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sleuth: inspect your RNA-Seq

Investigate RNA-Seq transcript abundance from kallisto and perform differential expression analysis.

Installation

The easiest way to install is using the devtools package through Bioconductor.

source("http://bioconductor.org/biocLite.R")
biocLite("devtools")    # only if devtools not yet installed
biocLite("pachterlab/sleuth")

These commands will install sleuth along with all of its dependencies. You can then load sleuth like any other R package:

library('sleuth')

Installation via conda

If you have conda, a cross-platform package manager installed, you can install sleuth via the bioconda channel.

conda install --channel bioconda r-sleuth

Documentation

We recommend starting with the vignette:

vignette('intro', package = 'sleuth')

Detailed documentation can be retrieved within R using the help() command:

help(package = 'sleuth')

Specific function documentation can also be accessed using ? as you would for any other function in R:

?sleuth_prep

Conventions

  • All sleuth "core" functionality is prefixed by sleuth_ (e.g.

sleuth_prep()).

  • All sleuth plots are prefixed with plot_ (e.g. plot_ma())

Further help

Please visit the sleuth website for ways to get help. We have several new walk-throughs at the main sleuth website. In particular, you might find the kallisto-sleuth users Google group helpful.

Please post bug reports on GitHub.

Copyright

Copyright (C) 2017 Harold Pimentel, Nicolas Bray, Pall Melsted, Lior Pachter

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Version

Version

0.29.0

License

GPL-3

Issues

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Maintainer

Last Published

February 7th, 2020

Functions in sleuth (0.29.0)

basic_filter

Basic row filter
$<-.sleuth

Extend internal '$<-' for sleuth object
get_col

Get a data.frame from all kallisto objects
kallisto_table

Get kallisto abundance table from a sleuth object
plot_ma

MA plot
design_matrix

Extract design matrix
plot_mean_var

Mean-variance relationship
plot_qq

QQ plot
plot_sample_density

Plot sample density
sleuth_prep

Constructor for a 'sleuth' object
extract_model

Extract a model from a sleuth object
plot_transcript_heatmap

Plot clustered heatmap
plot_vars

Plot technical variance versus observed variance
sleuth_save

save a sleuth object
sleuth_to_matrix

Convert a sleuth object to matrix
sleuth_results

Extract Wald test results from a sleuth object
plot_group_density

Plot density
plot_loadings

Plot Loadings and Interpretations
read_kallisto

Read kallisto output
read_kallisto_h5

Read a kallisto object from an HDF5 file
sleuth_load

load a sleuth object
sleuth_lrt

sleuth likelihood ratio test
sleuth_wt

Wald test for a sleuth model
transcripts_from_gene

Get the names of the transcripts associated to a gene
get_bootstrap_summary

bootstrap summary
get_bootstraps

Extract bootstrap for a specific transcript
plot_fld.kallisto

Plot fragment length distribution
plot_fld.sleuth

Plot fragment length distribution
plot_sample_heatmap

Plot sample heatmap
plot_scatter

Sample to sample scatter plot
read_kallisto_tsv

Read kallisto plaintext output
sleuth_deploy

deploy a sleuth object
plot_pc_variance

Plot PC Variance
plot_pca

Plot PCA
sleuth_fit

Fit a measurement error model
sleuth_gene_table

Create a gene table from a sleuth object
log_transform

Natural log and offset transformation
models

View which models have been fit
norm_factors

Normalization factors
plot_bootstrap

Plot bootstrap summary
plot_volcano

Plot volcano plot
print.sleuth_model

Print sleuth model
sleuth_live

Interactive sleuth visualization with Shiny
sleuth_live_settings

settings for sleuth_live
transform_fun<-

Change sleuth transform function
transform_status

Check Transform Sync Status of Sleuth Fits