Best bioinformatics skills, page 6

Identifies differentially bound ChIP-seq regions between conditions using DiffBind, csaw (sliding windows), DESeq2/edgeR/PyDESeq2 on count matrices, NormR (control-aware), or MAnorm2.

GPTomics/bioSkills

Discovers de novo motifs and tests known motif enrichment in ChIP-seq, ATAC-seq, or other peak sequences using HOMER, MEME-ChIP (STREME, CentriMo, TOMTOM, FIMO), monaLisa, and AME.

GPTomics/bioSkills

Annotates ChIP-seq peaks to genomic features, nearest genes, ENCODE candidate cis-regulatory elements (cCREs), and regulatory domains.

GPTomics/bioSkills

Calls ChIP-seq peaks with MACS3, MACS2, HOMER, or SPP across narrow (TF) and broad (histone) modes.

GPTomics/bioSkills

Assesses ChIP-seq quality across antibody specificity, fragmentation, enrichment, replicate concordance, and library complexity.

GPTomics/bioSkills

Normalizes ChIP-seq data using exogenous spike-in (ChIP-Rx with Drosophila chromatin per Orlando 2014 / Egan 2016; E.

GPTomics/bioSkills

Identifies super-enhancers from H3K27ac, MED1, or BRD4 ChIP-seq using ROSE, ROSE2, LILY, HOMER -style super, and ENCODE dELS cross-referencing.

GPTomics/bioSkills

Visualizes ChIP-seq data using deepTools (computeMatrix, plotHeatmap, plotProfile, bamCoverage, bamCompare), pyGenomeTracks (modern INI-driven track plots), Gviz (R browser-style), EnrichedHeatmap…

GPTomics/bioSkills

Identify direct miRNA-target interactions from AGO HITS-CLIP, AGO-CLEAR-CLIP (chimeric reads), HEAP (Halo-Ago2 mouse), chimeric eCLIP / miR-eCLIP (deep miRNA-target profiling), or CLASH using…

GPTomics/bioSkills

Align preprocessed CLIP-seq reads (eCLIP, iCLIP, iCLIP2, PAR-CLIP) to genome with STAR or bowtie2 using crosslink-preserving parameters, choosing between unique-mapper-only and multi-mapper-aware…

GPTomics/bioSkills

Predict RBP binding from RNA sequence using deep learning models (RBPNet sequence-to-signal, RNAProt RNN, GraphProt2 GCN with structure, DeepCLIP, DeepRiPe multi-modal CNN) for variant-effect…

GPTomics/bioSkills

Preprocess CLIP-seq reads (eCLIP, iCLIP, iCLIP2, iCLIP3, irCLIP, PAR-CLIP, FLASH) with protocol-specific UMI extraction, adapter trimming, length filtering, and post-alignment PCR-duplicate collapse.

GPTomics/bioSkills

Detect single-nucleotide crosslink (CL) sites in CLIP-seq data using truncation patterns (iCLIP/eCLIP CITS), crosslink-induced mutations (HITS-CLIP CIMS deletions, PAR-CLIP T-to-C), or…

GPTomics/bioSkills

Profiles RNA-binding protein targets without antibody or UV crosslinking using STAMP (APOBEC1-RBP fusion, C-to-U editing), scSTAMP (single-cell), TRIBE/HyperTRIBE (ADAR-RBP, A-to-I editing)…

GPTomics/bioSkills

Infer integer allele-specific copy number, tumor purity, and ploidy from tumor sequencing by jointly modeling read depth (logR) and B-allele frequency (BAF) with ASCAT, Sequenza, FACETS, PURPLE, and…

GPTomics/bioSkills

Visualize copy number profiles, segments, allele-specific tracks, and cohort patterns from CNVkit, GATK, ASCAT, FACETS, Sequenza, and other callers.

GPTomics/bioSkills

Detect somatic and germline copy number variants from targeted, exome, and whole-genome sequencing with CNVkit, a read-depth caller that combines on-target and off-target (antitarget) coverage.

GPTomics/bioSkills

Resolve the architecture of focal oncogene amplifications — extrachromosomal DNA (ecDNA), breakage-fusion-bridge (BFB) cycles, homogeneously staining regions (HSR), and linear amplification — from…

GPTomics/bioSkills

Quantify homologous recombination deficiency (HRD) from tumor copy number using the three genomic-scar metrics — loss of heterozygosity (LOH), large-scale state transitions (LST), and telomeric…

GPTomics/bioSkills

Resolve subclonal copy number, whole-genome doubling, and copy-number tumor evolution from bulk sequencing with Battenberg, TITAN, and MEDICC2.

