3. Data, Science & AI

Analyzes CRISPR gene editing outcomes from amplicon sequencing data, quantifying indels and HDR efficiency to generate comprehensive editing reports.

Aligns bisulfite-converted sequencing reads (WGBS, RRBS) to reference genomes using Bismark, producing methylation-aware BAM files.

Detects copy number variants from targeted/exome sequencing data using CNVkit, supporting tumor-normal, tumor-only, and germline analysis for WES and targeted panels.

Performs de novo genome assembly from Illumina short reads using SPAdes for bacterial, fungal, small eukaryotic, metagenome, and transcriptome data.

Interprets genetic variants using ClinVar, ACMG guidelines, and pathogenicity predictors to prioritize diagnostic and research variants.

Detects structural genomic variants (deletions, insertions, inversions) from long-read sequencing data using Sniffles, cuteSV, and SVIM.

Identifies differentially accessible chromatin regions between experimental conditions in ATAC-seq data using DiffBind or DESeq2.

Executes differential expression analysis on RNA-seq count data via edgeR in R/Bioconductor, handling normalization, dispersion estimation, and statistical testing.

Aligns RNA-seq reads to a reference genome using splice-aware STAR alignment with two-pass mode for novel splice junction detection.

Identifies metabolites in untargeted metabolomics by matching m/z, retention time, and MS/MS spectra against databases with confidence scoring.

Creates reproducible bioinformatics analysis reports with R Markdown, embedding code, results, and visualizations in HTML, PDF, or Word formats.

Provides foundational knowledge for creating, validating, and manipulating BED format files (BED3-BED12) in genomic coordinate analysis and bioinformatics workflows.

Executes Reactome pathway enrichment analysis including over-representation and GSEA with visualization and hierarchy exploration for biological data.

End-to-end microbiome analysis pipeline processing 16S amplicon data from FASTQ to differential abundance testing using DADA2 and ALDEx2.

Visualizes differential gene expression results from DESeq2 and edgeR, including MA plots, dispersion estimates, and sample distance heatmaps.

Identifies super-enhancers from H3K27ac ChIP-seq data using ROSE, supporting research on cell identity, cancer, and transcription factor binding.

Manipulates phylogenetic trees using Biopython Bio.Phylo for rooting, pruning, collapsing, and extracting subtrees.

End-to-end metabolomics pipeline automating raw mass spectrometry data processing, statistical analysis, and pathway mapping via XCMS.

Performs de novo and known motif analysis on genomic peak data using HOMER and MEME-ChIP for transcription factor binding site identification.

Performs metabolomics data preprocessing with MS-DIAL, including peak detection, alignment, and annotation for R/Python downstream analysis.

Converts raw Nanopore signal data (FAST5/POD5) to nucleotide sequences using AI-powered basecallers, including model selection and quality filtering.

Provides best practices for filtering genetic variants using GATK VQSR, hard filters, and bcftools expressions for SNPs and indels.

Handles multiple sequence alignment file conversions and operations for phylogenetic and conservation analysis using Biopython's Bio.AlignIO.

Fetches biological records from NCBI databases via Biopython, enabling sequence downloads, GenBank retrieval, and data parsing for bioinformatics workflows.