Best bioinformatics skills, page 13

Draw and export phylogenetic trees with Bio.Phylo plus matplotlib, and route rich figures to ggtree, ETE4, or iTOL.

GPTomics/bioSkills

Single-variant common-variant GWAS with plink2 --glm (linear/logistic, Firth) and the linear mixed models GEMMA, BOLT-LMM, SAIGE, regenie (SPA).

GPTomics/bioSkills

Computes linkage disequilibrium (r2, D', composite Rogers-Huff r2), prunes correlated variants, clumps GWAS summary statistics to lead SNPs, and defines haplotype blocks with PLINK 1.9/2.0 and…

GPTomics/bioSkills

Manages PLINK genotype filesets - format conversion (VCF, BED/BIM/FAM, PED/MAP, pgen/pvar/psam) and sample/variant QC (missingness, MAF, HWE, sex check, heterozygosity, KING relatedness) with PLINK…

GPTomics/bioSkills

Gene and region-based rare-variant aggregation - burden/collapsing, SKAT, SKAT-O, ACAT-V/ACAT-O, annotation-weighted STAAR - with regenie (--vc-tests), SAIGE-GENE+, and the SKAT R package.

GPTomics/bioSkills

In-memory Python population genetics with scikit-allel - GenotypeArray/HaplotypeArray/AlleleCountsArray, diversity (pi, theta, Tajima's D), SFS, FST (Weir-Cockerham, Hudson, Patterson), f3/D…

GPTomics/bioSkills

Checks whether a PCR primer PAIR amplifies only the intended target genome-wide, using pair-aware in-silico PCR (MFEprimer-3.0, UCSC isPcr, NCBI Primer-BLAST) plus a primer3-py 3'-end-stability…

GPTomics/bioSkills

Validates chosen PCR/qPCR oligos for intramolecular thermodynamic liabilities with primer3-py - hairpins, self-dimers, cross-dimers (calchairpin/homodimer/heterodimer), and 3'-end stability…

GPTomics/bioSkills

Co-designs qPCR/RT-qPCR primers and hydrolysis (TaqMan) or molecular-beacon probes with primer3-py (PRIMERPICKINTERNALOLIGO, PRIMERINTERNAL tags), for assays whose deliverable is a quantitative…

GPTomics/bioSkills

Loads mass-spectrometry data into Python/R and strips the search engine's bookkeeping before any number is trusted -- removes decoys (REV/Reverse), contaminants (CON/Potential contaminant)…

GPTomics/bioSkills

Groups proteins from peptide identifications and controls protein-level FDR, framing inference as a chosen explanation (parsimony or a probability model) of underdetermined peptide evidence rather…

GPTomics/bioSkills

Builds and manages DIA spectral libraries as peptide query parameters (precursor m/z, a few fragment m/z plus relative intensities, normalized RT, optional CCS), covering experimental DDA…

GPTomics/bioSkills

Aligns DNA short reads to a reference with Bowtie2, choosing end-to-end (whole read must align) vs local (soft-clip read ends) mode and a sensitivity preset; the de-facto aligner for ChIP-seq…

GPTomics/bioSkills

Aligns DNA short reads (paired- or single-end) to a reference genome with bwa-mem2, the maintained successor to BWA-MEM, for WGS/WES and germline/somatic variant-calling pipelines; covers index…

GPTomics/bioSkills

Aligns RNA-seq reads to a genome with HISAT2, the splice-aware aligner whose hierarchical graph FM-index runs at roughly a quarter of STAR's memory (~7 GB for human), whose SNP/haplotype graph index…

GPTomics/bioSkills

Aligns RNA-seq reads to a genome with STAR, the fast splice-aware aligner whose splice-junction database (built from a GTF at sjdbOverhang = readlength-1) and two-pass mode set junction sensitivity…

GPTomics/bioSkills

Detects contamination in sequencing reads - cross-species (FastQ Screen, Kraken2), vector/PhiX/adapter, rRNA, and same-species cross-sample/index-hopping and sample swaps (SNP fingerprints via…

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

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

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

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

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

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

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