Getting Started with Random Forest
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A collection of my notes for getting started with random forest for genomics research.
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A collection of my notes for getting started with random forest for genomics research.
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A collection of data science, programming, and data visualization tutorials I have found on the internet. Sources referenced.
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A brief primer on heritability and estimating heritability using phenotype (any observable trait such as height, eye color, or a health condition) data from twins.
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I want to introduce sed in a quick and informal way for anyone who just wants to get a taste of what sed can do.
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If you are tired of typing out the same long command over and over again, it’s time to set up a few bash aliases. Aliases allow you to create shortcut commands for longer ones. For example, instead of typing out ls -l
, you could type ll
+ Enter
to save time.
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The standard pipeline that we use in the Brito Lab for quality control, alignments, and gene abundance calculations for metagenomic data.
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LSA was developed as a pre-assembly tool for partitioning metagenomic reads. It uses a hyperplane hashing function and streaming SVD in order to find covariance relations between k-mers. The code, and the process outline in LSFScripts in particular, have been optimized to scale to massive data sets in fixed memory with a highly distributed computing environment. For resources on LSA, see the following: Manual Github Useful Tips Reference
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How to get started using my favorite text editor.
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Are you tired of typing in a password every time you log into the lab’s server? Follow this tutorial to set up SSH keys so that you never have to type in your password again while logging in!
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We now have RStudio Server installed on all CBSU machines! This means that you can run a hosted RStudio session in your browser and not worry about copying over files from the server, or running out of memory on your own machine. Here are the steps you need to follow to use it.
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Disclaimer: This blog post will only be relevant to members of the Brito Lab.
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Welcome to my academic page. While working as a computational geneticist in graduate school, I’ve collected a lot of notes about how various programs/methods/fun little tricks work. I want to use this blog to share those insights, frustrations, and solutions. Some of them may only be useful to members of the Brito Lab, but my hope is that most will be general enough that anyone in the bioinformatics world could find them interesting.