tri.surv: Survival Analysis of Triplets

In LncMod: Predicting Modulator and Functional/Survival Analysis

Description

Generate plots describing expression and survival comparison for train/test sample groups of a triplet (or triplets).

Usage

tri.surv(tri, exp.sur, train, test, index = 1)

Arguments

tri	a character string dataframe (or matrix) specifying triplets in which the first column is modulator,the second is effector,the third is target.
exp.sur	a dataframe specifying expression and survival information.Its rownames are sample names.Its colnames are factor names in triplets and survival tag (see example data in details).
train	a character string vector specifying train sample names.
test	a character string vector specifying test sample names.
index	a numeric vector (default 1) reprsenting rowindex of triplets analyed.

Details

Note:All the arguments without default value must be assigned.

For the output,a triplet corresponds 6 plots,3 for train samples and 3 for test samples.For train sameples,one plot is to show expression of triplet,another is to show risk scores,the other is comparison of survivorship curve between highrisk and lowrisk sameples.

Value

A dataframe whose rows represent different triplets while columns represent 15 kinds of information on the triplet. The columns are:

• modulator the modulator name;

• effector the effector name;

• target the target name;

• coef_modulator the coxph coefficient of modulator;

• p_modulator the significance of coef_lnc;

• coef_effector the coxph coefficient of effector;

• p_effector the significance of coef_effector;

• coef_target the coxph coefficient of target;

• p_target the significance of coef_target;

• N_train1 the sample number with low risk score in train sameples;

• N_train2 the sample number with high risk score in train sameples;

• dif_train the significance of survival difference between low/high risk sameples in train samples;

• N_test1 the sample number with low risk score in test sameples;

• N_test2 the sample number with high risk score in test sameples;

• dif_test the significance of survival difference between low/high risk sameples in test samples;

See Also

coxph,Surv,survdiff

Examples

#a triplet
tri.surv(tri=datatests[["tri_bs"]],exp.sur=datatests[["exp_sur"]],
         train=datatests[["train"]],test=datatests[["test"]])
#two triplets(or more)
tri.surv(tri=datatests[["tri_bs"]],exp.sur=datatests[["exp_sur"]],
         train=datatests[["train"]],test=datatests[["test"]],
		 index=c(1,2))

LncMod documentation built on May 2, 2019, 9:33 a.m.