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Scientific computing and academic tools.

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bioinformatics
471

bio-causal-genomics-fine-mapping

Identify likely causal variants within GWAS loci using SuSiE for sum of single effects regression and FINEMAP for shotgun stochastic search. Computes posterior inclusion probabilities and credible sets to prioritize variants for functional follow-up. Use when narrowing GWAS association signals to candidate causal variants or building credible sets for functional validation.

GPTomics
GPTomics
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bioinformatics
471

bio-clip-seq-clip-alignment

Align CLIP-seq reads to the genome with crosslink site awareness. Use when mapping preprocessed CLIP reads for peak calling.

GPTomics
GPTomics
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scientific-computing
471

bio-local-blast

Run local BLAST searches using BLAST+ command-line tools. Use when running fast unlimited searches, building custom databases, performing large-scale analysis, or when NCBI servers are slow or unavailable.

GPTomics
GPTomics
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scientific-computing
471

bio-methylation-methylkit

DNA methylation analysis with methylKit in R. Import Bismark coverage files, filter by coverage, normalize samples, and perform statistical comparisons. Use when analyzing single-base methylation patterns, comparing samples, or preparing data for DMR detection.

GPTomics
GPTomics
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scientific-computing
471

bio-atac-seq-differential-accessibility

Find differentially accessible chromatin regions between conditions using DiffBind or DESeq2. Use when comparing chromatin accessibility between treatment groups, cell types, or developmental stages in ATAC-seq experiments.

GPTomics
GPTomics
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bioinformatics
471

bio-atac-seq-footprinting

Detect transcription factor binding sites through footprinting analysis in ATAC-seq data using TOBIAS. Use when identifying TF occupancy patterns within accessible regions, as TF binding protects DNA from Tn5 cutting.

GPTomics
GPTomics
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bioinformatics
471

bio-atac-seq-motif-deviation

Analyze transcription factor motif accessibility variability using chromVAR. Use when identifying which TF motifs show variable accessibility across samples or conditions in ATAC-seq data.

GPTomics
GPTomics
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bioinformatics
471

bio-atac-seq-atac-qc

Quality control metrics for ATAC-seq data including fragment size distribution, TSS enrichment, FRiP, and library complexity. Use when assessing ATAC-seq library quality before or after peak calling to identify problematic samples.

GPTomics
GPTomics
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bioinformatics
471

bio-atac-seq-nucleosome-positioning

Extract nucleosome positions from ATAC-seq data using NucleoATAC, ATACseqQC, and fragment analysis. Use when analyzing chromatin organization, identifying nucleosome-free regions at promoters, or characterizing nucleosome occupancy patterns from ATAC-seq fragment size distributions.

GPTomics
GPTomics
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bioinformatics
471

bio-causal-genomics-mediation-analysis

Decompose genetic effects into direct and indirect paths through mediating variables using the mediation R package. Tests whether gene expression, methylation, or other molecular phenotypes mediate the effect of genetic variants on disease. Use when testing whether a molecular phenotype mediates the genotype-to-phenotype relationship.

GPTomics
GPTomics
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bioinformatics
471

bio-splicing-qc

Assesses RNA-seq data quality for splicing analysis including junction saturation curves, splice site strength scoring, and junction coverage metrics using RSeQC. Use when evaluating data suitability for splicing analysis or troubleshooting low event detection.

GPTomics
GPTomics
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bioinformatics
471

bio-splicing-quantification

Quantifies alternative splicing events (PSI/percent spliced in) from RNA-seq using SUPPA2 from transcript TPM or rMATS-turbo from BAM files. Calculates inclusion levels for skipped exons, alternative splice sites, mutually exclusive exons, and retained introns. Use when measuring splice site usage or isoform ratios from RNA-seq data.

GPTomics
GPTomics
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bioinformatics
471

bio-atac-seq-atac-peak-calling

Call accessible chromatin regions from ATAC-seq data using MACS3 with ATAC-specific parameters. Use when identifying open chromatin regions from aligned ATAC-seq BAM files, different from ChIP-seq peak calling.

GPTomics
GPTomics
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bioinformatics
471

bio-alignment-validation

Validate alignment quality with insert size distribution, proper pairing rates, GC bias, strand balance, and other post-alignment metrics. Use when verifying alignment data quality before variant calling or quantification.

GPTomics
GPTomics
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scientific-computing
471

bio-clinical-databases-gnomad-frequencies

Query gnomAD for population allele frequencies to assess variant rarity. Use when filtering variants by population frequency for rare disease analysis or determining if a variant is common in the general population.

GPTomics
GPTomics
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bioinformatics
471

bio-geo-data

Query NCBI Gene Expression Omnibus (GEO) for expression datasets using Biopython Bio.Entrez. Use when finding microarray/RNA-seq datasets, downloading expression data, or linking GEO series to SRA runs.

GPTomics
GPTomics
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bioinformatics
471

bio-microbiome-amplicon-processing

Amplicon sequence variant (ASV) inference from 16S rRNA or ITS amplicon sequencing using DADA2. Covers quality filtering, error learning, denoising, and chimera removal. Use when processing demultiplexed amplicon FASTQ files to generate an ASV table for downstream analysis.

GPTomics
GPTomics
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computational-chemistry
471

bio-alignment-pairwise

Perform pairwise sequence alignment using Biopython Bio.Align.PairwiseAligner. Use when comparing two sequences, finding optimal alignments, scoring similarity, and identifying local or global matches between DNA, RNA, or protein sequences.

GPTomics
GPTomics
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bioinformatics
471

bio-differential-splicing

Detects differential alternative splicing between conditions using rMATS-turbo (BAM-based) or SUPPA2 diffSplice (TPM-based). Reports events with FDR-corrected significance and delta PSI effect sizes. Use when comparing splicing patterns between treatment groups, tissues, or disease states.

GPTomics
GPTomics
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scientific-computing
471

bio-isoform-switching

Analyzes isoform switching events and functional consequences using IsoformSwitchAnalyzeR. Predicts protein domain changes, NMD sensitivity, ORF alterations, and coding potential shifts between conditions. Use when investigating how splicing changes affect protein function.

GPTomics
GPTomics
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bioinformatics
471

bio-alignment-multiple

Perform multiple sequence alignment using MAFFT, MUSCLE5, ClustalOmega, or T-Coffee. Guides tool and algorithm selection based on dataset size, sequence divergence, and downstream application. Use when aligning three or more homologous sequences for phylogenetics, conservation analysis, or evolutionary studies.

GPTomics
GPTomics
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scientific-computing
471

bio-batch-downloads

Download large datasets from NCBI efficiently using history server, batching, and rate limiting. Use when performing bulk sequence downloads, handling large query results, or production-scale data retrieval.

GPTomics
GPTomics
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bioinformatics
471

bio-methylation-based-detection

Analyzes cfDNA methylation patterns for cancer detection using cfMeDIP-seq or bisulfite sequencing with MethylDackel. Identifies cancer-specific methylation signatures and performs tissue-of-origin deconvolution. Use when using methylation biomarkers for early cancer detection or minimal residual disease.

GPTomics
GPTomics
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bioinformatics
471

bio-long-read-sequencing-clair3-variants

Deep learning-based variant calling from long reads using Clair3 for SNPs and small indels. Use when calling germline variants from ONT or PacBio alignments, particularly when high accuracy is needed for clinical or research applications.

GPTomics
GPTomics
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