kma is an R package that performs intron retention estimation and detection
using biological replicates and resampling. Updated code can always be found at
https://github.com/pachterlab/kma
To install, first ensure you have the required packages:
required_packages <- c("devtools", "data.table", "reshape2", "dplyr")
install.packages(required_packages)
You can then install the package using devtools:
devtools::install_github("pachterlab/kma")
Assuming all goes well, load kma:
library("kma")
After it has been installed, please see the vignette in R:
vignette("kma")
Please file these on Github.
- Additional exploratory analysis plotting tools
- Provide differential intron usage analysis between experimental conditions
- We currently have some ideas on how to do this and will likely be implementing it soon
- Provide time series analysis
Software was developed by Harold Pimentel. Methods were developed with Lior Pachter and John Conboy.
Below you will find a list of related tools and how they differ from kma.
DEXSeq is interested in differential usage across genic regions. As a result, it does not determine whether an intron is being "used" (relative to transript expression), simply that it is being "differentially used."
MISO can calculate the intronic percent spliced in (PSI), though it currently
requires a modified annotation from their website. kma can currently work with any
annotation, as the annotation will be processed during the pre-processing step.
Also, MISO does not currently provide built-in suppport for
replicates.