Current Virtual Training Projects (VTPs)

Be the first to learn about new VTPs from MILRD


VTPs Utilize:

  • Bioinformatics, computational biology and/or data science methods. Examples include: Data QC, Filtering, Normalization, Regression, Clustering, Biomarker Identification, Dimensionality Reduction, and Data Visualization (e.g. violin plots, scatterplots, heatmapts), Gene Set Enrichment/Pathway Analysis, Bulk RNAseq, Single-cell Transcriptomics/Epigenomics, Social Mobility Analysis, and Machine Learning.
  • Open-source programming languages (e.g. Unix, R, Python) so participants can use acquired skills after finishing a VTP without purchasing cost-prohibitive software.
  • Publicly available datasets so participants can continue to utilize the data if desired.

Metagenomics + Microbial Surveillance

Collaboration with Dr. David Danko, Mason Lab, Cornell Medical Center

 

Goal

Characterize mass-transit environmental microbiome samples using metagenomic analysis.

Domains

Linux, Data Analysis & Visualization in R, Metagenomics, Principal Component Analysis, Kraken (bioinformatics tool for metagenomic characterization/quantification)

Data Source

Danko, D., Bezdan, D. et al. Global Genetic Cartography of Urban Metagenomes and Anti-Microbial Resistance. Preprint on bioRxiv

Danko, D., Bezdan, D. et al. A global metagenomic map of urban microbiomes and antimicrobial resistance. Cell. New York Times coverage.

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Single-cell Transcriptomics + Lung Cell Characterization

Collaboration with Dr. Martina Bradic, Memorial Sloan Kettering Cancer Center

 

Goal

Transcriptomically profile the aging mouse lung using single-cell RNA-sequencing (scRNA-seq) analysis

Domains

Seurat, Linux, R, Library QC, Data filtering/clustering/PCA/t-SNE, Cell-type Assignment, Gene Expression, Drop-seq, 10x (optional additional dataset)

Data Source

Angelidis, I., Simon, L.M., Fernandez, I.E. et al. An atlas of the aging lung mapped by single cell transcriptomics and deep tissue proteomics. Nature Communications 2019. Preprint on bioRxiv.

(Optional additional 10x dataset) O’Koren, E., Yu, C. et al. Microglial Function Is Distinct in Different Anatomical Locations during Retinal Homeostasis and Degeneration. Immunity

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Variant Calling + COVID-19

Collaboration with Dr. Adriana Heguy, NYU Medical Center

 

Goal

Characterize nucleotide and amino acid variants from SARS-CoV-2+ patient samples

Domains

Linux, Bowtie2, SAMtools, BCFtools, IGV Genome Browser, GISAID

Data Source

Maurano et al. Sequencing identifies multiple early introductions of SARS-CoV-2 to the New York City Region. Genome Research 2020. Preprint on MedRxiv. New York Times coverage.

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Variant Calling

Single-cell Transcriptomics + Neuron Characterization in Habenula

Collaboration with Dr. Mike Wallace, Sabatini Lab at Harvard Medical School

 

Goal

Transcriptomically profile the murine habenula using single-cell RNA-sequencing (scRNA-seq) analysis.

Domains

Cellular/molecular neuroscience, Seurat, Linux, R, Library QC, Data filtering/clustering/PCA/t-SNE, Cell-type Assignment, Gene Expression

Data Source

Wallace et al. Anatomical and single-cell transcriptional profiling of the murine habenular complex. eLife 2020.  

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tSNE of Cell Clusters

Large-scale Data Economics + Social Mobility Analysis

Collaboration with Dr. Raj Chetty's Group & Opportunity Insights, Harvard University

 

Goal

Analyze and explore the childhood roots of social mobility at the community level.

Domains

Data Analysis in R, Data Visualization, Regression & Correlation Analysis

Data Source

Chetty et al. The Opportunity Atlas: Mapping the Childhood Roots of Social Mobility. NBER. Manuscript on Opportunity Insights. New York Times coverage.

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Single-cell Epigenomics + Neurodegenerative Disorder Elucidation

Goal

Profile the epigenomic state of human brain cells using single-cell Assay for Transposase-Accessible Chromatin sequencing (scATAC-seq) analysis and explore their implications for Alzheimer’s and Parkinson’s diseases. 

