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Skills في هذا المستودع
جمع SkillsMP عدد ٤٩٦ من skills من zja2004/BGI-CLI. افتح أي skill لمراجعة مصدره وتفاصيله.
zja2004/BGI-CLIعرض ٤٠ من أصل ٤٩٦ skills مجمعة.
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 neighborhood enrichment, or identifying…
لغة النص الأصلي: الإنجليزية
Predict B-cell and T-cell epitopes using BepiPred, IEDB tools, and structure-based methods for vaccine and antibody design. Identify immunogenic regions in antigens. Use when designing vaccines, mapping antibody binding sites, or predicting immunogenic…
لغة النص الأصلي: الإنجليزية
Score and prioritize neoantigens and epitopes for immunogenicity using multi-factor models combining MHC binding, processing, expression, and sequence features. Rank candidates for vaccine design. Use when prioritizing epitopes for vaccine development or…
لغة النص الأصلي: الإنجليزية
Predict peptide-MHC class I and II binding affinity using MHCflurry and NetMHCpan neural network models. Identify potential T-cell epitopes from protein sequences. Use when predicting MHC binding for vaccine design or neoantigen identification.
لغة النص الأصلي: الإنجليزية
Identify tumor neoantigens from somatic mutations using pVACtools for personalized cancer immunotherapy. Predict mutant peptides that bind patient HLA and may elicit T-cell responses. Use when identifying vaccine targets or checkpoint inhibitor response…
لغة النص الأصلي: الإنجليزية
Predict TCR-epitope specificity using ERGO-II and deep learning models for T-cell receptor antigen recognition. Match TCRs to their cognate epitopes or predict TCR targets. Use when analyzing TCR repertoire specificity or identifying antigen-reactive T-cells.
لغة النص الأصلي: الإنجليزية
Analyzes isoform switching events and functional consequences using IsoformSwitchAnalyzeR. Predicts protein domain changes, NMD sensitivity, ORF alterations, and coding potential shifts between conditions. Use when investigating how splicing changes affect…
لغة النص الأصلي: الإنجليزية
Deep learning-based variant calling from long reads using Clair3 for SNPs and small indels. Use when calling germline variants from ONT or PacBio alignments, particularly when high accuracy is needed for clinical or research applications.
لغة النص الأصلي: الإنجليزية
Analyze PacBio Iso-Seq data for full-length isoform discovery and quantification. Use when characterizing transcript diversity or identifying novel splice variants.
لغة النص الأصلي: الإنجليزية
Calls DNA methylation from Oxford Nanopore sequencing data using signal-level analysis. Use when detecting 5mC or 6mA modifications directly from nanopore reads without bisulfite conversion.
لغة النص الأصلي: الإنجليزية
Tracks ctDNA dynamics over time for treatment response monitoring using serial liquid biopsy samples. Analyzes tumor fraction trends, mutation clearance kinetics, and defines molecular response criteria. Use when monitoring patients during therapy or…
لغة النص الأصلي: الإنجليزية
Align long reads using minimap2 for Oxford Nanopore and PacBio data. Supports various presets for different read types and applications. Use when aligning ONT or PacBio reads to a reference genome for variant calling, SV detection, or coverage analysis.
لغة النص الأصلي: الإنجليزية
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 data without short-read polishing.
لغة النص الأصلي: الإنجليزية
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 run quality or filtering reads before assembly…
لغة النص الأصلي: الإنجليزية
Detect structural variants from long-read alignments using Sniffles, cuteSV, and SVIM. Use when detecting deletions, insertions, inversions, translocations, or complex rearrangements from ONT or PacBio data, especially those missed by short-read methods.
لغة النص الأصلي: الإنجليزية
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 classes, chain composition, or lipid-specific pathways.
لغة النص الأصلي: الإنجليزية
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 untargeted metabolomics.
لغة النص الأصلي: الإنجليزية
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 or when preferring GUI-based preprocessing.
لغة النص الأصلي: الإنجليزية
Quality control and normalization for metabolomics data. Covers QC-based correction, batch effect removal, and data transformation methods. Use when correcting technical variation in metabolomics data before statistical analysis.
لغة النص الأصلي: الإنجليزية
Map metabolites to biological pathways using KEGG, Reactome, and MetaboAnalyst. Perform pathway enrichment and topology analysis. Use when interpreting metabolomics results in the context of biochemical pathways.
لغة النص الأصلي: الإنجليزية
Statistical analysis for metabolomics data. Covers univariate testing, multivariate methods (PCA, PLS-DA), and biomarker discovery. Use when identifying differentially abundant metabolites or building classification models.
لغة النص الأصلي: الإنجليزية
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 and internal standards.
