Welcome to the ArtathonBack to Top

The following page is divided into 3 sections. The 1st describes the general problem in visualizing biological data that we would like to solve. The 2nd describes the more specific characteristics of immune cell populations and the 3rd the specific question and datasets we wish to address. Feel free to read one or all before you start thinking of what to do.

Section 1- How can we create an iteractive visualization of millions of individuals?Back to Top

Our body is a population. Trillions of different cells working in tandem with no specific master cells. The study of biology is thus study of many individual cells, acting together. It is hard to characterize and understand the actions of many individuals. Until recently this was only a theoretical worry in biology because most experiments could either measure a few isolated cells or the impact of groups of cells, summing over whole populations. They could not measure and describe many individual cells from the same population. However, in the last few years, an explosion of novel experimental techniques has made it feasible to measure cell characteristics from thousands and even hundreds of thousands of individual cells at once. The things we can measure now far surpass our tools for visualization and analysis. We would like to present two related challenges for this more general problem:

Section 2- a clonal description of the B cell (antibody) populationsBack to Top

The difference between a harmful and successful immune response is not based on the behavior a single B cell with a single specific antibody/ B cell receptor type. Rather it’s the result of the action of a population of B cells with many different B cell receptors. The diversity of B cell receptors is huge (> 1011 in a single person) and is the result of two steps of diversification and selection (see Figure).

Section 3- creating interactive visualizations of B cell populationsBack to Top

In the Artathon we wish to take the challenges in section 1 and make them more B cell specific. Leading us to the following challenges in B cell population visualization:

Accessing & Using the DataBack to Top

Accessing the Data

Data for each dataset can be accessed in two ways:

  1. The TSV-formatted data can be directly downloaded here.
  2. The underlying databases can be directly accessed with the commands listed with each dataset.

Using the Data

For each dataset there are two or three sets of files:

  1. One file for each subject named SUBJECT.changeo.tsv which is the sequence data in Change-O format.
  2. A file named clones.tsv which contains information about the clones in the dataset.
  3. For some datasets, a file selection_pressure.tsv which contains information about the selection pressure on each clone/sample combination.

DatasetsBack to Top

We will be working with three datasets:

1. Tissue Atlas (With Insertion / Deletions)

Link: http://clash.biomed.drexel.edu/databases/lp15
MySQL - Philadelphia: mysql -u artathon -h clash.biomed.drexel.edu lp15
MySQL - localhost: "TBD"
Relevant Publication: An atlas of B-cell clonal distribution in the human body
Data Description: B-cell responses result in clonal expansion, and can occur in a variety of tissues. To define how B-cell clones are distributed in the body, we sequenced 933,427 B-cell clonal lineages and mapped them to eight different anatomic compartments in six human organ donors. We show that large B-cell clones partition into two broad networks—one spans the blood, bone marrow, spleen and lung, while the other is restricted to tissues within the gastrointestinal (GI) tract (jejunum, ileum and colon). Notably, GI tract clones display extensive sharing of sequence variants among different portions of the tract and have higher frequencies of somatic hypermutation, suggesting extensive and serial rounds of clonal expansion and selection. Our findings provide an anatomic atlas of B-cell clonal lineages, their properties and tissue connections. This resource serves as a foundation for studies of tissue-based immunity, including vaccine responses, infections, autoimmunity and cancer.

2. Multiple Sclerosis

Link: http://clash.biomed.drexel.edu/databases/ms
MySQL - Philadelphia: mysql -u artathon -h clash.biomed.drexel.edu ms
MySQL - localhost: "TBD"
Relevant Publication: B cells populating the multiple sclerosis brain mature in the draining cervical lymph nodes
Data Description: Multiple sclerosis (MS) is an inflammatory disease of the central nervous system (CNS) characterized by autoimmune-mediated demyelination and neurodegeneration. The CNS of patients with MS harbors expanded clones of antigen-experienced B cells that reside in distinct compartments including the meninges, cerebrospinal fluid (CSF), and parenchyma. It is not understood whether this immune infiltrate initiates its development in the CNS or in peripheral tissues. B cells in the CSF can exchange with those in peripheral blood, implying that CNS B cells may have access to lymphoid tissue that may be the specific compartment(s) in which CNS-resident B cells encounter antigen and experience affinity maturation. Paired tissues were used to determine whether the B cells that populate the CNS mature in the draining cervical lymph nodes (CLNs). High-throughput sequencing of the antibody repertoire demonstrated that clonally expanded B cells were present in both compartments. Founding members of clones were more often found in the draining CLNs. More mature clonal members derived from these founders were observed in the draining CLNs and also in the CNS, including lesions. These data provide new evidence that B cells traffic freely across the tissue barrier, with the majority of B cell maturation occurring outside of the CNS in the secondary lymphoid tissue. Our study may aid in further defining the mechanisms of immunomodulatory therapies that either deplete circulating B cells or affect the intrathecal B cell compartment by inhibiting lymphocyte transmigration into the CNS.

3. Influenza

Link: http://clash.biomed.drexel.edu/databases/influenza
MySQL - Philadelphia: mysql -u artathon -h clash.biomed.drexel.edu influenza
MySQL - localhost: "TBD"
Relevant Publications: High-resolution antibody dynamics of vaccine-induced immune responses, The mutation patterns in B-cell immunoglobulin receptors reflect the influence of selection acting at multiple time-scales
Data Description: The immune system must constantly adapt to combat infections and other challenges. This is accomplished by continuously evolving the antibody repertoire, and by maintaining memory of prior challenges. By using next-generation DNA sequencing technology, we have examined the shear amount of antibody made by individuals during a flu vaccination trial. We demonstrate one of the first characterizations of the fast antibody dynamics through time in multiple individuals responding to an immune challenge.