Research & Science · For researchers

Assembles a genome de novo from Illumina short reads with SPAdes (isolate/careful/sc/meta/plasmid/rna modes), MEGAHIT (low-memory, huge datasets), Unicycler (bacterial finishing/hybrid), MaSuRCA…

GPTomics/bioSkills

Designs cytosine (CBE, C-to-T) and adenine (ABE, A-to-G) base-editor guides by positioning the target base at the activity-peak of the editing window (protospacer positions ~5-7, PAM-distal…

GPTomics/bioSkills

Designs and ranks guide RNAs (sgRNAs) for CRISPR-Cas9/Cas12a gene knockout by scanning a target for PAM sites (NGG SpCas9, NNGRRT SaCas9, TTTV Cas12a, NG SpCas9-NG, near-PAMless SpRY), enumerating…

GPTomics/bioSkills

Designs donor/repair templates for precise CRISPR knock-ins -- choosing the format (ssODN, long-ssDNA/Easi-CRISPR, dsDNA/plasmid, AAV6), sizing homology arms, placing the cut within ~10 bp of the…

GPTomics/bioSkills

Designs pegRNAs and nicking guides for prime editing (PE) -- choosing the nick/strand, tuning the primer-binding site (PBS) and reverse-transcription template (RTT) as a per-locus panel, selecting…

GPTomics/bioSkills

Handles BED-format genomic intervals (BED3 through BED12, narrowPeak/broadPeak) and the coordinate-system substrate the whole interval category rests on, with bedtools (CLI) and…

GPTomics/bioSkills

Generates, normalizes, and converts bedGraph signal tracks (4-column chrom/start/end/value, 0-based half-open) with bedtools genomecov, deepTools bamCoverage/bamCompare/bigwigCompare, bedtools…

GPTomics/bioSkills

Reads, queries, and writes bigWig indexed binary signal tracks (coverage, fold-change, conservation, methylation-rate) with pyBigWig (Python) and the UCSC Kent tools (bedGraphToBigWig…

GPTomics/bioSkills

Computes and interprets sequencing read depth and coverage over a genome, windows, or target regions with mosdepth (windowed depth, cumulative distribution, --quantize callable BEDs), bedtools…

GPTomics/bioSkills

Performs set operations on genomic intervals - intersect (-wa/-wb/-wo/-wao/-loj/-c/-v/-u), subtract (-A), merge (-d, -c/-o), complement, cluster, multiinter, unionbedg, map, and groupby - with…

GPTomics/bioSkills

Performs proximity operations on genomic intervals with bedtools (closest, window, flank, slop) and pybedtools - nearest-feature queries with signed/strand-aware distance, fixed-radius window…

GPTomics/bioSkills

Detects TAD boundaries from balanced Hi-C contact matrices via the diamond-window insulation score (cooltools insulation) and HiCExplorer hicFindTADs, returning a continuous log2 insulation track…

GPTomics/bioSkills

Segment single cells from multiplexed IMC/MIBI tissue images using Mesmer/DeepCell, Cellpose, or ilastik+CellProfiler, covering whole-cell vs nuclear segmentation, the summed-membrane-channel…

GPTomics/bioSkills

Load and preprocess imaging mass cytometry (IMC) and MIBI data from raw MCD/TXT through hot-pixel removal, spillover compensation, and variance-stabilizing transformation, covering readimc/steinbock…

GPTomics/bioSkills

Compare cell-type composition and spatial features across conditions in IMC/MIBI cohorts with the patient as the experimental unit, covering pseudoreplication, per-patient aggregation, mixed models…

GPTomics/bioSkills

Interactive cell annotation and image QC for IMC/MIBI using napari, napari-imc, Mantis Viewer, and cytomapper, covering the pixels-to-cell-table bridge, overlaying masks to catch…

GPTomics/bioSkills

Assign cell types from marker expression in IMC/MIBI data using clustering (PhenoGraph/FlowSOM/Leiden/Pixie), marker-based probabilistic classifiers (Astir), or image-context CNNs (CellSighter)…

GPTomics/bioSkills

Predict B-cell and T-cell epitopes for vaccine antigen design and epitope mapping with BepiPred-3.0, DiscoTope-3.0, the IEDB tools, and EL-mode MHC presentation.

GPTomics/bioSkills

Predict peptide-MHC class I binding and natural presentation with MHCflurry, NetMHCpan-4.1, and MixMHCpred to nominate candidate CD8 T-cell epitopes.

GPTomics/bioSkills

Predict peptide-MHC class II (HLA-DR/DQ/DP) binding and presentation for CD4 T-cell epitopes with NetMHCIIpan-4.3 and MixMHC2pred-2.0.

GPTomics/bioSkills

Identify tumor neoantigens from somatic variants with pVACtools (pVACseq/pVACfuse/pVACbind/pVACvector/pVACview) for personalized cancer vaccines and checkpoint biomarkers.

