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Claude Skills by HolobiomicsLab
github.com/HolobiomicsLab7,765 skills0 installs8,278 views
- Rnaseq Count Matrix AnalysisUse when you have a count matrix (genes × samples) from HTSeq, featureCounts, or transcript abundance quantification (Salmon, kallisto), a sample metadata table with experimental design, and you need to test for differential expression while controlling false discovery rate via independent.Votes: 0GitHub stars: 15
- Salmon Output ParsingUse when when you have salmon quant.sf.gz output files from pseudoalignment-based transcript quantification and need to convert transcript-level abundance estimates and counts into gene-level matrices for differential expression analysis with edgeR, DESeq2, or limma-voom.Votes: 0GitHub stars: 15
- Salmon Quantification Output VerificationUse when after running salmon quant with the --writeMappings/-z flag to produce SAM output, or when investigating discrepancies between the number of mapped reads reported in quant.sf and the actual number of records written to the output SAM file.Votes: 0GitHub stars: 15
- Sam Bam Mapping Record InspectionUse when after quantifying the same read set with two versions of a mapping/quantification tool (e.g., C++ salmon 1.11.Votes: 0GitHub stars: 15
- Sam Record Parsing And ValidationUse when salmon quant is run with the --writeMappings/-z flag and you need to verify that all mapped reads appear in the SAM output file.Votes: 0GitHub stars: 15
- Sample Metadata Preparation And AssignmentUse when before constructing a DESeqDataSet from any count matrix (whether from tximport, HTSeq, featureCounts, or raw counts). You have sample identifiers (run IDs, file names, or row names) and must link them to condition labels (e.Votes: 0GitHub stars: 15
- Scanpy Preprocessing Pipeline ExecutionUse when you have raw or minimally processed single-cell RNA-seq expression data loaded into an AnnData object (dense, sparse, or Dask-backed array as X), and you need to apply standardized preprocessing transformations (normalization, filtering, PCA) before downstream analysis such as clustering.Votes: 0GitHub stars: 15
- Scientific Task FormulationUse when you encounter a published scientific article or software paper that makes claims about data processing, analysis, or results, but the reproducibility context is unclear, artifacts are scattered, or the connection between claims and outputs is not immediately evident.Votes: 0GitHub stars: 15
- Seed Representation Variant ComparisonUse when you have observed mapping rate or quantification disagreement (e.g., >0.1% divergence in mapping rate or Pearson r < 0.Votes: 0GitHub stars: 15
- Selective Alignment Parameter TuningUse when you observe discrepancies in mapping rate or per-transcript quantification between two salmon implementations, or when the default chain-pruning thresholds (orphanChainSubThresh, postMergeChainSubThresh) are leaving a substantial fraction of reads unmapped (e.Votes: 0GitHub stars: 15
- Selective Alignment Sensitivity EvaluationUse when when comparing mapping outputs between two selective-alignment implementations (e.g., C++ vs. Rust port) on byte-identical reference indices and observing a multi-percentage-point gap in mapping rate or read assignments.Votes: 0GitHub stars: 15
- Seurat Workflow Orchestration For ScrnaseqUse when you have a raw or Seurat object-backed scRNA-seq expression matrix and need to: (1) stabilize variance across genes with SCTransform normalization, (2) extract feature loadings in reduced dimensionality space via reverse PCA to use as input for GESECA or other coregulation-based enrichment.Votes: 0GitHub stars: 15
- Single Cell Graph Construction NeighborhoodUse when you have preprocessed single-cell RNA-seq data (normalized and dimensionality-reduced via PCA) and need to establish cell-to-cell connectivity for trajectory inference, clustering validation, or graph-based visualization.Votes: 0GitHub stars: 15
- Single Cell Rna Seq NormalizationUse when immediately after loading raw single-cell gene expression count matrices (AnnData objects) and before identifying highly variable genes or performing dimensionality reduction.Votes: 0GitHub stars: 15
- Single Cell Rna Seq Quality Control And NormalizationUse when when you have a raw or minimally processed scRNA-seq dataset (e.g., a Seurat object loaded from GEO) and need to prepare it for pathway enrichment or coregulation analysis.Votes: 0GitHub stars: 15
