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Perform differential expression analysis using edgeR in R/Bioconductor. Use for analyzing RNA-seq count data with the quasi-likelihood F-test framework, creating DGEList objects, normalization, dispersion estim...
Validate PCR primers for specificity, dimers, hairpins, and secondary structures using primer3-py thermodynamic calculations. Check self-complementarity, heterodimer formation, and 3' stability.
Load, convert, and manipulate Hi-C contact matrices using cooler format. Read .cool/.mcool files, convert from .hic format, access matrix data, and export to different formats.
Calculate sequence properties like GC content, molecular weight, isoelectric point, and GC skew using Biopython. Use when analyzing sequence composition, computing physical properties, or comparing sequences.
Calculate read depth and coverage across genomic intervals using bedtools genomecov and coverage. Generate bedGraph files, compute per-base depth, and summarize coverage statistics. Use when assessing sequencin...
Find patterns, motifs, and subsequences in biological sequences using Biopython. Use when searching for transcription factor binding sites, regulatory elements, or any sequence pattern. For restriction enzyme a...
Load spatial transcriptomics data from Visium, Xenium, MERFISH, Slide-seq, and other platforms using Squidpy and SpatialData. Read Space Ranger outputs, convert formats, and access spatial coordinates.
Convert raw Nanopore signal data (FAST5/POD5) to nucleotide sequences using Dorado or Guppy basecallers. Covers model selection, GPU acceleration, modified base detection, and quality filtering. Use when proces...
Call topologically associating domains (TADs) from Hi-C data using insulation score, HiCExplorer, and other methods. Identify domain boundaries and hierarchical domain structure.
Specialized lipidomics analysis for lipid identification, quantification, and pathway interpretation. Covers LC-MS lipidomics with LipidSearch, MS-DIAL, and LipidMaps annotation. Use when analyzing lipid classe...
Modify protein structures using Biopython Bio.PDB. Use for transforming coordinates, removing atoms or residues, adding new entities, modifying B-factors and occupancies, renumbering residues, and building stru...
End-to-end metabolomics workflow from raw MS data to pathway analysis. Orchestrates XCMS preprocessing, annotation, normalization, statistical analysis, and pathway mapping.
Targeted metabolomics analysis using MRM/SRM with standard curves. Covers absolute quantification, method validation, and quality assessment. Use when quantifying specific metabolites using calibration curves a...
Parse and write protein structure files using Biopython Bio.PDB. Use for reading PDB, mmCIF, and MMTF files, downloading structures from RCSB PDB, extracting header information, and writing structures to variou...
MS-DIAL-based metabolomics preprocessing as alternative to XCMS. Covers peak detection, alignment, annotation, and export for downstream analysis. Use when processing MS-DIAL output files for R/Python analysis...
Metabolite identification from m/z and retention time. Covers database matching, MS/MS spectral matching, and confidence level assignment. Use when assigning compound identities to detected features in untarget...
Post-translational modification analysis including phosphorylation, acetylation, and ubiquitination. Covers site localization, motif analysis, and quantitative PTM analysis. Use when analyzing phosphoproteomic...
Statistical methods for calling hits in CRISPR screens. Covers MAGeCK, BAGEL2, drugZ, and custom approaches for identifying essential and resistance genes. Use when identifying significant genes from screen cou...
End-to-end copy number variant detection workflow from BAM files. Covers CNVkit analysis for exome/targeted sequencing with visualization and annotation.
Spatial analysis of cell neighborhoods and interactions in IMC data. Covers neighbor graphs, spatial statistics, and interaction testing. Use when analyzing spatial relationships between cell types, testing for...
XCMS3 workflow for LC-MS/MS metabolomics preprocessing. Covers peak detection, retention time alignment, correspondence (grouping), and gap filling. Use when processing raw LC-MS data into a feature table for u...
Detect chromatin loops and point interactions from Hi-C data using cooltools, chromosight, and HiCCUPS-like methods. Identify CTCF-mediated loops and enhancer-promoter contacts.
RNA-seq specific quality control including rRNA contamination detection, strandedness verification, gene body coverage, and transcript integrity metrics. Use to validate RNA-seq libraries before differential ex...
End-to-end flow cytometry workflow from FCS files to differential analysis. Orchestrates compensation, transformation, gating/clustering, and statistical testing with CATALYST/diffcyt.
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.