DEG_overview: Visualization of pairwise DEG analysis

In Kan-E/rnaseqviewer: Toolkit for automated, systematic, and integrated RNA-seq DEG analysis

Visualization of pairwise DEG analysis

Description

Visualization of pairwise DEG analysis

Usage

DEG_overview(
  Count_matrix,
  DEG_result,
  Species = NULL,
  fdr = 0.05,
  fc = 2,
  basemean = 0
)

Arguments

Count_matrix	Count matrix txt file
DEG_result	result txt file of DEG analysis
Species	Species
fdr	Accepted false discovery rate for considering genes as differentially expressed
fc	the fold change threshold. Only genes with a fold change >= fc and padj <= fdr are considered as significantly differentially expressed.
basemean	basemean threshold

References

T Wu, E Hu, S Xu, M Chen, P Guo, Z Dai, T Feng, L Zhou, W Tang, L Zhan, X Fu, S Liu, X Bo, and G Yu. clusterProfiler 4.0: A universal enrichment tool for interpreting omics data. The Innovation. 2021, 2(3):100141

Guangchuang Yu, Li-Gen Wang, Guang-Rong Yan, Qing-Yu He. DOSE: an R/Bioconductor package for Disease Ontology Semantic and Enrichment analysis. Bioinformatics 2015 31(4):608-609

Hervé Pagès, Marc Carlson, Seth Falcon and Nianhua Li (2020). AnnotationDbi: Manipulation of SQLite-based annotations in Bioconductor. R package version 1.52.0.

Marc Carlson (2020). org.Hs.eg.db: Genome wide annotation for Human. R package version 3.12.0.

Marc Carlson (2020). org.Mm.eg.db: Genome wide annotation for Mouse. R package version 3.12.0.

R. Gentleman, V. Carey, W. Huber and F. Hahne (2021). genefilter: methods for filtering genes from high-throughput experiments. R package version 1.72.1.

Gu, Z. (2016) Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics.

Alboukadel Kassambara (2020). ggpubr: 'ggplot2' Based Publication Ready Plots. R package version 0.4.0. https://CRAN.R-project.org/package=ggpubr

Hadley Wickham, Romain François, Lionel Henry and Kirill Müller (2021). dplyr: A Grammar of Data Manipulation. R package version 1.0.7. https://CRAN.R-project.org/package=dplyr

Examples

library(rnaseqviewer)

data(Row_count_data)
write.table(Row_count_data, file = "Row_count_data.txt", sep = "\t", quote = FALSE)
deseq2("Row_count_data.txt")
DEG_overview(Count_matrix = "Normalized_count_matrix_from_Row_count_data_Cond1-vs-Cond2_DEseq2-BH.txt",
             DEG_result = "result_of_Row_count_data_Cond1-vs-Cond2_DEseq2-BH.txt",
             Species = "human", fc = 1.5)

Kan-E/rnaseqviewer documentation built on May 30, 2022, 10:34 a.m.