Project Update

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Some Background:  My long term goal is to complete a BS CompE and an MBA under the UNM 3+2 program, expected May 2015. I’ve got a ton of work experience in project management; I’m really good at it, and I love it.  I came back to school so I could eventually get into management.

Anthony and I have been talking quite a bit about the best fit for me here in the BioPhysics Lab. I really enjoy learning about everything, and it is all really interesting, and Anthony and I all work well together. One morning we were talking about all the projects we have going on and Anthony asked if I wanted to be the project manager for them. What a great fit for my goals and experience. We decided that I would work as a Research Assistant, focusing on the project management side of our work.

So, the semester is started, and I’ve finally gotten a regular lab schedule worked out. Anthony and I met today about all of our ongoing projects. The synopsis of current and upcoming happenings in our lab is posted on Google Docs.

P.S. I’ve had to shelve my R learning project for now. I’ve gotten a fair understanding of the language… enough to basically understand code already written and edit it if needed. I’ve also gotten the hang of the syntax. Had to put it down for a bit though, this semester I’ve got 4 classes with 4 languages to learn. I didn’t want to push my brain over the edge.


Running someone else’s code

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Dr. Koch wrote some R code to compare Anthony and my FTIR data with Dr. Siegelstein’s data from 1981. The night before my presentation took a look at his code and thought, I’m going to tweak it just a little bit before my presentation to show how easy working with R can be. I had forgotten that all the little non-code related things can turn into a lot of work when “tweaking.” Especially when I’m new to the language (and haven’t written code in a really, really long time. Needless to say I ran out of time.

Today I’ve been working on the tweak (open in notepad, or some other editor). It’s been a really good learning experience. Here is what I’ve done so far:

I had to first upload the Rcurl and binom packages for the require command.

Dr. Koch read the Siegelstein data in as a table (read.table). I couldn’t get that to work so I copied the data into an Excel spreadsheet and saved it as a .csv file which I was then able to upload with the read.csv command.

Running the code I was getting an error message after the names(refwater) command. Steve skipped the first 5 rows of the table file and then adding the column names with names(). This wasn’t working for me. I was getting the following error:

names(refwater) <- c(“wavelength”, “abs”)
## getting the following error after this line
## Error in names(refwater) <- c(“wavelength”, “abs”) :
##  ‘names’ attribute [2] must be the same length as the vector [1]
## which is messing up all references to refwater

Steve suggested that I try str(refwater) to see what kind of data structure I was dealing with. I tried that, hoping for some enlightenment. What I recieved was:

‘data.frame’:   1262 obs. of  1 variable:
 $ V1: Factor w/ 1262 levels “10,21928”,”100,6.82E+05″,..: 1262 1 48 89 125 166 247 332 402 444 …

Which I think may mean exactly what Steve thought, “it’s coming in as a 1-dimension array of characters (vector). ” I don’t feel very enlightened.

So, I decided to forget the names() option and just put the names of the columns in the .csv file directly.  Adding ‘wavelength’ and ‘abs’ to row 5 columns 1 and 2, respectively, did the trick (and commented out the names() line)!

Now I’m only getting the following error message in two places.
> lines(subref$wavelength/1000, subref$abs, type=”l”, lty=1, col=”red”)
Error in subref$wavelength : $ operator is invalid for atomic vectors
Which I think may because we are using a matrix instead of a dataset. I’m looking into that now.
Oh and my graphs are a little wacked:

REU January Presentation

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Today was presentation day at CHTM. All the REU students (me included) gave a 20 minute presentation about what we have been doing for our research. I don’t know why, but I get extremely nervous for these presentations. The strange thing is I have a lot of experience speaking to crowds of people. I used to teach continuing education classes, and was never even a little bit nervous. I wonder what is going on?

Anyway, all this week Dr. Koch, Anthony and I have been working on my Mind Map presentation. I wanted to do something different from the standard PowerPoint presentation. Don’t get me wrong, PowerPoint is a good tool, I just wanted to do something different. We decided a Mind Map would be a good way to show case one of the many tools/applications that we use here in Kochlab.

In addition, I handed out little cards with a qr code and a short link to a google docs spreadsheet with links to many of the tools we use for our ONS. My Mind Map also had links to most of the information that I used for my research and presentation.

After it was all over I realized that I had forgotten to show the really cool, time lapse growth images that Anthony had put together for the D2O experiments.

Next presentation I will take Dr. Koch’s suggestion and practice, out loud, the entire presentation. If I do this several times I might not get stage fright quite so bad.

I’m really grateful for the opportunities that have come my way  since I’ve been working here at CHTM and KochLab. Dr. Koch and Anthony have been absolutely great to work with. Linda Bugge has been a good friend and really helpful with all the administrative “stoof.” It is an honor to have been selected to be a part of the NSF grant. I’m meeting some really awesome and brilliant people here. I’m super lucky.

