By GPTomics

Runs all-in-one FASTQ preprocessing with fastp in a single pass - adapter trimming via paired-end overlap analysis, quality/length filtering, 2-color poly-G removal, base correction, optional…

GPTomics/bioSkills

Filters reads by quality, length, N content, and complexity with Trimmomatic, fastp, and Cutadapt, including sliding-window trimming, per-read unqualified-base filtering, and 2-color poly-G removal.

GPTomics/bioSkills

Generates and interprets per-file and cross-sample QC reports from FASTQ data with FastQC, falco, and MultiQC, covering Phred quality, per-base composition, GC, duplication, overrepresented…

GPTomics/bioSkills

Runs RNA-seq-specific post-alignment QC - strandedness inference, gene-body 5'-3' coverage, read distribution (exonic/intronic/intergenic), rRNA/globin/mitochondrial rate, transcript integrity…

GPTomics/bioSkills

Extracts UMIs and collapses reads to original molecules with umitools (directional dedup) or builds error-corrected single-strand/duplex consensus reads with fgbio.

GPTomics/bioSkills

Read biological sequence files (FASTA, FASTQ, GenBank, EMBL, ABI, SFF) with Biopython Bio.SeqIO, choosing between streaming, in-memory, and on-disk-indexed access.

GPTomics/bioSkills

Aggregates per-tool QC metrics (FastQC, fastp, alignment, quantification, variant calling, single-cell) into one interactive MultiQC report, and guides module scoping, sample-name resolution…

GPTomics/bioSkills

Exports publication-ready figures with the correct vector/raster split, embedded editable fonts, color-space-robust palettes, and journal-correct sizing and resolution in matplotlib and ggplot2.

GPTomics/bioSkills

Runs parameterized Jupyter notebooks as reproducible batch report generators with papermill, renders them to HTML/PDF with nbconvert, aggregates results across samples, and makes notebook outputs…

GPTomics/bioSkills

Builds reproducible Quarto reports, presentations, and websites across R, Python, and Julia, with correct engine selection, cache-vs-freeze semantics, native cross-references, parameters, and…

GPTomics/bioSkills

Creates reproducible R Markdown analysis reports (HTML, PDF, Word) with knitr, covering the render pipeline, the interactive-vs-knit session trap, cache invalidation, bookdown cross-references…

GPTomics/bioSkills

Select restriction enzymes for cloning or diagnostics using Biopython Bio.Restriction.

GPTomics/bioSkills

Predict restriction digest fragment sizes and gel patterns using Biopython Bio.Restriction.

GPTomics/bioSkills

Design and validate Type IIS scarless DNA assembly (Golden Gate, MoClo) using Biopython Bio.Restriction.

GPTomics/bioSkills

Build restriction maps showing enzyme cut positions and inter-site distances along DNA using Biopython Bio.Restriction.

GPTomics/bioSkills

Find restriction enzyme cut sites in DNA sequences using Biopython Bio.Restriction.

GPTomics/bioSkills

Performs retrosynthetic planning using AiZynthFinder (template-based MCTS), maintained or version-pinned template-free models, ASKCOS, and emerging RetroSynFormer with explicit handling of route…

GPTomics/bioSkills

Generate reverse complements and complements of DNA/RNA sequences using Biopython, including IUPAC ambiguity codes, gapped alignments, and minus-strand features.

GPTomics/bioSkills

Map translation initiation sites, including non-AUG and alternative starts, from initiation-drug ribosome profiling (TI-seq).

GPTomics/bioSkills

Detect and quantify translated ORFs from Ribo-seq using 3-nucleotide periodicity, including uORFs, internal ORFs, dORFs, and novel ORFs.

GPTomics/bioSkills

Preprocess ribosome profiling reads with UMI handling, adapter trimming, contaminant/rRNA depletion, and footprint-aware alignment.

GPTomics/bioSkills

Validate Ribo-seq library quality by measuring 3-nucleotide periodicity and calibrating read-length-specific P-site offsets.

GPTomics/bioSkills

Detect ribosome pausing and stalling at codon resolution from Ribo-seq, using local-relative occupancy metrics and A-site assignment.

GPTomics/bioSkills

Quantify translation efficiency (TE) as ribosome occupancy relative to mRNA abundance and test for differential TE between conditions.

