Hypoxia Response Genes

Last updated: 2020-06-14

Checks: 7 0

Knit directory: Comparative_APA/analysis/

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File	Version	Author	Date	Message
Rmd	17e018c	brimittleman	2020-06-14	add hypoxia test

I want to check if any of the APA factors are differentially responsive in hypoxia conditions. The data comes from Michelles paper, supplemental table 3. (https://elifesciences.org/articles/42374/figures#supp3)

library(tidyverse)

── Attaching packages ────────────────────────────── tidyverse 1.2.1 ──

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✔ tibble  2.1.1       ✔ dplyr   0.8.0.1
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✔ readr   1.3.1       ✔ forcats 0.3.0

── Conflicts ───────────────────────────────── tidyverse_conflicts() ──
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library(ggpubr)

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library(cowplot)


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library(workflowr)

This is workflowr version 1.6.0
Run ?workflowr for help getting started

mkdir ../data/hypoxia

nameID=read.table("../../genome_anotation_data/ensemble_to_genename.txt",sep="\t", header = T, stringsAsFactors = F) %>% rename("genes"=Gene.name) %>% select(-Source_of_gene_name)

Cons=read.table("../data/hypoxia/ConsvResp_elife-42374.txt", col.names = "Gene_stable_ID", stringsAsFactors = F) %>% inner_join(nameID, by="Gene_stable_ID") %>% mutate(Response="Conserved")

NonRes=read.table("../data/hypoxia/NonResp_elife-42374.txt", col.names = "Gene_stable_ID", stringsAsFactors = F) %>% inner_join(nameID, by="Gene_stable_ID") %>% mutate(Response="NoResponse")


HumanRes= read.table("../data/hypoxia/HumanResp_elife-42374.txt", col.names = "Gene_stable_ID", stringsAsFactors = F) %>% inner_join(nameID, by="Gene_stable_ID") %>% mutate(Response="Human")

ChimpRes=read.table("../data/hypoxia/ChimpResp_elife-42374.txt", col.names = "Gene_stable_ID", stringsAsFactors = F) %>% inner_join(nameID, by="Gene_stable_ID") %>% mutate(Response="Chimp")


ResponseGenes=Cons %>% bind_rows(NonRes) %>% bind_rows(HumanRes) %>% bind_rows(ChimpRes) %>% select(genes, Response)

I want to check the response genes implicated in APA and stress response, Sadek et al.

APAFactors=read.table("../data/hypoxia/APAandStressfactors.txt", col.names = "genes", stringsAsFactors = F)

Ask if any of these are in the response:

ResponseAPA=ResponseGenes %>% inner_join(APAFactors, by="genes")

APAFactors_anti=APAFactors %>% anti_join(ResponseGenes, by="genes") %>% mutate(Response="NotReported")

ResponseAPAall=ResponseAPA %>% bind_rows(APAFactors_anti)

ggplot(ResponseAPAall, aes(x=Response, fill=Response)) + geom_bar(stat="count") + theme(legend.position = "none", axis.text.x = element_text(angle = 90)) + scale_fill_brewer(palette = "RdYlBu") + labs(x="",y="genes", title="Hypoxia response for APA factors")

ResponseAPAall %>% filter(Response %in% c("Chimp", "Conserved"))

    genes  Response
1  PABPN1 Conserved
2    SFPQ Conserved
3   CDC73 Conserved
4   MBNL1 Conserved
5   CPSF4 Conserved
6 HNRNPH1 Conserved
7   CPEB1 Conserved
8   SRSF7     Chimp

sessionInfo()

R version 3.5.1 (2018-07-02)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Scientific Linux 7.4 (Nitrogen)

Matrix products: default
BLAS/LAPACK: /software/openblas-0.2.19-el7-x86_64/lib/libopenblas_haswellp-r0.2.19.so

locale:
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 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] workflowr_1.6.0 cowplot_0.9.4   ggpubr_0.2      magrittr_1.5   
 [5] forcats_0.3.0   stringr_1.3.1   dplyr_0.8.0.1   purrr_0.3.2    
 [9] readr_1.3.1     tidyr_0.8.3     tibble_2.1.1    ggplot2_3.1.1  
[13] tidyverse_1.2.1

loaded via a namespace (and not attached):
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 [7] yaml_2.2.0         rlang_0.4.0        later_0.7.5       
[10] pillar_1.3.1       glue_1.3.0         withr_2.1.2       
[13] RColorBrewer_1.1-2 modelr_0.1.2       readxl_1.1.0      
[16] plyr_1.8.4         munsell_0.5.0      gtable_0.2.0      
[19] cellranger_1.1.0   rvest_0.3.2        evaluate_0.12     
[22] labeling_0.3       knitr_1.20         httpuv_1.4.5      
[25] broom_0.5.1        Rcpp_1.0.4.6       promises_1.0.1    
[28] scales_1.0.0       backports_1.1.2    jsonlite_1.6      
[31] fs_1.3.1           hms_0.4.2          digest_0.6.18     
[34] stringi_1.2.4      grid_3.5.1         rprojroot_1.3-2   
[37] cli_1.1.0          tools_3.5.1        lazyeval_0.2.1    
[40] crayon_1.3.4       whisker_0.3-2      pkgconfig_2.0.2   
[43] xml2_1.2.0         lubridate_1.7.4    assertthat_0.2.0  
[46] rmarkdown_1.10     httr_1.3.1         rstudioapi_0.10   
[49] R6_2.3.0           nlme_3.1-137       git2r_0.26.1      
[52] compiler_3.5.1

Hypoxia Response Genes

Briana Mittleman

6/14/2020