Domains

Cellular/Molecular Neuroscience, Neurodegenerative Disorders, Epigenetic State Analysis, Single-cell Epigenomics, Linux, R

Data Source

M. Ryan Corces et al. Single-cell epigenomic analyses implicate candidate causal variants at inherited risk loci for Alzheimer’s and Parkinson’s diseases. Nature Genetics.


Coming Soon


Stem Cell Biology + Pathway Analysis + Oncology

Goal

Conduct single-cell transcriptomics and pathway analysis to elucidate mechanisms underlying colorectal cancer and stem-cell Biology/regeneration. 

Domains

Cellular/Molecular Biology, Cancer Genetics, Single-cell Trancriptomics, Pathway Analysis, Linux, R

Data Source

Priscilla Cheung, Jordi Xiol et al. Regenerative Reprogramming of the Intestinal Stem Cell State via Hippo Signaling Suppresses Metastatic Colorectal Cancer. Cell Stem Cell

Detailed Descriptions:

  • Research Staff · Postdoc · Graduate Student Track
  • Undergraduate · High School Student Track

Epigenetic Analysis + Tumorigenesis Initiation 

Goal

Epigenetically profile functionally perturbed mouse model pancreatic tissue to explore how gene mutations and tissue damage combine to promote a chromatin structure that initiates tumor emergence. 

Domain

Cellular/Molecular Biology, Cancer Genetics, Epigenetic State Analysis, Single-cell Epigenomics, Linux, Python

Data Source

Alonso-Curbelo, D., Ho, YJ., Burdziak, C. et al. A gene–environment-induced epigenetic program initiates tumorigenesis. Nature

Detailed Descriptions:

  • Research Staff · Postdoc · Graduate Student Track
  • Undergraduate · High School Student Track

Cardiogenesis + Cardiovascular Defects + Cell Trajectory Analysis 

Goal

Analyze the developmental trajectories of cardiac cells from healthy and disease-model mice to elucidate the molecular mechanisms of cardiovascular defects. 

Domains

Cellular/Molecular Biology, Developmental Biology, Cardiovascular Biology, Pseudotime analysis. Linux, R

 

Data Source

de Soysa, T.Y., Ranade, S.S., Okawa, S. et al. Single-cell analysis of cardiogenesis reveals basis for organ-level developmental defects. Nature.

Detailed Descriptions:

  • Research Staff · Postdoc · Graduate Student Track
  • Undergraduate · High School Student Track

Spatial Transcriptomics + Amyotrophic Lateral Sclerosis

Goal

Using spatial transcriptomics, analyze control and amyotrophic lateral sclerosis (ALS) model mice at presymptomatic, onset, symptomatic, and end-stage time points to elucidate the underlying molecular mechanisms in ALS.

Domains

Cellular/Molecular Neuroscience, Neurodegenerative Disorders, Spatial Transcriptomics Analysis, Linux, Python

Data Source

Silas Maniatis, Tarmo Äijö, Sanja Vickovic et al. Spatiotemporal dynamics of molecular pathology in amyotrophic lateral sclerosis. Science

Detailed Descriptions:

  • Research Staff · Postdoc · Graduate Student Track
  • Undergraduate · High School Student Track

Single-cell Transcriptomics + Stem Cell Microenvironment 

Goal

Characterize the transcriptional landscape of bone-marrow microenvironment at single-cell resolution in homeostasis and under stress-induced haematopoiesis.

Domains

Cellular/Molecular Biology, Stem-cell Microenvironment, Hematology, scRNAseq, Bulk RNA-seq (optional), Linux, R

Data Source

Tikhonova, A.N., Dolgalev, I., Hu, H. et al. The bone marrow microenvironment at single-cell resolution. Nature

Detailed Descriptions:

  • Research Staff · Postdoc · Graduate Student Track
  • Undergraduate · High School Student Track

DNA Methylation State + Embryonic Stem Cell Biology + CRISPR Screens

Goal

Using data from a genome-wide CRISPR-Cas9 screen in human embryonic stem cells, characterize and validate top-hit DNA methylation regulators.

Domains

Cellular/Molecular Biology, CRISPR Screens, Methylation Analysis, Pathway Analysis, Linux, R

Data Source

Gary Dixon, Heng Pan, et al. QSER1 protects DNA methylation valleys from de novo methylation. Science.

Detailed Descriptions:

  • Research Staff · Postdoc · Graduate Student Track
  • Undergraduate · High School Student Track

Please contact us at [email protected] for more information about our VTPs.