Effects of cytokinin on gene expression in rice roots and shoots
This project contains data analysis code and data files for a project investigating how exogenous cytokinin affects gene expression in rice seedlings.
RNA-Seq libraries were prepared from roots and shoots of rice seedlings undergoing a 2 hour treatment with BA (synthetic cytokinin) applied hydroponically.
To visualize RNA-Seq read alignments, coverage graphs, and junctions inferred from spliced alignments, visit the japonica rice genome in Integrated Genome Browser.
About this project
This project is a collaboration between the Kieber Lab at UNC Chapel Hill, the Schaller Lab at Dartmouth University, the Solano lab at the National Biotechnology Center, and the Loraine Lab at the North Carolina Research Campus (and UNC Charlotte). A grant from the US National Science Foundation Plant Genome Research Program to PI Kieber and Co-PIs Ann Loraine and Eric Schaller funded this work.
About this repository
This repository contains analysis folders named for the type of data analysis code and results they contain.
Most analysis folders contain:
- .Rproj file - an RStudio project file. Open this in RStudio to re-run project code.
- .Rmd files - R Markdown files that contain an analysis focused on answering one or two discrete questions. These are typically formatted like miniature research articles, with Introduction, Results/Analysis, and Conclusions sections.
- .html files - output from running knitr on .Rmd files.
- results folders - contain files (typically tab-delimited) and images produced by .Rmd files.
- data - data files obtained from a compute cluster or other external source upstream of this data analysis
- src - R, python, or perl scripts used for simple data processing tasks
- README.md - documentation
Code used for analysis, making figures, and making data files for visualization in external site and programs are grouped into folders with names indicating their common purpose or analysis type.
Each module folder is designed to be run as a relatively self-contained project in RStudio. As such, each folder contains an ".Rproj" file. To run the code in RStudio, just open the .Rproj file and go from there. However, note that the code expects Unix-style file paths and depends on external libraries, mainly from Bioconductor.
Some modules depend on the output of other modules. Some modules also depend on externally supplied data files, which are version-controlled in ExternalDataSets but may also be available from external sites.
Analysis modules and other directories include .Rmd files (R Markdown), output from knitting Rmd files in HTML (Web pages), folders containing results (results) and (sometimes) folders containing externally supplied data used only in one module (data). Results folders also contain high-quality image files suitable for inclusion in slides or publications.
Makes counts, RPM, and RPKM files. Contains code for
- processing counts data (RiceCounts.Rmd)
- making RPM and RPKM files (MakeRpmRpkmFiles.Rmd)
- identifying most expressed genes per sample (TopExpressed.Rmd)
Look in Counts/results for RPM, RPKM, and other counts-related results files.
Identifies differentially expressed genes using tools and libraries from BioConductor.
Makes files with differential expression testing results:
- S.tsv.gz - compares BA-treated shoots (TS) to mock-treated, control shoots (CS)
- R.tsv.gz - same as above, but roots (TR vs. CR)
- C.tsv.gz - compares mock-treated, control roots (CR) to mock-treated, control shoots (CS)
- I.tsv.gz - tests for different responsiveness in roots versus shoots to cytokinin (I for "interaction" between tissue type and treatment)
Contains rice annotations and other data sets downloaded from IGBQuickLoad.org, GeneOntology.org, and other sources.
Identifies over and under represented GO categories among differentially expressed genes identifed in the DiffGeneExpr module.
Look here for lists of GO categories with unusually many or unusually few differentially expressed genes.
Contains manuscript, figure, and supplemental data files intended for publication.
Note that many of the files in this directory were automatically generated and then edited by hand to improve readability. The script "deployPaper.sh" documents some of this but is out of date.
Uses GOSeq to identify MapMan categories containing unusually many or few cytokinin-regulated genes.
Note: Uses a data file (Osa_MSU_v7.txt.gz) from MapMan Web site. Because of licensing restrictions, this file is not version-controlled here. To get this file, register at the MapMan site and following links labeled "download."
Contains code that:
- searches for over-represented motifs and sequences in promoter regions of differentially expressed genes and
- plots the location of motif instances within promoter regions.
by Ivory Blakley
Contains code and data files for analysis of Nanostrings gene expression analysis.
Uses groups of orthologous genes to compare the cytokinin response in rice to the response in Arabidopsis.
by Ivory Blakley
Compares rice RNA-Seq results with results from rice microarray experiments testing effects of pathogen infection on gene expression.
Contains code and data files used to assess enrichment of OsRR22 binding sites among differentially expressed genes.
Compares differential expression in roots to differential expression in shoots.
by Ivory Blakley
Investigates cytokinin up and down regulation of transcription factors, especially transcription factors from the WRKY family.
Generates rectangular, proportionately sized Venn diagram indicating overlap between up- or down-regulated differentially expressed genes in roots and shoots.
by Ivory Blakley
- Ann Loraine email@example.com
- Ivory Blakley firstname.lastname@example.org
Copyright (c) University of North Carolina at Charlotte
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