exploreRep: exploreRep: function to explore the reproducibility

In shaileshtripathi/samExploreR: samExploreR package: high-performance read summarisation to count vectors with avaliability of sequencing depth reduction simulation

Description

This function explores the reproducibility of analysis with annotation altering

Usage

exploreRep(df_d, lbl_vect, f)

Arguments

df_d	a dataframe containing the dataset to explore with 3 columns: label, f ratio, value to compare (e.g. number of differentially expressed genes)
lbl_vect	a vector of character strings specifing the labels for which the analysis should be run
f	A numeric value of f for which the analysis should be run

Details

exploreRep function to explore the reproducibility of the analysis with altering of annotation. It runs ANOVA test for values to compare (e.g. number of differentially expressed genes) corresponding to different Annotation labels (i.e. analysis' run for different annotation types)

This function takes as input a dataframe containing the dataset to explore.

Here is the example of the dataframe

...
AnnotA	0.1	13
AnnotB	0.1	101	
AnnotC	0.1	36
AnnotA	0.1	13
AnnotB	0.1	101	
AnnotC	0.1	36
AnnotA	0.4	40
AnnotB	0.4	153	
AnnotC	0.4	62
AnnotA	0.8	71
AnnotB	0.8	203
AnnotC	0.8	160
...

exploreRob Thired column gives the values to compare (here number of differentially expressed genes).

exploreRep function subsets the dataset to consider only valyes for one f and runs ANOVA test for groups corresponding to annotations of interest.

Value

An output of aov function

Author(s)

Alexey Stupnikov and Shailesh Tripathi

Examples

#library(samExploreR)
data("df_sole")
#run ANOVA for annotation types labeled 'New, Gene' and 'New, Exon' and 
#f value 0.9
exploreRep(df_sole, lbl_vect = c('New, Gene', 'Old, Gene'), f = 0.9)

#run ANOVA for annotation type labeled 'Old' and 'New' and f value 0.5
exploreRep(df_sole, lbl_vect = c('New, Gene', 'Old, Gene'), f = 0.5)

shaileshtripathi/samExploreR documentation built on May 29, 2019, 8:06 p.m.