Skills

Programming: 

• • Bioinformatics:  Python, R, Shell Scripting

  • Signal, image, and video processing: C, C++ (with OpenCV), MATLAB

Environments: 

• • Databricks, conda, Docker, AWS

  • RStudio, Jupyter notebook, Visual Studio.

Pipeline development:

Snakemake, nextflow

Deep learning

• • PyTorch, Pytorch Geometric, TensorFlow

  • Transformer, Performer, Graph Attention Network

  • Introductory knowledge of fastai

ML

• Classification, Gradient Boosting.

Statistical models

• Regression, Generalized linear model, Hypothesis testing

Genomics consortiums:

• Genomics England, UKBB, ENCODE, Open Targets Platform, ReMap2022

GWAS / QTL / variant analysis / TWAS / SNP:

• • GWAS inference: PLINK, SAIGE, GCTA / fastGWA

  • Variant analysis: GATK, PLINK, HLApers

  • eQTL analysis: MatrixQTL, tensorQTL, RASQUAL 

  • Fine mapping, colocalization, TWAS: CAVIAR, FINEMAP, coloc, enloc, prediXcan

  • Motif analysis: MEME suite

  • Databases: fiveX eQTL browser, DICE, ImmunexuT, Open Targets Genetics, A2F, eQTLGen, GWAS Catalog

Transcriptomics data analysis:

• • Short read RNA-seq: 

    • Alignment: STAR, Cufflinks, Picard, HTSeq

    • Quality control: FastQC

    • Differential gene analysis: DESeq2, edgeR, limma

    • Regulatory module analysis: WGCNA 

  • Long read RNA-seq:

    • PacBio long read: Developed custom pipeline using ISO-seq standard.

    • Oxford Nanopore (ONT) long read

      • QC: Nanoplot

      • Alignment: minimap2

      • Transcript quantification: FLAIR

  • Transposable element (TE) analysis and quantification: SQUIRE

Single-cell data analysis:

• • Single-cell RNA-seq and multi-omic data: CellRanger,  Seurat, scanpy, ArchR, Signac

  • Visualization: cellxgene, azimuth

  • Trajectory analysis: scVelo, multiVelo.

  • Batch correction: Harmony

  • Gene regulatory network analysis: Scenic+

  • Single-cell T cell receptor (TCR-seq) data analysis: MiXCR, Immcantation, immunarch

Epigenomics data (ChIP-seq, ATAC-seq) analysis:

• Alignment + Preprocessing + Quantification: Bowtie2, Tophat2, STAR, Cufflinks, Picard, HTSeq

• Peak Calling: MACS2

• Quality control: FastQC, ATACseqQC, ATAQV

Chromatin conformation capture (3C) data analysis:

• Preprocessing: BWA-MEM, HiC-pro, ICE, Juicebox,  Juicer tools, HiCRep 

• TAD calling: TOPDOM, Insulation score

• Loop callers: FitHiC & FitHiC2 (developed), FitHiChIP (developed), MAPS, hichipper

• Perturbation datasets (CRISPR) and Deep Learning tools: C. Origami

• List of important Hi-C tools: here

Generic NGS data analysis tools:

• • Generic suites:  HOMER, bedtools, deeptools, samtools, GSEA, Metascape

  • Genome browsers: WashU Epigenome browser, UCSC genome browser, IGV browser

  • Databases: JASPAR, ADASTRA

Phylogenetic analysis:              

• • Generic phylogenetic tree construction and analysis packages: Dendropy, Phylip, MrBayes, MEGA, PAML, PHYML, RAxML, FastTree (Uses NJ + NNI to infer likelihood trees), Tree Puzzle,  Tree-Rex

  • Protein / DNA sequence similarity/alignment packages: CLUSTAL, CLUSTALW, CLUSTALW2, MUSCLE, CLUSTAL OMEGA, QuickTree, and various  Sequence converter tools

  • Phylogenetic Tree Viewers: EvolView (online), TreeView (click here for Java version), Dendroscope, TreeGraph, FigTree, TreeCmp, TOPD/FMTS

Image/video processing:

• • OpenCV

Version Control:

• • GitHub