GPTomics/bioSkills

Infer or annotate TCR antigen specificity by unsupervised clustering (TCRdist/tcrdist3, GLIPH2, clusTCR, GIANA) and database lookup (VDJdb, IEDB, McPAS-TCR), and rank candidates with supervised…

GPTomics/bioSkills

Basecalls raw Oxford Nanopore signal (POD5/FAST5) into reads with Dorado, choosing the chemistry-matched model and accuracy tier (fast/hac/sup), requesting modified bases (5mCG5hmCG, 6mA, m6A) at…

GPTomics/bioSkills

Calls germline small variants (SNPs and indels) from Oxford Nanopore and PacBio HiFi long reads with Clair3, a two-stage (pileup + full-alignment) deep-learning caller, selecting the chemistry- and…

GPTomics/bioSkills

Phases small variants, SVs, and methylation from Oxford Nanopore and PacBio long reads (read-backed/physical phasing) with WhatsHap, LongPhase, or HiPhase, and haplotags the BAM (HP/PS tags) for…

GPTomics/bioSkills

Aligns Oxford Nanopore and PacBio long reads (and assemblies) to a reference with minimap2 using the error-rate-matched preset (map-ont, lr:hq, map-hifi, map-pb, splice/splice:hq, asm5/10/20, ava)…

GPTomics/bioSkills

Assesses Oxford Nanopore and PacBio long-read quality with NanoPlot, cramino, NanoComp, pycoQC/toulligQC, and seqkit, and filters reads with chopper/Filtlong for the downstream goal.

GPTomics/bioSkills

Polishes Oxford Nanopore draft assemblies to higher consensus accuracy with medaka, a basecaller-model-specific neural consensus net, produces haploid variant calls (VCF) for microbial…

GPTomics/bioSkills

Calls DNA base modifications (5mC, 5hmC, 6mA, 4mC) directly from Oxford Nanopore and PacBio HiFi long reads encoded as MM/ML SAM tags, piles them into per-site bedMethyl with modkit (or pb-CpG-tools…

GPTomics/bioSkills

Detects structural variants (deletions, insertions, inversions, duplications, translocations) from Oxford Nanopore and PacBio long-read alignments with Sniffles2, cuteSV, SVIM, and assembly-based…

GPTomics/bioSkills

Designs and analyzes stable-isotope-resolved metabolomics (SIRM / isotope tracing / fluxomics) experiments that measure metabolic ACTIVITY via 13C/15N/2H tracers, distinct from steady-state pool…

GPTomics/bioSkills

Turns shotgun classifier output into a defensible abundance table with Bracken Bayesian re-estimation, then compositional treatment (CLR, zero handling), library-size normalization, reference-frame…

GPTomics/bioSkills

Profiles the antimicrobial-resistance gene content (resistome) of shotgun metagenomes - read-based quantification with RGI bwt, AMR++/MEGARes, ARGs-OAP/SARG, deepARG, or GROOT, and presence calling…

GPTomics/bioSkills

Cleans a shotgun metagenome of everything that is not the target community before profiling - host-read depletion (Hostile, bowtie2/T2T-CHM13), reagent/kitome contamination control with blanks and…

GPTomics/bioSkills

Profiles the functional potential of shotgun metagenomes with HUMAnN 3's tiered search (MetaPhlAn prescreen, Bowtie2 pangenome, translated DIAMOND vs UniRef), giving gene-family (RPK) and MetaCyc…

GPTomics/bioSkills

Classifies shotgun metagenomic reads to taxa with Kraken2's minimizer/LCA matching against a chosen reference database, then hands off to Bracken for abundance re-estimation.

GPTomics/bioSkills

Profiles shotgun metagenomes to species/SGB relative abundance with MetaPhlAn 4's clade-specific marker genes (bowtie2 short reads, minimap2 long reads).

GPTomics/bioSkills

Resolves and compares bacterial strains below the species level from shotgun metagenomes with inStrain (popANI/conANI microdiversity), StrainPhlAn (marker-SNV consensus phylogeny and nGD), MIDAS2…

GPTomics/bioSkills

Turns raw Illumina Infinium methylation BeadChip IDATs (450K, EPIC, EPICv2) into a defensible beta/M matrix with sesame (openSesame/SigDF) or minfi (RGChannelSet - MethylSet - GenomicRatioSet).

GPTomics/bioSkills

Performs probe filtering and sample-level QC on Illumina Infinium methylation arrays (450K / EPIC / EPICv2) to decide which probes and samples to trust.

GPTomics/bioSkills

Aligns bisulfite-converted (WGBS, RRBS, PBAT) and enzymatic (EM-seq) short reads to an in-silico C-T/G-A-converted reference with Bismark (Bowtie2 or HISAT2), preparing the genome index, choosing…

GPTomics/bioSkills

Reads, writes, and converts molecular file formats (SMILES, InChI, SDF V2000/V3000, MOL2, PDB, and BinaryCIF) using RDKit and Open Babel with rigorous handling of aromaticity perception…

GPTomics/bioSkills

Standardizes molecular structures using the ChEMBL structure pipeline for normalization and parent selection plus RDKit rdMolStandardize for explicit custom steps such as tautomer canonicalization…

GPTomics/bioSkills

Discovers shared and view-specific latent factors across bulk multi-omics blocks (RNA-seq, proteomics, methylation) on a common sample axis with MOFA2's unsupervised Bayesian group factor model…

GPTomics/bioSkills

Stratifies patients into multi-omics subtypes by building one patient-by-patient similarity network per omic, fusing them with SNF's cross-network diffusion, and spectral-clustering the fused graph…

GPTomics/bioSkills

Handle paired-end FASTQ files (R1/R2) using Biopython while keeping mates synchronized.

GPTomics/bioSkills

Runs Gene Ontology over-representation analysis (ORA) on a gene LIST with clusterProfiler enrichGO, the one-sided hypergeometric/Fisher 2x2 test phyper(k-1, M, N-M, n, lower.tail=FALSE).

GPTomics/bioSkills

Tests a gene list or ranked gene vector for over-representation or coordinated shifts in Reactome's curated, peer-reviewed, reaction-level pathways using ReactomePA's enrichPathway (ORA) and…

GPTomics/bioSkills