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blaserlab/README.md

Welcome to the Blaser Lab

parabiotics CXCR1 remodels the vascular niche to promote hematopoietic stem and progenitor cell engraftment

Welcome to the Blaser Lab Github page! This serves as our lab website. Why not? Github is a great resource that we use daily and from here you can find all of the papers and other resources we have published.

Our lab is interested in hematopoiesis and leukemogenesis. The image you see above is related to one of my papers from a few years ago. Using parabiotic zebrafish we found a way to make the zebrafish hematopoietic microenvironemt support more stem cells. The main question we have in the lab now is how does the hematopoietic microenvironment control long-term hematopoietic stem cell fate. Fate can be defined phylogenetically and in some ways can be thought of as clonal diversity. Fate can also be defined phenotypically which we often describe through functional assays and/or transcriptional state. We study HSC fate in the zebrafish model using genetics, cellular barcoding, time-lapse imaging, and single cell transcriptomic and epigenetic assays. By understanding how the microenvironment alters these aspects of HSC fate, we can understand more about how leukemia develops. We may also be able to preserve HSC clonal diversity under conditions of stress such as hematopoietic stem cell transplantation.

Click here for my NCBI Bibliography

Selected Research Publications

Here are links to some recent papers with their corresponding data and analysis packages.

Code to generate all R-based figures (probably 90-95% of the panels for most manuscripts) is stored in an analysis project. These are public git repositories. They will only work if you also have the companion data package. The data packages are elsewhere - either in figshare or another repository if required by the journal. Instructions for installing and using the code and data together are provided on the analysis project README.

Computational Resources

This started out as project setup templates.

It expanded to become a general utility package for setting up projects and handling packages.

Then it expanded again to become a deployable computational environment for single or multi-user systems. Works on Mac, Linux and Windows.

It takes some concepts from renv, incorporates pak as the default installation tool which massively improves speed, and enforces many optimized parameters for installation and cacheing functions.

The underlying philosophy of blaseRtools is that we try to reduce the cognitive burden related to working with diverse sets of bioinformatics tools. We try to process raw data into common data structures that are as simple to understand and work with as possible.

The primary focus is on tools for downstream analysis and visualization of single cell RNAseq data. A secondary set of functions focuses on manipulation of genomic sequences and export to genebank files for interactive use outside of R.

This is like a CRAN repo for everybody. This is your best option for installing blaseRtools and blaseRtemplates. MAC and Windows binaries are available. See the top of the page for instructions on how to enable blaserlab repo.

Laboratory Resources

  • Recipes: Basic recipes we use regularly for fish work, cloning and molecular biology.
  • Protocols: These are protocols we use for cloning, fish work etc. WIP.

Teaching

The course is complete for 2023. You can find the course page and links to the tutorial videos at the link above.

People

  • Brad Blaser: Assistant Professor of Medicine, OSU College of Medicine, Division of Hematology.
  • Wantong Li: Wantong is a third-year graduate student in the OSU MCDB program.
  • Konur Oyman: Konur is a second-year graduate student in the OSU MCDB program.
  • Annika Chura: Annika is a second-year graduate student in the OSU MCDB program.

Pinned Loading

  1. blaseRtools blaseRtools Public

    R Tools for Blaser Lab Data Analysis

    R 1

  2. carson_ibr_trial carson_ibr_trial Public

    Analysis of mdscs in cancer patients treated with ibrutinib

    R

  3. ficlatuzumab_aml ficlatuzumab_aml Public

    HTML

  4. hanel_lapo hanel_lapo Public

    R

  5. mace_paper_2020 mace_paper_2020 Public

    ScRNAseq for Mace Lab Paper, JITC 2020

    R

  6. pkc_cxcl8 pkc_cxcl8 Public

    R