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Claude Skills by HolobiomicsLab
github.com/HolobiomicsLab7,765 skills0 installs8,278 views
- Hi C Map Artifact ValidationUse when after executing the Juicer pipeline on raw Hi-C FASTQ files, to confirm that the pipeline has generated the expected .hic output artifact and that the contact matrix construction and normalization steps completed without error.Votes: 0GitHub stars: 15
- Hi C Matrix Normalization Pipeline SetupUse when before running HiC-Pro's normalization stage on aligned Hi-C BAM files. Specifically, when you have SAM/BAM-formatted aligned Hi-C reads that need bias correction and matrix balancing to produce normalized contact maps suitable for downstream chromatin structure analysis.Votes: 0GitHub stars: 15
- Hi C Normalization And Bias CorrectionUse when after generating raw Hi-C contact matrices from aligned reads (post-merge, pre-analysis).Votes: 0GitHub stars: 15
- Hic Contact Map Feature AnnotationUse when you have completed Hi-C map generation (producing .hic files from aligned reads) and need to detect and annotate topological features such as chromatin loops, topologically associating domains (TADs), or interaction peaks.Votes: 0GitHub stars: 15
- Hic Map Format ValidationUse when after running the ENCODE Hi-C uniform processing pipeline or Juicer on FASTQ input data and generating a .hic output file.Votes: 0GitHub stars: 15
- Hierarchical Dendrogram InterpretationUse when you have a methylBase object containing aligned methylation calls across multiple samples and need to verify whether samples cluster by expected experimental condition (e.g., test vs. control) or identify unexpected sample relationships.Votes: 0GitHub stars: 15
- Hpc Cluster Scheduler ConfigurationUse when when installing HiC-Pro on a shared HPC cluster or multi-node computing environment where job submission must be routed through a scheduler rather than running locally.Votes: 0GitHub stars: 15
- Illumina 450k Epic Dataset LoadingUse when you have raw .idat files or a beta-valued matrix from an Illumina HumanMethylation450 or EPIC array experiment and need to import the full probe set into R for downstream quality control, normalization, and differential methylation analysis.Votes: 0GitHub stars: 15
- Illumina Array Data Processing EpicUse when you have raw Illumina EPIC or 450k methylation array data (.idat files or beta-valued matrices) and need to perform comprehensive quality assessment, probe correction, batch effect adjustment, and identification of differentially methylated regions or blocks across sample groups.Votes: 0GitHub stars: 15
- Illumina Methylation Array PreprocessingUse when your input is raw .idat files or a beta-valued matrix from Illumina HumanMethylation450 or EPIC arrays, and you need to remove unreliable probes (those with detection p-value > 0.01 or insufficient bead counts) before performing differential methylation or other downstream analyses.Votes: 0GitHub stars: 15
- Interactive Visualization Interpretation Methylation ResultsUse when after running ChAMP detection functions (champ.Votes: 0GitHub stars: 15
- Iterative Lsi Dimensionality ReductionUse when when you have aligned paired scATAC-seq and scRNA-seq data from the same cells (multiome data) and need to create a single reduced-dimension coordinate space that integrates both chromatin accessibility and gene expression signals for joint clustering, trajectory analysis, or visualization.Votes: 0GitHub stars: 15
- Juicer Cli Tool ExecutionUse when you have a pre-generated .hic contact map file (from Juicer pipeline or external source) and need to systematically call chromatin loops, detect topologically associating domains, or annotate other structural features without re-running the full alignment and contact matrix construction.Votes: 0GitHub stars: 15
- Juicer Pipeline Configuration And ExecutionUse when you have raw Hi-C FASTQ files from a high-throughput chromatin conformation capture experiment and need to generate a normalized contact matrix (.hic file) for downstream genomic analysis.Votes: 0GitHub stars: 15
- Kilobase Resolution Contact Map AnalysisUse when you have paired-end Hi-C FASTQ files from a public repository (NCBI SRA, GEO, or ENCODE-deposited) and need to produce standardized .hic binary contact maps that conform to ENCODE reference formats and integrity standards for downstream 3D genome analysis.Votes: 0GitHub stars: 15
- Kilobase Resolution Genomics AnalysisUse when you have raw Hi-C FASTQ data and need to generate contact maps at kilobase resolution, or you have pre-generated .hic files and need to annotate structural features (loops, domains) for downstream 3D genome analysis.Votes: 0GitHub stars: 15