GPTomics/bioSkills

Identifies essential genes from CRISPR-Cas9 fitness screens using BAGEL2 (Kim & Hart 2021 Genome Med), a Bayesian classifier scoring per-gene Bayes Factors via log-likelihood ratios over per-sgRNA…

GPTomics/bioSkills

Batch effect correction for CRISPR screens covering ComBat empirical-Bayes, RUV, SVA, control-sgRNA normalization, and the model-based alternative of including batch as a covariate in MAGeCK MLE or…

GPTomics/bioSkills

Corrects the gene-independent copy-number artifact in CRISPR-Cas9 screens (Aguirre 2016 / Munoz 2016 Cancer Discov) where amplified loci appear essential from DNA-damage burden of simultaneous cuts.

GPTomics/bioSkills

Quantifies CRISPR editing outcomes with CRISPResso2 (Clement 2019 Nat Biotechnol) across Cas9-nuclease (indels, HDR), CBE and ABE base editors (target conversion + bystander), and prime editor…

GPTomics/bioSkills

Cross-method decision tree for calling hits in pooled CRISPR screens.

GPTomics/bioSkills

Designs and analyzes in vivo CRISPR screens in animal tumor models, organoids, and immune-cell adoptive transfers.

GPTomics/bioSkills

Runs JACKS (Joint Analysis of CRISPR/Cas9 Knockout Screens; Allen et al 2019 Genome Research) which models per-sgRNA log-fold-change as the product of a treatment-dependent gene-essentiality term…

GPTomics/bioSkills

Analyzes single-cell pooled CRISPR screens (Perturb-seq, CROP-seq, Perturb-CITE-seq, ECCITE-seq, multiome) where each cell carries an sgRNA and a scRNA-seq / surface-protein / chromatin readout.

GPTomics/bioSkills

Build circular genome visualizations using circlize (R), pyCirclize (Python), or Circos (Perl CLI) with ideogram tracks, multi-data tracks (scatter, histogram, heatmap), chord/link arcs for…

GPTomics/bioSkills

Produce and interpret PCA, t-SNE, UMAP, and PHATE plots for high-dimensional omics data with rigor about which method preserves what (variance, local structure, manifold, transitions)…

GPTomics/bioSkills

Build genome-browser-style multi-track figures with pyGenomeTracks (config-driven), Gviz (R), and IGV batch screenshotting.

GPTomics/bioSkills

Build Manhattan, Miami, QQ, and locuszoom-style regional plots from GWAS, TWAS, PWAS, and QTL summary statistics with correct genomic-inflation diagnostics, multi-trait overlays, lead-SNP labeling…

GPTomics/bioSkills

Mark and remove PCR/optical duplicates using samtools fixmate and markdup.

GPTomics/bioSkills

Query the Ensembl REST API for gene/transcript/protein lookup, sequence retrieval, comparative genomics (Compara), variant effect prediction (VEP), regulatory features, and cross-species…

GPTomics/bioSkills

Retrieve records from NCBI databases using Biopython Bio.Entrez (EFetch, ESummary).

GPTomics/bioSkills

Find cross-database references between NCBI databases using Biopython Bio.Entrez (ELink).

GPTomics/bioSkills

Download genome assemblies, gene records, and ortholog data from NCBI using the modern Datasets v2 CLI (replaces assemblysummary.txt scraping and many EFetch workflows).

GPTomics/bioSkills

Detects aberrant splicing in single rare-disease patients vs a control panel using FRASER 2.0 (Bioconductor; Beta-binomial autoencoder on Intron Jaccard Index, default delta cutoff 0.1, q…

GPTomics/bioSkills

Detect distant homologs using profile and structure-aware methods that go beyond standard BLAST.

GPTomics/bioSkills

Creates sashimi-style plots showing RNA-seq read coverage and splice junction counts using ggsashimi (general-purpose, condition-grouped overlays), rmats2sashimiplot (rMATS-output-aware)…

GPTomics/bioSkills

Download raw sequencing reads from NCBI SRA using sra-tools (prefetch, fasterq-dump, vdb-validate) or the ENA mirror.

GPTomics/bioSkills

End-to-end post-GWAS causal inference pipeline orchestrating heritability partitioning, genetic correlation, Mendelian randomization with CHP-aware sensitivity (CAUSE / LHC-MR), colocalization…

GPTomics/bioSkills

End-to-end CLIP-seq pipeline from FASTQ to ENCODE-compliant binding sites, single-nucleotide crosslink maps, annotation, motifs, and (optionally) differential binding.

GPTomics/bioSkills

Trains and applies base-resolution deep learning models on ChIP-seq / ChIP-nexus / CUT&RUN data.

GPTomics/bioSkills

Query and download from NCBI Gene Expression Omnibus (GEO) and EMBL-EBI's BioStudies/ArrayExpress mirror.

GPTomics/bioSkills

Generate pileup data for variant calling using samtools mpileup and pysam.

GPTomics/bioSkills

Comprehensive CRISPR screen analysis for functional genomics.

wu-yc/LabClaw

Production-ready genomics and epigenomics data processing for BixBench questions.

wu-yc/LabClaw