Results for “dna-sequence-analysis”
12 skillsMore results
rnaseq-de
Performs differential expression analysis on bulk RNA-seq or pseudo-bulk count matrices with QC, PCA, and contrast testing.
17 · bundle
rna
Annotates single-cell RNA-seq data by scoring marker genes, transferring labels with CellTypist, or reasoning over marker lists with an LLM.
567 · bundle
deeptools
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
bulk-rnaseq
Orchestrates a complete bulk RNA-seq differential-expression study from raw FASTQ reads through QC, alignment, quantification, differential expression, pathway enrichment, and publication figures.
30.2k · bundle
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
scikit-bio
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
pydeseq2
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
scvelo
Analyze RNA velocity in single-cell RNA-seq data with scVelo, estimating cell state transitions from unspliced/spliced mRNA dynamics, inferring trajectory directions, computing latent time, and identifying driver genes.
253 · bundle
scanpy
Analyze single-cell RNA-seq data using Scanpy, including quality control, normalization, clustering, marker gene identification, and visualization.
42.4k
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
scanpy
Analyze single-cell RNA-seq data with Scanpy, covering quality control, normalization, dimensionality reduction, clustering, marker gene identification, and visualization.
0 · bundle