Results for “dna-sequence-analysis”

26 skills

alterlab-jaspar

Query JASPAR for transcription factor binding site (TFBS) profiles (PWMs/PFMs), searching by TF name, species, or class, scanning DNA sequences for binding sites, and comparing matrices. Use when doing motif analysis, regulatory genomics, transcription factor binding prediction, or interpreting regulatory/non-coding GWAS variants. Part of the AlterLab Academic Skills suite.

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Process and analyze high-throughput sequencing data with deepTools for quality control, normalization, comparison, and publication-quality visualizations of ChIP-seq, RNA-seq, and ATAC-seq experiments.

30.2k · bundle

Use when profiling nucleotide content (AT/GC percentages, base counts) of genomic intervals against a FASTA reference.

advanced-botany-analysis

Advanced Botany Analysis Skill

authoring-analysis

Analyze content sequences from page structure to determine whether each should be default content or a specific block, and validate block selection for AEM Edge Delivery Services imports.

performing-dns-tunneling-detection

Detects DNS tunneling by computing Shannon entropy of DNS query names, analyzing query length distributions, inspecting TXT record payloads, and identifying high subdomain cardinality using scapy for packet capture analysis.

24.6k · bundle

Analyze biological sequences, alignments, phylogenetic trees, and diversity metrics (alpha/beta, UniFrac) with ordination (PCoA) and PERMANOVA for microbiome and community ecology data.

30.2k · bundle

Perform differential gene expression analysis for bulk RNA-seq data using PyDESeq2, supporting formulaic designs, Wald tests, FDR correction, LFC shrinkage, and result visualization.

30.2k · bundle

Use when searching DNA or RNA queries against nucleotide sequence databases with HMMER's nucleotide homology search engine.

Single-cell RNA-seq analysis. Load .h5ad/10X data, QC, normalization, PCA/UMAP/t-SNE, Leiden clustering, marker genes, cell type annotation, trajectory, for scRNA-seq analysis.

Análise de RNA-seq de célula única. Carregue dados .h5ad/10X, QC, normalização, PCA/UMAP/t-SNE, clustering Leiden, genes marcadores, anotação de tipo celular, trajetória, para análise de scRNA-seq.

Differential gene expression analysis (Python DESeq2). Identify DE genes from bulk RNA-seq counts, Wald tests, FDR correction, volcano/MA plots, for RNA-seq analysis.

detecting-dns-exfiltration-with-dns-query-analysis

Detect data exfiltration through DNS tunneling by analyzing query entropy, subdomain length, query volume, TXT record abuse, and response payload sizes using passive DNS monitoring.

24.6k · bundle

Use when aligning RNA-seq reads to a reference genome using graph-based indexing for fast and sensitive spliced alignment.

Use when searching protein query sequences against a translated nucleotide database to identify protein-coding regions or homologs in genomic data.

Analyze any text to extract a cognitive fingerprint across 12 dimensions, revealing reasoning patterns, decision styles, and thinking signatures.

30.2k · bundle

applied-botany-synthesis

Applied Botany Synthesis Skill

Mines git history and codebase to reconstruct the development lifecycle, identify sequential and parallel patterns, and produce actionable recommendations for future iterations.

Use when you need to remove adapter sequences from high-throughput sequencing reads, trim low-quality bases, or filter reads by length. Supports single-end and paired-end FASTQ/FASTA input with error-tolerant adapter matching.

Single-cell RNA-seq analysis. Load .h5ad/10X data, QC, normalization, PCA/UMAP/t-SNE, Leiden clustering, marker genes, cell type annotation, trajectory, for scRNA-seq analysis.

Biological data toolkit. Sequence analysis, alignments, phylogenetic trees, diversity metrics (alpha/beta, UniFrac), ordination (PCoA), PERMANOVA, FASTA/Newick I/O, for microbiome analysis.

botany-debugging-expert

Botany Debugging Expert Skill

metinduraktr-44

Differential gene expression analysis (Python DESeq2). Identify DE genes from bulk RNA-seq counts, Wald tests, FDR correction, volcano/MA plots, for RNA-seq analysis.

metinduraktr-44

Single-cell RNA-seq analysis. Load .h5ad/10X data, QC, normalization, PCA/UMAP/t-SNE, Leiden clustering, marker genes, cell type annotation, trajectory, for scRNA-seq analysis.

Use when aligning RNA-seq reads to a reference genome with junction detection, including exon-exon junctions and gene fusions.

Use when searching nucleotide sequences against a nucleotide database using translated protein comparison. Useful for detecting distant evolutionary relationships between nucleotide sequences.