Fix in vignette

Author: ashishjain1988

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: TissueEnrich
 Type: Package
 Title: A tool to calculate tissue-specific gene enrichment
-Version: 1.0.3
+Version: 1.0.5
 Authors@R: c(person("Ashish Jain",
         email="jain@iastate.edu",
         role=c("aut", "cre")), person("Geetu Tuteja",

vignettes/TissueEnrich.Rmd

@@ -94,7 +94,7 @@ TissueEnrich now enables users to provide the background genes for carrying out
 $$ P(X \gt k) = \sum\limits_{i=k+1}^n \frac{{{K_b}\choose{i}} {{N_b-K_b}\choose{n-i}}}{{{N_b}\choose{n}}} $$
 and the fold-change is calculated as:
 $$ Fold-change =\left( \frac{k}{n} \right)/\left( \frac{K_b}{N_b} \right) $$
-Where, $N_b$ is the total number of bacground genes, $K_b$ is the total number of tissue-specific genes for a tissue in background genes, n is the number of genes in the input gene set, k is the number of tissue-specific genes in the input gene set. The p-values can be corrected for multiple hypothesis testing using the Benjamini & Hochberg correction by setting `multiHypoCorrection = TRUE` (It is `TRUE` by default). If the background gene set is not provided all the genes will be used as background.
+Where, $N_b$ is the total number of background genes, $K_b$ is the total number of tissue-specific genes for a tissue in background genes, n is the number of genes in the input gene set, k is the number of tissue-specific genes in the input gene set. The p-values can be corrected for multiple hypothesis testing using the Benjamini & Hochberg correction by setting `multiHypoCorrection = TRUE` (It is `TRUE` by default). If the background gene set is not provided all the genes will be used as background.
 
 ## Example: Tissue-specific gene enrichment
 This example uses trophectoderm (TE) specific genes identified from single cell RNA-Seq analyses, performed on human blastocysts on days 5, 6, and 7 of preimplantation development [@Petropoulos2016]. The single cells are assigned to either the inner cell mass (epiblast plus emerging extraembryonic endoderm) or the TE using PCA. After that, a list of 100 TE-specific genes was generated using differential gene expression analysis [@Petropoulos2016]. We used those 100 genes as the input gene set and carried out tissue-specific gene enrichment using the tissue-specific genes defined by the HPA dataset.