Working in R


Brain Dump of what I’ve learned today:

  1. R’s GUI preferences are stored in the Rconsole file. I’ve found two on my machine, one in C:\Program Files\R\R-2.14.1\etc, and a second (the one that R seems to be using for its GUI) in C:\Users\Alex\Documents. I find it strange that the one that R is pulling from is in Documents and not with the other R program files.
  2. I’ve started a document listing the commands that I learn as I’m going (probably will stop updating when my book arrives on Saturday. It’s posted on Google Docs
  3. I wanted a way to sync my MS Office documents with Google Docs, and I didn’t see anything other than to re-upload and overwrite. Found Google Cloud Connect after searching for “sync google docs.” (I also didn’t like the way Google messed with my table formatting.) Note: The Google Cloud toolbar is bulky.
  4. Getting a file off of the internet requires the package RCurl, which has the function getURL.

I spent most of the day going over, line by line Dr. Koch’s R code when he compared Anthony’s and my FTIR with Seigelstein’s. I opened the code in RStudio and used the R Console to pull up the help for each of the commands/functions. Although, on a high level I understood what the code was doing, it was helpful to get down and dirty and read the specs and learn about the arguments. I wont remember how to do stuff on my own, but I’ll know what can be done. As I’m moving along I’m taking notes in my R commands.docx document.

I’m taking a break. I think I’ll watch some youtube videos tonight.

Tinn-R vs. RStudio


I spent some of the morning looking over some more R code information. Dr. Koch came in later and he set me up with a server account, and showed me some back-up options using Sync Toy.

Later we were discussing editor options for R we decided to install Tinn-R on my machine. It looked like a great tool when he showed it to me, but for some reason we could not get the thing to work properly on my machine. We followed the instructions on the BioInformatics site, but it just wouldn’t work for me. We would get the error message object “.trPaths” not found every time we ran a script. We were able to override this (once) using the source() option, but that kind of defeats the purpose of having an editor, right?

We did everything! Editing files manually, uninstalling Tinn-R and reinstalling. Checking to make sure all the files were being pointed to correctly. Nope! Would not work. After he left for the night, I tried some more. I eventually uninstalled both Tinn-R and R and reinstalled, setting the Rgui setting to SDI at install (hoping that would help … see page 4 of the install instructions from bioinformatics).

I finally was feeling very discouraged and did a search for “object “.trPaths” not found.” Search results netted a few solutions; none of them worked. I tried searching the R project site and tried that solution; also didn’t work. Then I thought, maybe its that I have the newest release (2.14.1), so I ran a google search for installing tinn-r to run with r 2.14.1.

The second result was a blog post about RStudio, so I gave it a try. Voila! It works!

I didn’t have to change any options or files. Note: I was only able to play with it for a minute or two, but it looks very similar to the MATLAB environment. I think I’m gonna like it.

Uninstalling Tinn-R now.  Re-updating my file, and done!

R Tutorials


I spent all day going through several R tutorials. My brain is a little spent. I’ve realized that I need a good reference book. I’m the geek that likes to read the dictionary. When I learn new code I like to read through the book with the basic commands first, before I start banging stuff out. I learn best when I know what’s available to use and then I can put things together.

That being said, I did go to a local brick and mortor book store to look for a reference book a few weeks ago with Anthony. The selection of books available there was disappointing. Of course there is a plethora of books available online. I”ll be ordering one in the next day or two.  I’d also like to know what all the library packages do. I’m hoping that the book I get has a good package referrence.

Part of the reason for my lack of understanding might also be that I don’t have statistics experience. So, therre were a few things in the tutorials that I didn”t understand from that angle. I”ll get it. More studying to do tomorrow.

What is R?

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Last month Dr. Koch decided we would use R as our graphing/statistics tool for our figures. I had never heard of it before the email (and was wondering what happened to the letters between D and Q). So I did a quick search right before the holidays for a little introduction to R. I found a webinar by David Smith with Revolution.

Note: I watched the entire webinar before I realized that this was a third party presentation. Although the webinar has some good information the best place to start is at the R project’s home page.

Today I spent my first day back in the lab downloading, installing, and learning the basics of R. It looks like an interesting tool. I don’t think it qualifies as a full-on language like C/C++, but it looks like it may be just as powerful as say MATLAB. I’m not sure yet, and will spend tomorrow going through some online lessons. I also did some searching for a good R book… I’m hoping to get the ‘Introduction to R’ book.

I also spent part of the day reviewing my notes from before break, prioritizing my to-do list, and looking at a few of the other tools that Kochlab uses for open notebooks. I tried my hand at the Basic offering of Mind Meister, opened up Slide Share, and I’ve got Google+ operating with video.

Finally I started to jot down some notes for a presentation I have in two weeks. What I would like to do is take all of Anthony’s data from the DDW and Repeating Crumley experiments, analyze them, and create some really kick-a** graphs for the presentation using R.

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