- Sparse Matrix Csr Format AssemblyUse when when you have computed k-nearest neighbor indices and distances (e.Votes: 0GitHub stars: 15
- Sparse Matrix Format HandlingUse when your input is an AnnData object with expression matrix X as a sparse scipy matrix or Dask-backed array, and you need to apply preprocessing functions (normalization, PCA, filtering) that could trigger eager materialization.Votes: 0GitHub stars: 15
- Sparse Matrix Verification And ValidationUse when after calling squidpy.gr.spatial_neighbors or any graph-building operation that outputs sparse matrices to adata.Votes: 0GitHub stars: 15
- Spatial Coordinate Indexing Dense To SparseUse when you have computed k-nearest neighbors for spatial coordinates (e.g., via pynndescent or another NN backend) and need to store the resulting adjacency and distance information in a memory-efficient format compatible with downstream graph algorithms.Votes: 0GitHub stars: 15
- Spatial Coordinate Integration With Imaging DataUse when you have a spatial omics dataset (AnnData object with coordinate columns like 'x', 'y', 'z') and an associated tissue image file (e.g., TIFF, PNG, or HE-stained histology), and you need to extract image-based morphological features (e.Votes: 0GitHub stars: 15
- Spatial Enrichment Score ValidationUse when after executing a spatial statistics function (e.g., squidpy.gr.sepal) on a spatial transcriptomics dataset in AnnData format, and before using the computed rankings or enrichment scores in downstream analysis.Votes: 0GitHub stars: 15
- Spatial Gene Ranking ComputationUse when when working with spatial transcriptomics datasets (e.g., Slide-seq v2, MERFISH) stored in AnnData format and you need to identify genes whose expression shows significant spatial patterns or enrichment within tissue regions.Votes: 0GitHub stars: 15
- Spatial Neighbor Graph ConstructionUse when when you have spatial molecular data (e.g., Visium, imaging-based cytometry) stored in an AnnData object with coordinate information in .Votes: 0GitHub stars: 15
- Spatial Neighbor Graph Properties ValidationUse when after calling squidpy.gr.spatial_neighbors on an AnnData object containing spatial coordinates in obsm.Votes: 0GitHub stars: 15
- Spatial Omics Dataset LoadingUse when you have a spatial transcriptomics experiment (e.Votes: 0GitHub stars: 15
- Spatial Statistics InterpretationUse when when you have a spatial molecular dataset (e.g., Visium, MERFISH) with categorical cell-type or feature annotations and want to test whether specific categories are preferentially located near or away from each other in tissue space, beyond what random spatial distribution would predict.Votes: 0GitHub stars: 15
- Splicing Matrix NormalizationUse when you have transcript-level quantification (TPM or counts from Salmon/kallisto) and need to quantify the inclusion level of specific alternative splicing events (exon skipping, intron retention, alternative splice sites, etc.) in a form suitable for differential splicing analysis across.Votes: 0GitHub stars: 15
- Statistical Comparison P Value ConservationUse when you have run the same pathway enrichment analysis (e.Votes: 0GitHub stars: 15
- Statistical Hypothesis Testing Rna SeqUse when you have RNA-seq count matrices (from alignment, transcript quantification, or HTSeq-count files) and need to test for differential expression between two or more conditions while controlling for batch effects or other covariates.Votes: 0GitHub stars: 15
- Statistical Precision Comparison Ranked OutputsUse when when a statistical method offers a parameter to trade computational cost for precision (e.Votes: 0GitHub stars: 15
- Statistical Ranking Wilcoxon TestUse when when you have leiden or louvain cluster assignments in single-cell data (stored in adata.obs) and need to identify cluster-specific marker genes.Votes: 0GitHub stars: 15
- Temporal Gene Expression DynamicsUse when you have time-ordered gene expression data (e.Votes: 0GitHub stars: 15
- Test Failure Diagnosis And Logging AnalysisUse when you have modified the Scanpy codebase (e.g., added a feature or bugfix) and need to confirm that all unit and integration tests pass before submitting a pull request, or when a CI workflow fails and you need to reproduce the failure locally to diagnose the root cause.Votes: 0GitHub stars: 15
- Trajectory Inference PreprocessingUse when you have raw or normalized single-cell RNA-seq expression data stored in an AnnData object (`.h5ad` format) and your analysis goal is to infer developmental or differentiation trajectories.Votes: 0GitHub stars: 15
