Research & Science · By GPTomics

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

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

Plot per-gene mutation distributions on a protein-domain map (lollipop / needle plots) showing mutation position, recurrence count, and variant classification with maftools, g3-lollipop…

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

Build local BLAST databases and run searches using NCBI BLAST+ command-line tools.

GPTomics/bioSkills

Performs ML-based protein-ligand pose prediction and scoring using DiffDock-L (diffusion-based), Boltz-1 / Boltz-2 (foundation model with affinity), Chai-1, AlphaFold3 ligand, EquiBind, TANKBind…

GPTomics/bioSkills

Calculates molecular fingerprints (ECFP/Morgan, FCFP, MACCS, RDKit, AtomPair, TopologicalTorsion, Avalon, MAP4, MHFP6) and physicochemical descriptors (Lipinski, QED, TPSA, Crippen LogP, 3D shape)…

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

Enumerates virtual chemical libraries via reaction SMARTS transformations using RDKit and reaction templates, with explicit handling of atom mapping, RDChiral template extraction, product…

GPTomics/bioSkills

Generate consensus sequences and manage reference files using samtools.

GPTomics/bioSkills

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

GPTomics/bioSkills

View, convert, and understand SAM/BAM/CRAM alignment files using samtools and pysam.

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

Performs 3D shape-based similarity searching using ROCS (OpenEye), USRCAT (ultra-fast), Open3DAlign (RDKit), ESPSim (electrostatic), and ShaEP with explicit handling of Tanimoto-Combo (shape +…

GPTomics/bioSkills

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

GPTomics/bioSkills

Searches molecular libraries for substructure matches using SMARTS patterns with explicit handling of recursive SMARTS, ring membership, aromaticity dialect, vector binding, atom map indices, and…

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

Perform multiple sequence alignment using MAFFT, MUSCLE5, ClustalOmega, or T-Coffee.

GPTomics/bioSkills

Align protein structures using Foldseek 3Di, TM-align, US-align, DALI, or Foldmason for structural MSA.

GPTomics/bioSkills

Trim multiple sequence alignments using ClipKIT, trimAl, BMGE, Divvier, or HMMcleaner with mode selection guidance per downstream goal.

GPTomics/bioSkills

Call accessible chromatin regions from ATAC-seq BAM files using MACS3, MACS2, Genrich, or HMMRATAC.

GPTomics/bioSkills

Identify differentially accessible chromatin regions across conditions using DiffBind, csaw, DESeq2, or edgeR.

GPTomics/bioSkills

Analyze TF motif accessibility variability across samples or single cells using chromVAR.

GPTomics/bioSkills

Process and analyze single-cell ATAC-seq data with Signac, ArchR, SnapATAC2, or Cell Ranger ATAC.

GPTomics/bioSkills

Test whether two or more traits share a causal variant at a locus using Bayesian colocalization (coloc.abf, coloc.susie, HyPrColoc, moloc, eCAVIAR, SMR/HEIDI, PWCoCo, SharePro).

GPTomics/bioSkills

Maps GWAS-implicated loci to candidate effector (causal) genes by integrating variant-to-gene (V2G) features via Open Targets L2G (Mountjoy 2021), MAGMA gene-based association (de Leeuw 2015), FUMA…

GPTomics/bioSkills

Resolves GWAS associations to candidate causal variants and credible sets via SuSiE, susierss, FINEMAP, CAVIAR, DAP-G, PAINTOR, PolyFun, SuSiEx, MultiSuSiE, and FOCUS.

GPTomics/bioSkills

Estimates bivariate genetic correlation (rg) between traits from GWAS summary statistics or individual-level genotypes using cross-trait LDSC, HDL, LAVA, rho-HESS, GREML-bivariate, Popcorn, and HDL-L.

GPTomics/bioSkills

Fits structural equation models to GWAS summary statistics using GenomicSEM (Grotzinger 2019), including common-factor models, confirmatory factor models, ESEM, common-factor GWAS with QSNP…

GPTomics/bioSkills

Estimates SNP heritability and partitions it across functional annotations, cell types, and loci from GWAS summary statistics or individual-level genotypes.

GPTomics/bioSkills

Decompose total effects into direct and indirect paths through mediators using mediation, CMAverse 4-way, HIMA/HIMA2 high-dimensional, BAMA, two-step / MVMR mediation, or double-ML medDML.

GPTomics/bioSkills

Estimate causal effects of an exposure on an outcome from GWAS summary statistics using genetic instruments.

GPTomics/bioSkills

Detect and adjust for horizontal pleiotropy in two-sample Mendelian randomization by distinguishing uncorrelated (UHP) from correlated (CHP) pleiotropy and choosing among Egger, MR-PRESSO, MR-RAPS…

GPTomics/bioSkills

Runs cis-pQTL Mendelian randomization for drug-target validation using UKB-PPP (Olink), deCODE (SomaScan), Fenland, INTERVAL, ARIC, and FinnGen-PPP proteomes plus colocalization triangulation…

GPTomics/bioSkills

Performs gene-level association from GWAS summary statistics via genetically predicted tissue expression using FUSION, PrediXcan, S-PrediXcan, S-MultiXcan, UTMOST, MOSTWAS, kTWAS, EpiXcan, TIGAR-V2…

GPTomics/bioSkills