GitHub
bio-workflows-crispr-screen-pipeline
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.
☆ 299Voir le skill
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GitHub
bio-primer-design-primer-basics
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.
☆ 299Voir le skill
GitHub
bio-crispr-screens-crispresso-editing
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...
☆ 299Voir le skill
GitHub
bio-fastq-quality
Work with FASTQ quality scores using Biopython. Use when analyzing read quality, filtering by quality, trimming low-quality bases, or generating quality reports.
☆ 299Voir le skill
GitHub
bio-spatial-transcriptomics-spatial-preprocessing
Quality control, filtering, normalization, and feature selection for spatial transcriptomics data. Calculate QC metrics, filter spots/cells, normalize counts, and identify highly variable genes.
☆ 299Voir le skill
GitHub
bio-data-visualization-circos-plots
Create circular genome visualizations with Circos and pyCircos. Display multi-track data including ideograms, genes, variants, CNVs, and interaction arcs.
☆ 299Voir le skill
GitHub
bio-workflows-hic-pipeline
End-to-end Hi-C analysis workflow from contact pairs to compartments, TADs, and loops. Covers cooler matrices, cooltools analysis, and visualization.
☆ 299Voir le skill
GitHub
bio-metabolomics-statistical-analysis
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...
☆ 299Voir le skill
GitHub
bio-de-results
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...
☆ 299Voir le skill
GitHub
bio-local-blast
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.
☆ 299Voir le skill
GitHub
bio-metagenomics-functional-profiling
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.
☆ 299Voir le skill
GitHub
bio-expression-matrix-counts-ingest
Load gene expression count matrices from various formats including CSV, TSV, featureCounts, Salmon, kallisto, and 10X. Use when importing quantification results for downstream analysis.
☆ 299Voir le skill
GitHub
bio-data-visualization-interactive-visualization
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...
☆ 299Voir le skill
GitHub
bio-hi-c-analysis-hic-visualization
Visualize Hi-C contact matrices, TADs, loops, and genomic features using matplotlib, cooltools, and HiCExplorer. Create triangle plots, virtual 4C, and multi-track figures.
☆ 299Voir le skill
GitHub
bio-proteomics-protein-inference
Protein grouping and inference from peptide identifications. Handles shared peptides, protein groups, and protein-level FDR control using parsimony and probabilistic approaches.
☆ 299Voir le skill
GitHub
bio-genome-assembly-contamination-detection
Detect contamination and assess genome quality using CheckM, CheckM2, GTDB-Tk, and GUNC for metagenome-assembled genomes and isolate assemblies.
☆ 299Voir le skill
GitHub
bio-expression-matrix-gene-id-mapping
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.
☆ 299Voir le skill
GitHub
bio-longread-qc
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...
☆ 299Voir le skill
GitHub
bio-sam-bam-basics
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.
☆ 299Voir le skill
GitHub
bio-sequence-similarity
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...
☆ 299Voir le skill
GitHub
bio-chipseq-peak-calling
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...
☆ 299Voir le skill
GitHub
bio-alignment-pairwise
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...
☆ 299Voir le skill
GitHub
bio-atac-seq-atac-peak-calling
Call accessible chromatin regions from ATAC-seq data using MACS3 with ATAC-specific parameters. Use when identifying open chromatin regions from aligned ATAC-seq BAM files, different from ChIP-seq peak calling.
☆ 299Voir le skill
GitHub
bio-pathway-go-enrichment
Gene Ontology over-representation analysis using clusterProfiler enrichGO. Tests whether GO terms are enriched in a gene list compared to background. Supports all three ontologies (BP, MF, CC), multiple ID type...
☆ 299Voir le skill
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.