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Generate 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 initia...
Detect copy number variants from targeted/exome sequencing using CNVkit. Supports tumor-normal pairs, tumor-only, and germline CNV calling. Use for WES or targeted panel sequencing.
End-to-end CRISPR screen analysis from FASTQ to hit genes. Orchestrates guide counting, QC, statistical analysis with MAGeCK, and hit calling with multiple methods.
Design PCR primers for a target sequence using primer3-py. Specify target regions, product size, melting temperature, and other constraints. Returns ranked primer pairs with quality metrics.
CRISPResso2 for analyzing CRISPR gene editing outcomes. Quantifies indels, HDR efficiency, and generates comprehensive editing reports. Use when analyzing amplicon sequencing data from CRISPR editing experiment...
Work with FASTQ quality scores using Biopython. Use when analyzing read quality, filtering by quality, trimming low-quality bases, or generating quality reports.
Quality control, filtering, normalization, and feature selection for spatial transcriptomics data. Calculate QC metrics, filter spots/cells, normalize counts, and identify highly variable genes.
Create circular genome visualizations with Circos and pyCircos. Display multi-track data including ideograms, genes, variants, CNVs, and interaction arcs.
End-to-end Hi-C analysis workflow from contact pairs to compartments, TADs, and loops. Covers cooler matrices, cooltools analysis, and visualization.
Statistical analysis for metabolomics data. Covers univariate testing, multivariate methods (PCA, PLS-DA), and biomarker discovery. Use when identifying differentially abundant metabolites or building classific...
Extract, filter, annotate, and export differential expression results from DESeq2 or edgeR. Use for identifying significant genes, applying multiple testing corrections, adding gene annotations, and preparing r...
Run local BLAST searches using BLAST+ command-line tools. Use for fast unlimited searches, custom databases, large-scale analysis, and when NCBI servers are slow or unavailable.
Profile functional potential of metagenomes using HUMAnN3 and similar tools. Use when you need pathway abundances, gene family counts, or functional annotations from metagenomic data.
Load gene expression count matrices from various formats including CSV, TSV, featureCounts, Salmon, kallisto, and 10X. Use when importing quantification results for downstream analysis.
Create interactive HTML plots with plotly and bokeh for exploratory data analysis and web-based sharing of omics visualizations. Use when building zoomable, hoverable plots for data exploration or web dashboard...
Visualize Hi-C contact matrices, TADs, loops, and genomic features using matplotlib, cooltools, and HiCExplorer. Create triangle plots, virtual 4C, and multi-track figures.
Protein grouping and inference from peptide identifications. Handles shared peptides, protein groups, and protein-level FDR control using parsimony and probabilistic approaches.
Detect contamination and assess genome quality using CheckM, CheckM2, GTDB-Tk, and GUNC for metagenome-assembled genomes and isolate assemblies.
Convert between gene identifier systems including Ensembl, Entrez, HGNC symbols, and UniProt. Use when you need to map IDs for pathway analysis or to match different data sources.
Quality control for long-read sequencing data using NanoPlot, NanoStat, and chopper. Generate QC reports, filter reads by length and quality, and visualize read characteristics. Use when assessing ONT or PacBio...
View, convert, and understand SAM/BAM/CRAM alignment files using samtools and pysam. Use when inspecting alignments, converting between formats, or understanding alignment file structure.
Find homologous sequences using iterative BLAST (PSI-BLAST), profile HMMs (HMMER), and reciprocal best hit analysis. Use for identifying orthologs, distant homologs, and protein family members when standard BLA...
ChIP-seq peak calling using MACS3 (or MACS2). Call narrow peaks for transcription factors or broad peaks for histone modifications. Supports input control, fragment size modeling, and various output formats inc...
Perform pairwise sequence alignment using Biopython Bio.Align.PairwiseAligner. Use for comparing two sequences, finding optimal alignments, scoring similarity, and identifying local or global matches between DN...
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.