لغة النص الأصلي: الإنجليزية
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 untargeted metabolomics.
لغة النص الأصلي: الإنجليزية
Species abundance estimation using Bracken with Kraken2 output. Redistributes reads from higher taxonomic levels to species for more accurate estimates. Use when accurate species-level abundances are needed from Kraken2 classification output.
لغة النص الأصلي: الإنجليزية
Detect antimicrobial resistance genes using AMRFinderPlus, ResFinder, and CARD. Screen isolates and metagenomes for resistance determinants. Use when characterizing resistance profiles in clinical isolates, surveillance samples, or metagenomic data.
لغة النص الأصلي: الإنجليزية
Profile functional potential of metagenomes using HUMAnN3 and similar tools. Use when obtaining pathway abundances, gene family counts, or functional annotations from metagenomic data.
لغة النص الأصلي: الإنجليزية
Taxonomic classification of metagenomic reads using Kraken2. Fast k-mer based classification against RefSeq database. Use when performing initial taxonomic classification of shotgun metagenomic reads before abundance estimation with Bracken.
لغة النص الأصلي: الإنجليزية
Marker gene-based taxonomic profiling using MetaPhlAn 4. Provides accurate species-level relative abundances using clade-specific markers. Use when accurate taxonomic profiling is needed and computational resources are limited, or for comparison with…
لغة النص الأصلي: الإنجليزية
Track bacterial strains using MASH, sourmash, fastANI, and inStrain. Compare genomes, detect contamination, and monitor strain-level variation. Use when needing sub-species resolution for outbreak tracking, transmission analysis, or within-host strain…
لغة النص الأصلي: الإنجليزية
Visualize metagenomic profiles using R (phyloseq, microbiome) and Python (matplotlib, seaborn). Create stacked bar plots, heatmaps, PCA plots, and diversity analyses. Use when creating publication-quality figures from MetaPhlAn, Bracken, or other taxonomic…
لغة النص الأصلي: الإنجليزية
Analyzes cfDNA methylation patterns for cancer detection using cfMeDIP-seq or bisulfite sequencing with MethylDackel. Identifies cancer-specific methylation signatures and performs tissue-of-origin deconvolution. Use when using methylation biomarkers for…
لغة النص الأصلي: الإنجليزية
Bisulfite sequencing read alignment using Bismark with bowtie2/hisat2. Handles genome preparation and produces BAM files with methylation information. Use when aligning WGBS, RRBS, or other bisulfite-converted sequencing reads to a reference genome.
لغة النص الأصلي: الإنجليزية
Extract methylation calls from Bismark BAM files using bismark_methylation_extractor. Generates per-cytosine reports for CpG, CHG, and CHH contexts. Use when extracting methylation levels from aligned bisulfite sequencing data for downstream analysis.
لغة النص الأصلي: الإنجليزية
Differentially methylated region (DMR) detection using methylKit tiles, bsseq BSmooth, and DMRcate. Use when identifying contiguous genomic regions with methylation differences between experimental conditions or cell types.
لغة النص الأصلي: الإنجليزية
DNA methylation analysis with methylKit in R. Import Bismark coverage files, filter by coverage, normalize samples, and perform statistical comparisons. Use when analyzing single-base methylation patterns, comparing samples, or preparing data for DMR…
لغة النص الأصلي: الإنجليزية
Amplicon sequence variant (ASV) inference from 16S rRNA or ITS amplicon sequencing using DADA2. Covers quality filtering, error learning, denoising, and chimera removal. Use when processing demultiplexed amplicon FASTQ files to generate an ASV table for…
لغة النص الأصلي: الإنجليزية
Differential abundance testing for microbiome data using compositionally-aware methods like ALDEx2, ANCOM-BC2, and MaAsLin2. Use when identifying taxa that differ between experimental groups while accounting for the compositional nature of microbiome data.
لغة النص الأصلي: الإنجليزية
Alpha and beta diversity analysis for microbiome data. Calculate within-sample richness, evenness, and between-sample dissimilarity with phyloseq and vegan. Use when comparing community composition across samples or testing for group differences in microbiome…
لغة النص الأصلي: الإنجليزية
Predict metagenome functional content from 16S rRNA marker gene data using PICRUSt2. Infer KEGG, MetaCyc, and EC abundances from ASV tables. Use when functional profiling is needed from 16S data without shotgun metagenomics sequencing.
لغة النص الأصلي: الإنجليزية
QIIME2 command-line workflow for 16S/ITS amplicon analysis. Alternative to DADA2/phyloseq R workflow with built-in provenance tracking. Use when preferring CLI over R, needing reproducible provenance, or working within QIIME2 ecosystem.
لغة النص الأصلي: الإنجليزية