Results for “genomebook”

Simulates meiotic recombination to produce offspring genomes from parent pairs, modeling Mendelian segregation, de novo mutation, sex determination, trait inference, and clinical evaluation against a disease registry.

Access NCBI GEO (Gene Expression Omnibus) for gene expression and functional genomics data — search and download microarray and RNA-seq datasets by GSE, GSM, GPL, or GDS accession and retrieve SOFT, MINiML, and series matrix files. Use when locating public expression datasets, fetching processed expression matrices, downloading a study's supplementary files, or sourcing per-study transcriptomics data for differential-expression analysis. For raw FASTQ sequencing reads by SRA/ENA run accession use alterlab-ena; for reference tissue-expression baselines (median TPM across human tissues) use alterlab-gtex; for cancer cohort somatic mutations and copy-number use alterlab-cbioportal. Part of the AlterLab Academic Skills suite.

Read, write, and analyze genomic datasets including SAM/BAM/CRAM alignments, VCF/BCF variants, and FASTA/FASTQ sequences using a Pythonic interface to htslib.

Train unsupervised machine learning models on genomic interval data from BED files, including region embeddings, single-cell ATAC-seq analysis, and consensus peak building.

Query 20+ bioinformatics databases from the command line or Python for gene information, sequences, protein structures, enrichment analysis, and more.

Trains machine learning models on genomic interval data from BED files, including region embeddings, single-cell ATAC-seq analysis, and consensus peak building.

Build and deploy apps/applets on the DNAnexus cloud genomics platform, manage data objects, run workflows, and use the dxpy Python SDK for genomics pipeline development and execution.

Access the COSMIC catalogue of somatic mutations in cancer to query somatic mutations, the Cancer Gene Census, mutational signatures, and gene fusions (authentication required). Use when curating known cancer driver genes, looking up recurrent somatic mutations in a gene, or interpreting mutational signatures for cancer research and precision oncology. Not for germline pathogenicity calls (use alterlab-clinvar) or interactive cohort visualization like OncoPrints and survival from study data (use alterlab-cbioportal). Part of the AlterLab Academic Skills suite.

Read, write, and manipulate genomic datasets including SAM/BAM/CRAM alignments, VCF/BCF variants, and FASTA/FASTQ sequences using a Pythonic interface to htslib.

Query 40+ bioinformatics services (UniProt, KEGG, ChEMBL, Reactome) with a unified Python interface for cross-database analysis, identifier mapping, and sequence analysis.

Assesses genome, transcriptome, and protein completeness with BUSCO v6, automatically resolving the correct lineage from an organism description and generating reproducible reports.

Queries 9 genomic databases in parallel for a given rsID, returning unified GWAS, PheWAS, eQTL, and fine-mapping reports.

Query cBioPortal via its keyless REST API for cancer genomics across TCGA, GENIE, MSK-IMPACT and hundreds of studies — somatic mutations, copy-number alterations (GISTIC), mRNA/protein expression, structural variants, and patient-level clinical/survival data. Use when asked how often a gene is mutated/amplified/deleted in a tumor type, to profile oncogenes or tumor suppressors across cancers (pan-cancer alteration frequency), to pull patient-level mutations joined to OS/clinical outcomes, or to validate a cancer target from cohort genomics. For germline variant pathogenicity use alterlab-clinvar; for mutational-signature (SBS) decomposition use alterlab-cosmic; for CRISPR/RNAi gene-dependency use alterlab-depmap; for aggregated target-disease evidence use alterlab-opentargets. Part of the AlterLab Academic Skills suite.

Compiles SOUL.md character profiles into synthetic diploid genomes by mapping trait scores to alleles at defined loci, producing .genome.json files.

Build and analyze phylogenetic trees using MAFFT, IQ-TREE 2, and FastTree, with visualization via ETE3 or FigTree for evolutionary analysis, microbial genomics, viral phylodynamics, and molecular clock studies.

Upserts a validated MDX book corpus into Supabase via Drizzle, hydrating books, chapters, sections, and chunks tables while preserving stable bookmark anchors and only re-embedding changed content.

Query the Cancer Dependency Map (DepMap) for cancer cell line gene dependency scores, drug sensitivity data, and gene effect profiles to identify cancer-specific vulnerabilities, synthetic lethal interactions, and validate oncology drug targets.