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FreedomIntelligence / arboretoInfer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3)
FreedomIntelligence / bio-alignment-filteringFilter alignments by flags, quality, and regions using samtools and pysam.
FreedomIntelligence / bio-alignment-indexingCreate indices for random access to alignment files using samtools and pysam.
FreedomIntelligence / bio-alignment-sortingSort alignment files by coordinate or read name using samtools and pysam.
FreedomIntelligence / bio-alignment-validationPost-alignment quality control to verify alignment quality and identify issues.
FreedomIntelligence / bio-batch-downloadsDownload large numbers of records from NCBI efficiently using the history server, batching, and proper rate limiting.
FreedomIntelligence / bio-blast-searchesRun BLAST searches against NCBI databases using Biopython's Bio.Blast module.
FreedomIntelligence / bio-clip-seq-clip-peak-callingPureCLIP uses an HMM to model crosslink sites, incorporating enrichment and truncation signals.
FreedomIntelligence / bio-codon-usageAnalyze codon usage patterns and calculate codon adaptation metrics using Biopython.
FreedomIntelligence / bio-data-visualization-circos-plotsCircular genome visualizations for displaying multiple data tracks around chromosome ideograms.
FreedomIntelligence / bio-entrez-fetchRetrieve records from NCBI databases using Biopython's Entrez module (EFetch, ESummary utilities).
FreedomIntelligence / bio-entrez-linkNavigate between NCBI databases using Biopython's Entrez module (ELink utility).
FreedomIntelligence / bio-entrez-searchSearch NCBI databases using Biopython's Entrez module (ESearch, EInfo, EGQuery utilities).
FreedomIntelligence / bio-genome-assembly-assembly-polishingImprove assembly accuracy by correcting errors using additional sequencing data.
FreedomIntelligence / bio-genome-assembly-assembly-qcEvaluate genome assembly quality with contiguity metrics (QUAST) and gene completeness (BUSCO).
FreedomIntelligence / bio-genome-assembly-long-read-assemblyAssemble genomes from Oxford Nanopore (ONT) or PacBio long reads for highly contiguous assemblies.
FreedomIntelligence / bio-genome-assembly-short-read-assemblyAssemble genomes from Illumina paired-end or single-end reads using SPAdes.
FreedomIntelligence / bio-genome-intervals-bed-file-basicsBED (Browser Extensible Data) format stores genomic intervals. Uses 0-based, half-open coordinates.
FreedomIntelligence / bio-genome-intervals-bigwig-tracksBigWig is an indexed binary format for continuous genomic data. Efficient for genome browsers and programmatic access.
FreedomIntelligence / bio-genome-intervals-coverage-analysisCalculate coverage and depth across genomic regions using bedtools and pybedtools.
FreedomIntelligence / bio-genome-intervals-gtf-gff-handlingGTF and GFF3 are standard gene annotation formats. Both use 1-based coordinates.
FreedomIntelligence / bio-genome-intervals-interval-arithmeticCore set operations on genomic intervals using bedtools (CLI) and pybedtools (Python).
FreedomIntelligence / bio-genome-intervals-proximity-operationsOperations for finding nearby features and extending intervals using bedtools and pybedtools.
FreedomIntelligence / bio-geo-dataQuery and access Gene Expression Omnibus datasets using Biopython's Entrez module.
FreedomIntelligence / bio-liquid-biopsy-pipelineComplete workflow for cfDNA analysis from sequencing to clinical interpretation.
FreedomIntelligence / bio-local-blastRun BLAST searches locally using NCBI BLAST+ command-line tools.
FreedomIntelligence / armored-cart-design-agentThe Armored CAR-T Design Agent provides AI-assisted design of next-generation armored CAR-T cells engineered to express cytokines, chemokines, or other enhancing factors.
FreedomIntelligence / aav-vector-design-agentThe AAV Vector Design Agent provides AI-driven design of adeno-associated virus vectors for gene therapy applications. It covers capsid selection and engineering, promoter/enhancer design, transgene optimization, and manufacturing considerations.
FreedomIntelligence / bio-experimental-design-power-analysisPower = probability of detecting a true effect. Underpowered studies waste resources; overpowered studies are inefficient.
FreedomIntelligence / bio-experimental-design-sample-sizeWhen resources are limited, prioritize: 1. Biological replicates over technical replicates 2. More samples over deeper sequencing (after ~20M reads for RNA-seq) 3. Balanced designs (equal n per group)
