HolobiomicsLab/asb-skill-collections

HolobiomicsLab/asb-skill-collections

Skill Claude CodeCodex

Use when you have raw .idat files or beta-valued matrices from HumanMethylation450 (450k) arrays and need to remove low-quality probes, correct for technical artifacts (batch effects, type-2 probe bias), and normalize the data before performing differential methylation analysis or DMR detection.

HolobiomicsLab/asb-skill-collections

Skill Claude CodeCodex

Use when when working with large single-cell ATAC-seq or multi-omics datasets where in-memory storage is infeasible (>1M cells), and you need to iteratively add or modify count matrices (tile-based, peak-based, or gene-based) while preserving fragment-level data for reproducibility and re-analysis.

HolobiomicsLab/asb-skill-collections

Skill Claude CodeCodex

Use when you have a processed ArchR project object (containing peak calls, cell barcodes, and quality control metadata) and need to: (1) reduce dimensionality of the peak matrix via iterative LSI; (2) integrate multimodal data by combining ATAC and RNA dimensions.

HolobiomicsLab/asb-skill-collections

Skill Claude CodeCodex

Use when when you have aligned ATAC-seq BAM files and need to quantify Tn5 transposase insertion patterns around specific genomic coordinates (motif sites, peaks, regulatory regions) to detect transcription factor occupancy footprints or compare chromatin accessibility between bound and unbound.

HolobiomicsLab/asb-skill-collections

Skill Claude CodeCodex

Use when when you need to assess whether a given ATAC-seq clustering method (or variant) is competitive on your data or when evaluating which published method to adopt.

HolobiomicsLab/asb-skill-collections

Skill Claude CodeCodex

Use when when you have processed scATAC-seq data (peak calling complete, cell-barcode matrix generated) and need to register it into ArchR for downstream multiome analysis alongside scRNA-seq gene expression data.

HolobiomicsLab/asb-skill-collections

Skill Claude CodeCodex

Use when you have completed Tn5 insertion bias correction on ATAC-seq reads and now need to quantify footprint signal strength (signal depletion around TF-bound sites) across accessible chromatin regions before classifying individual TF binding sites.

HolobiomicsLab/asb-skill-collections

Skill Claude CodeCodex

Use when after differential peak analysis (tl.difftest) has identified peaks that differ in accessibility across cell types or conditions.

HolobiomicsLab/asb-skill-collections

Skill Claude CodeCodex

Use when you have aligned ATAC-seq BAM files and need to detect transcription factor binding sites via footprint analysis. The skill is essential because raw Tn5 insertion signal contains systematic bias toward certain DNA sequences.

HolobiomicsLab/asb-skill-collections

Skill Claude CodeCodex

Use when you have raw ATAC-seq BAM files and need to perform footprinting analysis to detect transcription factor binding through Tn5 insertion patterns.

HolobiomicsLab/asb-skill-collections

Skill Claude CodeCodex

Use when after computing expected accessibility from filtered peak and sample counts, and before computing final deviation scores. Use this skill when working with sparse ATAC-seq or DNase-seq data where GC bias and accessibility depth are known confounders of motif-associated variability.

HolobiomicsLab/asb-skill-collections

Skill Claude CodeCodex

Use when before invoking pp.makefragmentfile on a BAM file from alignment or external sources, especially when the BAM's sort order is unknown or when integrating BAM files from multiple sequencing platforms (10X, standard genomics pipelines, or custom aligners) into a unified SnapATAC2 analysis.

HolobiomicsLab/asb-skill-collections

Skill Claude CodeCodex

Use when after running TOBIAS ATACorrect to generate bias-corrected signal tracks from aligned ATAC-seq reads. Use this skill when you have corrected cutsite signal (as .

HolobiomicsLab/asb-skill-collections

Skill Claude CodeCodex

Use when when you have coordinate-sorted BAM files from single-cell ATAC-seq experiments (e.g., 10X Genomics scATAC-seq) and need to generate a compressed fragment file for efficient downstream analysis. Use this step before matrix generation, clustering, or peak calling in SnapATAC2.

HolobiomicsLab/asb-skill-collections

Skill Claude CodeCodex

Use when you have a coordinate-sorted BAM file from a single-cell ATAC-seq experiment (especially 10X Genomics platforms) and need to extract per-fragment information including cell barcodes, fragment coordinates, and quality metrics for downstream analysis in SnapATAC2 or compatible tools.

HolobiomicsLab/asb-skill-collections

Skill Claude CodeCodex

Use when apply this filter after loading raw .idat files or beta-valued matrices from HumanMethylation450 or EPIC methylation arrays when you need to remove probes with insufficient bead counts that may introduce measurement noise or bias into downstream differential methylation or enrichment.

HolobiomicsLab/asb-skill-collections

Skill Claude CodeCodex

Use when you have extracted quantitative genomic features (e.g., insulation scores, boundary annotations) as a pandas DataFrame with bin coordinates and boolean or numeric columns, and need to export them as BED format for visualization in genome browsers (e.

HolobiomicsLab/asb-skill-collections

Skill Claude CodeCodex

Use when after computing per-bin coverage depth using cooltools.coverage() on a loaded cooler object, when you need to (1) share the coverage track with non-Python tools, (2) visualize it in a genome browser, or (3) integrate it with downstream analyses that expect bedGraph or tabular input.

HolobiomicsLab/asb-skill-collections

Skill Claude CodeCodex

Use when you have aligned ChIP-Seq reads (in BED or BEDPE format) and need to convert them into quantitative genome-wide signal tracks (coverage, p-value, or q-value scores) for downstream statistical comparison or peak detection.

HolobiomicsLab/asb-skill-collections

Skill Claude CodeCodex

Use when you have generated or received bedGraph files from paired-end sequencing (via bedtools genomecov or similar) and need to verify they conform to UCSC bedGraph format before passing them to peak-calling tools like SEACR.

HolobiomicsLab/asb-skill-collections

Skill Claude CodeCodex

Use when your ChIP-Seq input is paired-end sequencing data stored in BEDPE format (e.g., CTCFPEChIPchr2250k.bedpe.gz), and you need to estimate fragment length and call peaks while respecting the paired nature of the reads rather than treating them as independent single-end alignments.

HolobiomicsLab/asb-skill-collections

Skill Claude CodeCodex

Use when you are reproducing a comparative benchmarking claim (e.

HolobiomicsLab/asb-skill-collections

Skill Claude CodeCodex

Use when after computeDeviations has generated a SummarizedExperiment object with z-score assays reflecting bias-corrected deviations of observed vs. expected accessibility at motif or kmer sites.

HolobiomicsLab/asb-skill-collections

Skill Claude CodeCodex

Use when after bias correction of ATAC-seq reads (via ATACorrect) when you have a bias-corrected bigWig file and need to measure transcription factor footprint strength within defined accessible regions (peaks, motif sites, or called footprint boundaries).