- Transcript Abundance Correlation AnalysisUse when when validating a new or reimplemented quantification tool against a reference implementation on the same dataset and index, or when investigating whether changes to seed representation, chain pruning thresholds, or other algorithmic parameters affect downstream abundance estimates.Votes: 0GitHub stars: 15
- Transcript Abundance Quantification ImportUse when you have transcript abundance files (e.g., Salmon quant.sf.gz, kallisto abundance.h5, RSEM .isoforms.results) from a quantification tool and need to construct a gene-level count matrix for DESeq2 analysis.Votes: 0GitHub stars: 15
- Transcript Event ExtractionUse when you have a genome annotation GTF file and need to identify all transcript-level alternative splicing events (exon skipping, intron retention, alternative splice sites, mutually exclusive exons, alternative first/last exons) before quantifying their inclusion levels (PSI) across samples or.Votes: 0GitHub stars: 15
- Transcript Expression Quantification HandlingUse when you have transcript abundance estimates from RNA-seq quantification tools (e.Votes: 0GitHub stars: 15
- Transcript Level Abundance ImportUse when you have transcript-level quantification files (quant.sf.gz or quant.gz) from salmon, sailfish, kallisto, or oarfish and need to aggregate them into gene-level or transcript-level count, abundance, and length matrices for input to DESeq2, edgeR, or limma-voom.Votes: 0GitHub stars: 15
- Transcript Level Count AggregationUse when you have transcript-level abundance and count estimates from salmon, sailfish, kallisto, or oarfish and need gene-level matrices for downstream differential analysis with edgeR, DESeq2, or limma-voom.Votes: 0GitHub stars: 15
- Transcript Quantification Benchmark ComparisonUse when you have two implementations of the same quantification method (or major versions) and observe a persistent disagreement in mapped-read counts, per-read alignment agreement, or abundance correlations on the same reference index and read set.Votes: 0GitHub stars: 15
- Transcript Quantification IntegrationUse when you have transcript quantification output (TPM or raw counts) from a pseudo-aligner (Salmon or kallisto) and an ioe/ioi event definition file from SUPPA2's generateEvents step, and you need to calculate PSI values—the relative inclusion level of alternative splicing events—across multiple.Votes: 0GitHub stars: 15
- Transcript To Gene AggregationUse when when you have transcript-level quantification files (e.g., Salmon quant.sf.gz, kallisto abundance.h5, or RSEM .results) and need to construct a gene-level count matrix for DESeq2 differential expression testing.Votes: 0GitHub stars: 15
- Transcript To Gene MappingUse when you have transcript-level quantification files (salmon quant.sf.gz, kallisto, or Sailfish output) and need to perform gene-level differential expression analysis.Votes: 0GitHub stars: 15
- Umap Embedding VisualizationUse when after completing PCA and k-nearest neighbor graph construction on preprocessed, log-normalized, highly-variable-gene-filtered single-cell RNA-seq data (stored in an AnnData object), compute UMAP embeddings when you need a 2-D visualization for cluster inspection, cell-type annotation, or.Votes: 0GitHub stars: 15
- Uncertainty Aware Significance AssessmentUse when you have PSI matrices for two or more conditions with replicates per condition, and you need to determine which alternative splicing events show significant changes between conditions while accounting for measurement uncertainty that scales with transcript expression levels.Votes: 0GitHub stars: 15
- RouterUse when a task needs a skill from ASB Metabolomics — CE-MS — search this unit's 113 evidence-grounded skills, then apply and optionally ground the one that fits.Votes: 0GitHub stars: 15
- RouterUse when a task needs a skill from ASB Metabolomics — direct-infusion-MS — search this unit's 97 evidence-grounded skills, then apply and optionally ground the one that fits.Votes: 0GitHub stars: 15
- RouterUse when a task needs a skill from ASB Metabolomics — GC-MS — search this unit's 367 evidence-grounded skills, then apply and optionally ground the one that fits.Votes: 0GitHub stars: 15
- RouterUse when a task needs a skill from ASB Metabolomics — ion-mobility-MS — search this unit's 385 evidence-grounded skills, then apply and optionally ground the one that fits.Votes: 0GitHub stars: 15