- Kmer Annotation Matrix AssemblyUse when you have filtered peak counts from ATAC or DNase-seq data (with GC bias correction and sample/peak filtering applied) and want to annotate peaks by k-mer content rather than known transcription factor motifs—particularly when comparing how k-mer size affects the magnitude of chromatin.Votes: 0GitHub stars: 15
- Kmer Motif Synergy AssessmentUse when after computing deviations for both motif and kmer annotations on the same chromVAR dataset, when you need to determine whether kmers and motifs are redundant predictors of chromatin accessibility variability or provide complementary information for downstream clustering, annotation, or.Votes: 0GitHub stars: 15
- Large Scale Single Cell Matrix LoadingUse when you have a single-cell count matrix with 10 million or more cells that must be processed through dimension reduction, clustering, or integration pipelines. Use it specifically before executing matrix-free spectral embedding (tl.Votes: 0GitHub stars: 15
- Leiden Clustering Resolution OptimizationUse when you have performed spectral dimension reduction on single-cell omics count matrices and wish to partition cells into discrete populations.Votes: 0GitHub stars: 15
- Library Module Organization And AccessibilityUse when you are building or extending a multi-module Python library for scientific computation (e.Votes: 0GitHub stars: 15
- Local Background Bias EstimationUse when you have paired ChIP and control BED/BEDPE files and need to account for local sequencing bias before peak calling. Use it specifically when control signal varies across genomic regions at multiple spatial scales (e.Votes: 0GitHub stars: 15
- Local Background Estimation Multiple ScalesUse when when performing ChIP-Seq peak calling with MACS3, after duplicate filtering and fragment length prediction (d), to construct the background model that will be compared against ChIP signal.Votes: 0GitHub stars: 15
- Macs3 Subcommand ChainingUse when when you have aligned ChIP-Seq reads (BED or BEDPE format) and a corresponding control sample, and you need explicit control over peak-calling parameters—including fragment-length prediction, local bias windows (d, slocal=1kb, llocal=10kb), background scaling, and score-cutoff.Votes: 0GitHub stars: 15
- Makefile Based Build System ConfigurationUse when when deploying a complex bioinformatics pipeline (e.g., HiC-Pro) that depends on multiple external tools with version constraints (samtools ≥1.9, bowtie2, R packages, Python libraries) and you need to verify their availability and configure their paths before running the analysis.Votes: 0GitHub stars: 15
- Memory Profiling And MonitoringUse when when benchmarking or validating the scalability of single-cell algorithms that claim linear or sublinear space complexity, particularly when processing datasets with ≥10 million cells.Votes: 0GitHub stars: 15
- Method Comparison Statistical SummarizationUse when you have extracted clustering or classification accuracy metrics (NMI, ARI, purity scores) for two or more competing methods evaluated on multiple datasets, and need to determine which method performs overall rather than on individual datasets alone.Votes: 0GitHub stars: 15
- Methylation Batch Effect DetectionUse when you have loaded a normalized beta-valued methylation matrix (e.Votes: 0GitHub stars: 15
- Methylation Data ClusteringUse when after merging methylation call files across all samples into a unified methylBase object (via unite()), when you need to assess whether biological replicates cluster together, identify unexpected sample groupings, or visualize global methylation similarity relationships before proceeding.Votes: 0GitHub stars: 15
- Methylation Hyper Hypo ClassificationUse when after calculating differential methylation across samples using calculateDiffMeth(), when you need to separately enumerate and extract hyper-methylated (increased methylation) versus hypo-methylated (decreased methylation) bases that meet both statistical significance (q-value < 0.Votes: 0GitHub stars: 15
- Methylation Object Merging And UnionUse when you have loaded individual methylation call files as methylRawList objects from bisulfite sequencing experiments (via methRead()) and need to perform base-level comparative analysis across two or more samples.Votes: 0GitHub stars: 15
- Methylation Probe Count ValidationUse when immediately after loading raw methylation array data using champ.load() or champ.import() to verify data integrity.Votes: 0GitHub stars: 15
- Methylation Region Genomic Context AssignmentUse when after identifying differentially methylated bases or regions (via calculateDiffMeth() and getMethylDiff()), when you need to characterize WHERE these methylation changes occur relative to gene structure and CpG density landscapes.Votes: 0GitHub stars: 15
