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Quality control of phasing and imputation results. Filter by INFO scores, assess accuracy, and prepare imputed data for downstream analysis. Use when filtering low-quality imputed variants or validating imputat...
Call SNPs and indels from aligned reads using bcftools mpileup and call. Use when detecting variants from BAM files or generating VCF from alignments.
End-to-end multi-omics integration workflow. Orchestrates data harmonization, MOFA/mixOmics integration, factor interpretation, and downstream analysis across transcriptomics, proteomics, metabolomics, and othe...
Import transcript-level quantifications from Salmon/kallisto into R for gene-level analysis with DESeq2/edgeR using tximport or tximeta.
Unsupervised clustering and cell type identification for flow/mass cytometry. Covers FlowSOM, Phenograph, and CATALYST workflows. Use when discovering cell populations in high-dimensional cytometry data without...
Generate alignment statistics using samtools flagstat, stats, depth, and coverage. Use when assessing alignment quality, calculating coverage, or generating QC reports.
Polish assemblies and call variants from Oxford Nanopore data using medaka. Uses neural networks trained on specific basecaller versions. Use when improving ONT-only assemblies or calling variants from Nanopore...
Download, prepare, and manage reference panels for phasing and imputation. Covers 1000 Genomes, HRC, and TOPMed panels. Use when setting up imputation infrastructure or selecting appropriate reference panels fo...
All-in-one read preprocessing with fastp including adapter trimming, quality filtering, deduplication, base correction, and HTML report generation. Use when preprocessing Illumina data and wanting a single fast...
Filter alignments by flags, mapping quality, and regions using samtools view and pysam. Use when extracting specific reads, removing low-quality alignments, or subsetting to target regions.
Generate consensus sequences and manage reference files using samtools. Use when creating consensus from alignments, indexing references, or creating sequence dictionaries.
Interactive cell type annotation for IMC data. Covers napari-based annotation, marker-guided labeling, training data generation, and annotation validation. Use when manually annotating cell types for training c...
End-to-end ChIP-seq workflow from FASTQ files to annotated peaks. Covers QC, alignment, peak calling with MACS3, and peak annotation with ChIPseeker.
Infer developmental trajectories and pseudotime from single-cell RNA-seq data using Monocle3, Slingshot, and scVelo for RNA velocity analysis.
Differentially methylated region (DMR) detection using methylKit tiles, bsseq BSmooth, and DMRcate. Use when identifying contiguous genomic regions with methylation differences between experimental conditions o...
Comprehensive quality control for flow cytometry and CyTOF data. Covers flow rate stability, signal drift, margin events, dead cell exclusion, and batch QC. Use when assessing acquisition quality or identifying...
Work with sparse matrices for memory-efficient storage of count data. Use when dealing with single-cell data or large bulk RNA-seq datasets where most values are zero.
Call copy number variants using GATK best practices workflow. Supports both somatic (tumor-normal) and germline CNV detection from WGS or WES data. Use when following GATK best practices or integrating CNV call...
Similarity Network Fusion (SNF) for patient stratification using multi-omics data. Integrates multiple data types into a unified patient similarity network.
Find nearest features, search within windows, and extend intervals using closest, window, flank, and slop operations. Use when performing TSS proximity analysis, assigning enhancers to genes, defining promoter...
Identifies super-enhancers from H3K27ac ChIP-seq data using ROSE and related tools. Use when studying cell identity genes, cancer-associated regulatory elements, or master transcription factor binding regions t...
End-to-end GWAS workflow from VCF to association results. Covers PLINK QC, population structure correction, and association testing for case-control or quantitative traits.
Metagenome assembly from long reads using metaFlye and metaSPAdes with binning strategies. Use when reconstructing genomes from microbial communities, recovering metagenome-assembled genomes (MAGs), or resolvin...
Detect 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 ar...
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