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About me

Originally, I am from a town called Oxford, Ohio.  I graduated Miami University in 2014, obtaining degrees in Computer Science, Mathematics & Statistics, Electrical Engineering and Engineering Physics.  During that time, I have worked in numerous bioinformatics labs, at Miami University, Cold Spring Harbor Laboratories and Johns Hopkins University.  In addition, I was heavily involved with Miami University's autonomous robot, Redblade.

Now, my focus in microbiome studies.  I am currently a PhD student in Computer Science at University of California, San Diego working in Rob Knight's lab.  Specifically,  I am interested in developing algorithms and statistical theory to better understand microbial ecosystems.

I am currently involved with scikit-bio, Emperor the American-Gut project, and the Earth Microbiome project.






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ANCOM explained

In case you have not heard, ANCOM is another differential abundance test, designed specifically for tweezing out differentially abundance bacteria between groups.  Now, note that there are a ton of differential abundance techniques out there.  And one might ask why are there so many people focused on this seemingly simple problem. It turns out that this problem is actually impossible.   And this is rooted into the issue of relative abundances.  A change of 1 species between samples can be also explained by the change of all of the other species between samples.   Let's take a look at simple, concrete example. Here we have ten species, and 1 species doubles after the first time point.  If we know the original abundances of this species, it's pretty clear that species 1 doubled.  However, if we can only obtain the proportions of species within the environment, the message isn't so clear. Above are the proportions of the species in the e...
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Encoding design matrices in Patsy

Some of us have seen the connections between ANOVA and linear regression (see here  for more detailed explanation).  In order to draw the equivalence between ANOVA and linear regression, we need a design matrix. For instance if we have a series of observations A, B, C as follows \[ \{A, B, C, A, A, B, C\}\] If we wanted to reformulate this into ANOVA-style test, we can do a comparison between A vs B, and A vs C.  We can encode that design matrix as follows \begin{bmatrix} 0 & 1 & 0 & 0 & 0 & 1 & 0 \\ 0 & 0 & 0 & 1 & 1 & 0 & 1 \\ \end{bmatrix} In the first row of the matrix, only the entries with B are labeled (since we are doing a comparison between A and B. In the second row, only the entries with C are labeled.  Since we have set A to implicitly be the reference, there is no row corresponding to A. If we want to explicitly derive this design matrix in patsy, we can do it as f...
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Behind the scenes with BIOM tables

Today, I'll be covering the BIOM file format , a standardized file format for storing sequence counts in samples.  This file format is typically used in the biological sciences, most notably in amplicon sequencing technologies, such as 16S sequencing. For those of you that aren't as familiar with these technologies.  When we conduct survey studies, we like to get a broad overview of the microbes that are living within a raw sample.  But we don't need to sequence the entire bacteria's genome to identify what the bacteria is.  We can just a sequence a housekeeping gene that every bacteria as - the 16S ribosome. Its a similar strategy deployed in court.  When DNA evidence is presented in the court room, only a tiny, tiny portion of an individuals DNA is actually required to uniquely identify that person. But moving on. The BIOM file format was originally designed to store counts of 16S sequences across samples, but it has grown to become a more generalized...
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