- Methylation Region IdentificationUse when you have loaded normalized methylation beta-value matrices from Illumina EPIC or 450k arrays and need to move beyond single-CpG differential methylation testing to identify multi-CpG regions with coordinated differential methylation signals.Votes: 0GitHub stars: 15
- Methylbase Object HandlingUse when after reading in per-sample methylation call files with methRead() and obtaining methylRawList objects, but before calculating differential methylation or performing annotation.Votes: 0GitHub stars: 15
- Methylkit Database Mode ConfigurationUse when when analyzing DNA methylation data from bisulfite sequencing (RRBS, target-capture, or whole-genome) and the dataset is too large to fit comfortably in memory, or when you need to process multiple large samples sequentially without reloading data.Votes: 0GitHub stars: 15
- Module Import And Api VerificationUse when before invoking any Python module in a multi-step Hi-C processing pipeline, or when a dependency has been freshly installed or reinstalled.Votes: 0GitHub stars: 15
- Monocle3 Trajectory EmbeddingUse when you have an ArchR project object with dimensionality reduction results (LSI or combined dimensions from scATAC-seq ± scRNA-seq) and want to infer pseudotime trajectories and cell-state transitions.Votes: 0GitHub stars: 15
- Motif Annotation Correlation AnalysisUse when you have a chromVARDeviations object with multiple annotation sets (such as JASPAR motifs and kmers) and need to determine which annotation pairs are redundant (high correlation) versus synergistic (high synergy z-scores).Votes: 0GitHub stars: 15
- Motif Database Query And MatchingUse when you have a set of differentially accessible peaks (output from differential accessibility testing, e.g., tl.Votes: 0GitHub stars: 15
- Motif Enrichment Statistical TestingUse when after identifying a set of differentially accessible peaks (via tl.diff_test or equivalent), when you need to infer which transcription factors may regulate the observed chromatin state changes.Votes: 0GitHub stars: 15
- Motif Peak Overlap MatchingUse when you have a filtered set of non-overlapping peaks from ATAC-seq data and a collection of motifs (typically from JASPAR or similar databases), and you need to identify which peaks contain matches to which motifs as a prerequisite for computing motif-based deviation scores across samples.Votes: 0GitHub stars: 15
- Motif Site Occupancy ComparisonUse when you have bias-corrected ATAC-seq footprint signals (BigWig files) from two or more distinct conditions (e.Votes: 0GitHub stars: 15
- Multiome Data Ingestion Paired ModalitiesUse when you have independently generated or received both scATAC-seq peak count matrices and scRNA-seq gene expression matrices from the same set of cells (multiome experiment), and you need to perform joint analysis such as co-clustering, trajectory inference, or regulatory inference that.Votes: 0GitHub stars: 15
- Narrow Peak Calling Score ThresholdUse when after generating a q-value bedgraph track from ChIP-Seq pileup versus local lambda comparison, and you need to identify statistically significant narrow peaks with defined boundaries.Votes: 0GitHub stars: 15
- Narrow Peak Coordinate ValidationUse when after running macs3 callpeak with the -f BEDPE flag on paired-end ChIP-Seq data (e.g., CTCF_PE_ChIP_chr22_50k.bedpe.Votes: 0GitHub stars: 15
- Nucleotide Footprint Pattern RecognitionUse when you have aligned ATAC-seq BAM files and want to discriminate between transcription factor binding sites that are actually occupied by protein versus sites with matching sequence motifs that are unbound.Votes: 0GitHub stars: 15
- Numeric Range Validation BioinformaticsUse when after applying a quantitative analysis function (e.g., cooltools.insulation, contact frequency calculations) to Hi-C cooler files or other genomic datasets, validate that the output numeric columns contain values within plausible ranges (e.Votes: 0GitHub stars: 15
- Overdispersion Correction ApplicationUse when analyzing differential methylation from bisulfite sequencing data where you suspect overdispersion (variance exceeds binomial expectations), or when comparing uncorrected and corrected statistical tests to determine whether more stringent thresholds are justified by the data.Votes: 0GitHub stars: 15
- Paired Insertion Counting StrategyUse when you have loaded fragment data from single-cell ATAC-seq experiments into a backed AnnData object (with fragments stored in .obsm['fragment_paired'] or .Votes: 0GitHub stars: 15