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Understanding the Role of Transposable Elements in Maize Abiotic Stress Response

Abstract: 
<h3 class="red">Understanding the Role of Transposable Elements in Maize Abiotic Stress Response</h3><p>Abiotic stress, such as extreme temperatures or drought, severely limits agricultural productivity. These researchers have evidence that certain families of transposons can confer stress responsive expression patterns to nearby genes in maize. The first aim of this project is to define the role of transposons in gene expression responses to abiotic stress in several different tissues and genotypes. The focus of the second aim is to determining the mechanism by which transposons influence the stress-responsive expression of nearby genes. The third aim of this project will document natural variation for insertion sites of the transposons that confer stress-responsive gene expression and will attempt to identify protocols to mobilize these elements to generate novel allelic diversity in maize. This project will provide novel understanding of the molecular processes that underlie gene expression responses to abiotic stress. MSI is used for NGS data analysis and other downstream computationally intensive tasks.</p><p>Return to this PI&#39;s <a href="https://www.msi.umn.edu/pi/93cbdb0867d546668b1cec64d34ac20c/10968">main page</a>.</p>
Group name: 
hirschc3

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Deep Learning at MSI

Over the past year, MSI has been increasing resources available to researchers working in machine learning fields. Deep learning methods have been getting a great deal of attention due to recent advances in hardware and successful applications in the fields of image classification, computer vision...

breseq

Software Description: 

From the breseq manual pages:

breseq (pronounced: breeze-seq) is a computational pipeline for the analysis of short-read re-sequencing data (e.g. 454, Illumina, SOLiD, etc.).
 
It uses reference-based alignment approaches to predict mutations in a sample relative to an already sequenced genome. breseq is intended for microbial genomes (<10 Mb) and re-sequenced samples that are only slightly diverged from the reference sequence (<1 mutation per 1000 bp).
 
breseq‘s primary advantages over other existing software programs are that it can:
Predict new sequence junctions, such as those associated with mobile element insertions, from single-end read data.
 
Reliably identify short indel mutations by appropriately masking the ends of read alignments.
Produce annotated output describing biologically relevant mutational events.
breseq is available on the lab cluster.
 

 

Software Support Level: 
Secondary Support
Software Access Level: 
Open Access
Software Categories: 
Lab Documentation: 
module load breseq

This loads breseq, bowtie and R.

Example command:

>>>breseq -r NC_012967.gbk SRR030257_1.fastq SRR030257_2.fastq
 
The first named argument (-r) is the reference sequence. If you had multiple reference sequences, you could input multiple ones (e.g., -r NC_012967.gbk -r plasmid.gbk).
 
The unnamed arguments at the end of the command line are the read files. You can input as many as you need to and mix FASTQ files from different sequencing technologies (Illumina and 454).
 
Software Interactive/GUI: 
No

libsequence

Software Description: 

libsequence is a C++ library designed to aid writing applications for genomics and evolutionary genetics. A large amount of the library is dedicated to the analysis of "single nucleotide polymorphism", or SNP data. The library is intended to be viewed as a "BioC++" akin to the bioperl project, although the scope of libsequence is limited in comparison. Much of the bioperl project concerns parsing the output of various bioinformatics programs, and the management of databases of biological data. perl is a good language for such things, and libsequence tries not to re-invent the wheel. Rather, the focus is on biological computation, such as the analysis of SNP data and sequence divergence, and the analysis of data generated from coalescent simulation.

Software Support Level: 
Secondary Support
Software Access Level: 
Open Access
Software Categories: 
Software Interactive/GUI: 
No
General Linux Documentation: 

To use this software in an interactive Linux environment, run the commands:

module load libsequence

Documentation for libsequence can be found here

Tensorflow

Software Description: 

From the Tensorflow website:

TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. TensorFlow was originally developed by researchers and engineers working on the Google Brain Team within Google's Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well.

Software Support Level: 
Secondary Support
Software Access Level: 
Open Access
Software Categories: 
Mesabi Documentation: 

Tensorflow is available for use on MSI's Mesabi k40 nodes. To load tensorflow into your environment, use the following command:

module load tensorflow

Tensorflow is frequently used via its python interface. To use tensorflow in this manner after loading in the module, use the following procedure:

python

>>> import tensorflow as tf

There are a variety of tutorials available for using tensorflow on the official website.

Software Interactive/GUI: 
No

RStudio

Software Description: 

RStudio provides open source and enterprise-ready professional software for the R statistical computing environment. RStudio is an IDE for the R programming language.

Software Support Level: 
Secondary Support
Citrix Documentation: 

To run this software under Windows, connect using instructions provided on our Windows systems page.  Once logged in, navigate to:

Start > All Programs > RStudio > RStudio

RStudio home page
Additional documentation is available within the program through the help menu.

Software Access Level: 
Open Access
Software Interactive/GUI: 
No
General Linux Documentation: 

To run this software interactively in a Linux environment run the commands:

module load rstudio
rstudio

RStudio depends on the R package. This being the case, loading rstudio will by default load some version of R. If you wish to use a different version with RStudio, try something like the following:

module load rstudio
module unload R
module load R/2.15.1

Note that not all installed versions of R are compatible with rstudio.

Several versions of rstudio are available. To see a list, run the following command:

module avail rstudio

RStudio home page
Additional documentation is available within the program through the help menu.

HyPhy

Software Description: 

HyPhy stands for hypothesis testing using phylogenies. It is an open-source software package for the analysis of genetic sequences using techniques in phylogenetics, molecular evolution, and machine learning. It also features a complete graphical user interface (GUI) and a rich scripting language for limitless customization of analyses. Additionally, HyPhy features support for parallel computing environments (via message passing interface) and it can be compiled as a shared library and called from other programming environments such as Python or R.

Software Support Level: 
Primary Support
Itasca Documentation: 

To launch this software interactively in a Linux environment run the commands:

module load hyphy
HYPHYMPI

It requires a batch file to run the job.  For more detailed instruction on the program, please refer to:

http://hyphy.org/w/index.php/Main_Page

Software Access Level: 
Open Access
Software Categories: 
Lab Documentation: 

To launch this software interactively in a Linux environment run the commands:

module load hyphy
HYPHYMPI

It requires a batch file to run the job.  For more detailed instruction on the program, please refer to:

http://hyphy.org/w/index.php/Main_Page

Software Interactive/GUI: 
No

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