes: 0GitHub stars: 2
- Bio Ribo Seq Riboseq PreprocessingPreprocess ribosome profiling data including adapter trimming, size selection, rRNA removal, and alignment. Use when preparing Ribo-seq reads for downstream analysis of translation.Votes: 0GitHub stars: 2
- Bio Ribo Seq Ribosome PeriodicityValidate Ribo-seq data quality by checking 3-nucleotide periodicity and calculating P-site offsets. Use when assessing library quality or determining read offsets for downstream analysis.Votes: 0GitHub stars: 2
- Bio Ribo Seq Ribosome StallingDetect ribosome pausing and stalling sites from Ribo-seq data at codon resolution. Use when studying translational regulation, identifying pause sites, or analyzing codon-specific translation dynamics.Votes: 0GitHub stars: 2
- Bio Ribo Seq Translation EfficiencyCalculate translation efficiency (TE) as the ratio of ribosome occupancy to mRNA abundance. Use when comparing translational regulation between conditions or identifying genes with altered translation independent of transcription.Votes: 0GitHub stars: 2
- Bio Rnaseq QcRNA-seq specific quality control including rRNA contamination detection, strandedness verification, gene body coverage, and transcript integrity metrics. Use when validating RNA-seq libraries before differential expression analysis.Votes: 0GitHub stars: 2
- Bio Sam Bam BasicsView, convert, and understand SAM/BAM/CRAM alignment files using samtools and pysam. Use when inspecting alignments, converting between formats, or understanding alignment file structure.Votes: 0GitHub stars: 2
- Bio Seq ObjectsCreate and manipulate Seq, MutableSeq, and SeqRecord objects using Biopython. Use when creating sequences from strings, modifying sequence data in-place, or building annotated sequence records.Votes: 0GitHub stars: 2
- Bio Sequence PropertiesCalculate sequence properties like GC content, molecular weight, isoelectric point, and GC skew using Biopython. Use when analyzing sequence composition, computing physical properties, or comparing sequences.Votes: 0GitHub stars: 2
- Bio Sequence SimilarityFind homologous sequences using iterative BLAST (PSI-BLAST), profile HMMs (HMMER), and reciprocal best hit analysis. Use when identifying orthologs, distant homologs, or protein family members where standard BLAST is not sensitive enough.Votes: 0GitHub stars: 2
- Bio Sequence SlicingSlice, extract, and concatenate biological sequences using Biopython. Use when extracting subsequences, joining sequences, or manipulating sequence regions by position.Votes: 0GitHub stars: 2
- Bio Single Cell Cell CommunicationInfer cell-cell communication networks from scRNA-seq data using CellChat, NicheNet, and LIANA for ligand-receptor interaction analysis. Use when inferring ligand-receptor interactions between cell types.Votes: 0GitHub stars: 2
- Bio Single Cell ClusteringDimensionality reduction and clustering for single-cell RNA-seq using Seurat (R) and Scanpy (Python). Use for running PCA, computing neighbors, clustering with Leiden/Louvain algorithms, generating UMAP/tSNE embeddings, and visualizing clusters. Use when performing dimensionality reduction and clustering on single-cell data.Votes: 0GitHub stars: 2
- Bio Single Cell Data IoRead, write, and create single-cell data objects using Seurat (R) and Scanpy (Python). Use for loading 10X Genomics data, importing/exporting h5ad and RDS files, creating Seurat objects and AnnData objects, and converting between formats. Use when loading, saving, or converting single-cell data formats.Votes: 0GitHub stars: 2
- Bio Single Cell Doublet DetectionDetect and remove doublets (multiple cells captured in one droplet) from single-cell RNA-seq data. Uses Scrublet (Python), DoubletFinder (R), and scDblFinder (R). Essential QC step before clustering to avoid artificial cell populations. Use when identifying and removing doublets from scRNA-seq data.Votes: 0GitHub stars: 2
- Bio Single Cell Lineage TracingReconstruct cell lineage trees from CRISPR barcode tracing or mitochondrial mutations. Use when studying clonal dynamics, cell fate decisions, or developmental trajectories.Votes: 0GitHub stars: 2
- Bio Single Cell Markers AnnotationFind marker genes and annotate cell types in single-cell RNA-seq using Seurat (R) and Scanpy (Python). Use for differential expression between clusters, identifying cluster-specific markers, scoring gene sets, and assigning cell type labels. Use when finding marker genes and annotating clusters.Votes: 0GitHub stars: 2
- Bio Single Cell Perturb SeqAnalyze Perturb-seq and CROP-seq CRISPR screening data integrated with scRNA-seq. Use when identifying gene function through pooled genetic perturbations in single cells.Votes: 0GitHub stars: 2
- Bio Single Cell PreprocessingQuality control, filtering, and normalization for single-cell RNA-seq using Seurat (R) and Scanpy (Python). Use for calculating QC metrics, filtering cells and genes, normalizing counts, identifying highly variable genes, and scaling data. Use when filtering, normalizing, and selecting features in single-cell data.Votes: 0GitHub stars: 2
- Bio Single Cell Trajectory InferenceInfer developmental trajectories and pseudotime from single-cell RNA-seq data using Monocle3, Slingshot, and scVelo for RNA velocity analysis. Use when inferring developmental trajectories or pseudotime.Votes: 0GitHub stars: 2