GPTomics/bioSkills

Quantify transcript expression from FASTQ with Salmon (selective alignment) or kallisto (pseudoalignment), bypassing genome mapping.

GPTomics/bioSkills

Quality control and exploration of RNA-seq count matrices before differential expression.

GPTomics/bioSkills

Count reads per gene from aligned BAM files using Subread featureCounts.

GPTomics/bioSkills

Import transcript-level quantifications from Salmon/kallisto/RSEM into R for gene-level analysis with DESeq2/edgeR using tximport or tximeta.

GPTomics/bioSkills

Tests whether a proposed or predicted RNA secondary structure is supported by evolutionary covariation using R-scape, which scores compensatory substitutions against a phylogeny-aware null and…

GPTomics/bioSkills

Searches for non-coding RNA homologs and classifies RNA families with Infernal covariance models against Rfam, scoring sequence AND secondary-structure conservation jointly.

GPTomics/bioSkills

Processes experimental RNA structure probing data (SHAPE-MaP, DMS-MaPseq) into per-nucleotide reactivity profiles with ShapeMapper2, then uses them as soft restraints on thermodynamic folding.

GPTomics/bioSkills

Create and manipulate Seq, MutableSeq, and SeqRecord objects using Biopython.

GPTomics/bioSkills

Calculate nucleotide and protein sequence properties (GC content, GC skew, molecular weight, melting temperature, isoelectric point, instability, hydropathy) with Biopython.

GPTomics/bioSkills

Slice, extract, and concatenate biological sequences and annotated records using Biopython.

GPTomics/bioSkills

Calculate assembly and sequence statistics (N50/L50, auN, NG50/NGA50, length distribution, GC content with ambiguity handling, summary reports) using Biopython.

GPTomics/bioSkills

Performs molecular similarity searching using Tanimoto, Tversky, Dice, and cosine coefficients on bit/count fingerprints with explicit choice rules for symmetric vs asymmetric measures…

GPTomics/bioSkills

Integrate multiple scRNA-seq samples or batches with Harmony, scVI/scANVI, Seurat (CCA/RPCA), fastMNN, Scanorama, or BBKNN.

GPTomics/bioSkills

Automated reference-based cell type annotation for single-cell RNA-seq using CellTypist, SingleR, Azimuth, scANVI, and scmap to transfer labels from a reference.

GPTomics/bioSkills

Infers ligand-receptor cell-cell communication from scRNA-seq with a consensus-first workflow (LIANA), plus CellPhoneDB specificity tests, CellChat pathway probabilities, and NicheNet downstream…

GPTomics/bioSkills

Dimensionality reduction and graph-based clustering for single-cell RNA-seq with Scanpy (Python) and Seurat (R).

GPTomics/bioSkills

Infer large-scale copy-number alterations from tumor single-cell or single-nucleus RNA-seq to separate malignant from normal cells and call subclones, using inferCNV, copyKAT, Numbat, and SCEVAN.

GPTomics/bioSkills

Read, write, create, and convert single-cell objects across AnnData (Python), Seurat (R), and SingleCellExperiment (R).

GPTomics/bioSkills

Test whether cell-type proportions or composition changed between conditions in single-cell data using Milo (miloR), scCODA, sccomp, and propeller.

GPTomics/bioSkills

Detect and remove doublets (two or more cells in one droplet) from single-cell RNA-seq using scDblFinder (R), Scrublet (Python), and DoubletFinder (R).

GPTomics/bioSkills

Assign cells to their sample of origin from cell or nucleus hashing (CITE-seq HTOs, MULTI-seq lipid/cholesterol tags, CellPlex CMOs) and call cross-sample doublets using Seurat…

GPTomics/bioSkills

Reconstructs single-cell lineage trees and clonal relationships from CRISPR/Cas9 scars, static expressed barcodes (LARRY/CellTag), or somatic mtDNA mutations using Cassiopeia, Startle, and CoSpar.

GPTomics/bioSkills

Detect cluster marker genes and assign manual cell type labels in single-cell RNA-seq using Scanpy (Python) and Seurat (R).

GPTomics/bioSkills

Infers metabolite-mediated cell-cell communication from scRNA-seq by scoring enzyme-to-sensor pairs (MEBOCOST), with metabolic flux (scFEA), FBA state (Compass), and neurotransmitter (NeuronChat)…

GPTomics/bioSkills