DEPTH evaluates the tumor heterogeneity level of each tumor sample based on gene expression profiles Heterogeneity score vignette
This vignette shows an example of how to use the DEPTH algorithm to calculate tumor heterogeneity level in R.
DEPTH evaluates the tumor heterogeneity level of each tumor sample based on gene expression profiles.
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exp: gene expression profiles in both tumor and normal samples (microarray or RNA-Seq data, normalized);
Table 1. RNA expression of input data
Identification | TCGA-A6-2671-11A-01R-A32Z-07 | TCGA-A6-2675-11A-01R-1723-07 | TCGA-A6-2675-01A-02R-1723-07 |
---|---|---|---|
SKAP1 | 6.22 | 4.36 | 6.00 |
TPSB2 | 9.39 | 9.45 | 9.21 |
PLXNB3 | 6.09 | 8.45 | 4.95 |
VAT1L | 7.45 | 7.76 | 6.13 |
VIP | 9.43 | 10.99 | 7.71 |
WNT5B | 7.52 | 7.80 | 6.29 |
ZAP70 | 6.43 | 5.13 | 5.94 |
TNFRSF10C | 3.67 | 3.90 | 5.46 |
ZNF167 | 4.46 | 6.10 | 5.88 |
KIF26B | 3.62 | 4.61 | 7.68 |
STRA6 | 2.26 | 1.08 | 6.57 |
- match: sample type ("tumor" or "normal") in "exp".
Table2. Identification of tumor sample and normal sample
State | Identification |
---|---|
Normal | TCGA-A6-2671-11A-01R-A32Z-07 |
Normal | TCGA-A6-2675-11A-01R-1723-07 |
Tumor | TCGA-A6-2675-01A-02R-1723-07 |
Normal | TCGA-A6-2678-11A-01R-A32Z-07 |
Normal | TCGA-A6-2679-11A-01R-A32Z-07 |
Normal | TCGA-A6-2680-11A-01R-A32Z-07 |
Normal | TCGA-A6-2682-11A-01R-A32Z-07 |
Tumor | TCGA-A6-2682-01A-01R-1410-07 |
Table 1 is an example of "exp" and Table 2 is an example of "match".
Example "exp": gene expression profiles in cholangiocarcinoma from the genomic data commons data portal (https://portal.gdc.cancer.gov/). There are 45 samples (36 tumor and 9 normal samples) and 20,531 genes in "exp". The DEPTH function will output the heterogeneity score for each of the 36 tumor samples as shown in Table 3.
Table 3. heterogeneity score of tumor samples in output data
Samp | heterogeneity score |
---|---|
TCGA-A6-2675-01A-02R-1723-07 | 2.954321 |
TCGA-A6-2682-01A-01R-1410-07 | 4.307523 |
TCGA-A6-2684-01A-01R-1410-07 | 3.916457 |
TCGA-A6-2685-01A-01R-1410-07 | 2.85864 |
You can install the released version of ‘DEPTH’ with:
if (!requireNamespace("devtools", quietly = TRUE))
install.packages("devtools")
devtools::install_github("MLi-lab-Bioinformatics-NJUCM/DEPTH/DEPTH")
exp=read.csv("DEPTH/exp.csv",header=F)
match=read.csv("DEPTH/match.csv")
library(DEPTH)
DEPTH(exp, match)
Mengyuan Li, Zhilan Zhang, Lin Li, Xiaosheng Wang. An algorithm to quantify intratumor heterogeneity based on alterations of gene expression profiles. Communications Biology 2020, 3(1), 505. DOI: https://doi.org/10.1038/s42003-020-01230-7.