- Bio Small Rna Seq Differential MirnaPerform differential expression analysis of miRNAs between conditions using DESeq2 or edgeR with small RNA-specific considerations. Use when identifying miRNAs that change between treatment groups, disease states, or developmental stages.Votes: 0GitHub stars: 2
- Bio Small Rna Seq Mirdeep2 AnalysisDiscover novel miRNAs and quantify known miRNAs using miRDeep2 de novo prediction from small RNA-seq data. Use when identifying new miRNAs or performing comprehensive miRNA profiling with discovery.Votes: 0GitHub stars: 2
- Bio Small Rna Seq Mirge3 AnalysisFast miRNA quantification with isomiR detection and A-to-I editing analysis using miRge3. Use when quantifying known miRNAs quickly or analyzing isomiR variants and RNA editing.Votes: 0GitHub stars: 2
- Bio Small Rna Seq Smrna PreprocessingPreprocess small RNA sequencing data with adapter trimming and size selection optimized for miRNA, piRNA, and other small RNAs. Use when preparing small RNA-seq reads for downstream quantification or discovery analysis.Votes: 0GitHub stars: 2
- Bio Small Rna Seq Target PredictionPredict miRNA target genes using sequence-based algorithms and database lookups. Use when identifying potential mRNA targets of differentially expressed or functionally important miRNAs.Votes: 0GitHub stars: 2
- Bio Spatial Transcriptomics Image AnalysisProcess and analyze tissue images from spatial transcriptomics data using Squidpy. Extract image features, segment cells/nuclei, and compute morphological features from H&E or IF images. Use when processing tissue images for spatial transcriptomics.Votes: 0GitHub stars: 2
- Bio Spatial Transcriptomics Spatial CommunicationAnalyze cell-cell communication in spatial transcriptomics data using ligand-receptor analysis with Squidpy. Infer intercellular signaling, identify communication pathways, and visualize interaction networks. Use when analyzing cell-cell communication in spatial context.Votes: 0GitHub stars: 2
- Bio Spatial Transcriptomics Spatial Data IoLoad spatial transcriptomics data from Visium, Xenium, MERFISH, Slide-seq, and other platforms using Squidpy and SpatialData. Read Space Ranger outputs, convert formats, and access spatial coordinates. Use when loading Visium, Xenium, MERFISH, or other spatial data.Votes: 0GitHub stars: 2
- Bio Spatial Transcriptomics Spatial DeconvolutionEstimate cell type composition in spatial transcriptomics spots using reference-based deconvolution. Use cell2location, RCTD, SPOTlight, or Tangram to infer cell type proportions from scRNA-seq references. Use when estimating cell type composition in spatial spots.Votes: 0GitHub stars: 2
- Bio Spatial Transcriptomics Spatial DomainsIdentify spatial domains and tissue regions in spatial transcriptomics data using Squidpy and Scanpy. Cluster spots considering both expression and spatial context to define anatomical regions. Use when identifying tissue domains or spatial regions.Votes: 0GitHub stars: 2
- Bio Spatial Transcriptomics Spatial MultiomicsAnalyze high-resolution spatial platforms like Slide-seq, Stereo-seq, and Visium HD. Use when working with subcellular resolution or high-density spatial data.Votes: 0GitHub stars: 2
- Bio Spatial Transcriptomics Spatial NeighborsBuild spatial neighbor graphs for spatial transcriptomics data using Squidpy. Compute k-nearest neighbors, Delaunay triangulation, and radius-based connectivity for downstream spatial analyses. Use when building spatial neighborhood graphs.Votes: 0GitHub stars: 2
- Bio Spatial Transcriptomics Spatial PreprocessingQuality control, filtering, normalization, and feature selection for spatial transcriptomics data. Calculate QC metrics, filter spots/cells, normalize counts, and identify highly variable genes. Use when filtering and normalizing spatial transcriptomics data.Votes: 0GitHub stars: 2
- Bio Spatial Transcriptomics Spatial StatisticsCompute spatial statistics for spatial transcriptomics data using Squidpy. Calculate Moran's I, Geary's C, spatial autocorrelation, co-occurrence analysis, and neighborhood enrichment. Use when computing spatial autocorrelation or co-occurrence statistics.Votes: 0GitHub stars: 2
- Bio Spatial Transcriptomics Spatial VisualizationVisualize spatial transcriptomics data using Squidpy and Scanpy. Create tissue plots with gene expression, clusters, and annotations overlaid on histology images. Use when visualizing spatial expression patterns.Votes: 0GitHub stars: 2
- Bio Sra DataDownload sequencing data from NCBI SRA using the SRA toolkit. Use when downloading FASTQ files from SRA accessions, prefetching large datasets, or validating SRA downloads.Votes: 0GitHub stars: 2
- Bio Structural Biology Alphafold PredictionsAccess and analyze AlphaFold protein structure predictions. Use when you need predicted structures for proteins without experimental structures, or confidence scores (pLDDT).Votes: 0GitHub stars: 2
- Bio Structural Biology Modern Structure PredictionPredict protein structures using modern ML models including AlphaFold3, ESMFold, Chai-1, and Boltz-1. Use when predicting structures for novel proteins, protein complexes, or when comparing predictions across multiple methods.Votes: 0GitHub stars: 2
- Bio Tcr Bcr Analysis Immcantation AnalysisAnalyze BCR repertoires for somatic hypermutation, clonal lineages, and B cell phylogenetics using the Immcantation framework. Use when studying B cell affinity maturation, germinal center dynamics, or antibody evolution.Votes: 0GitHub stars: 2