Last updated: 2020-01-28

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Knit directory: 20170327_Psen2S4Ter_RNASeq/

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File Version Author Date Message
Rmd 3a9933c Steve Ped 2020-01-28 Finished Enrichment analysis on MutVsWt
html b086aff Steve Ped 2020-01-26 Added first step of enrichment analysis
Rmd ba189be Steve Ped 2020-01-26 Corrected packages
html 96d8cc7 Steve Ped 2020-01-25 Compiled after data export & added compression to output
Rmd 10a285b Steve Ped 2020-01-22 Expanded description in index and tried reusing an image
html 10a285b Steve Ped 2020-01-22 Expanded description in index and tried reusing an image
html b096ad9 Steve Ped 2020-01-21 Recompiled index
Rmd 01512da Steve Ped 2020-01-21 Added initial DE analysis to index
Rmd fbb6242 Steve Ped 2020-01-21 Paused DE analysis
html fbb6242 Steve Ped 2020-01-21 Paused DE analysis
html f154205 Steve Ped 2020-01-20 Got rid of pointless warning
Rmd bc12101 Steve Ped 2020-01-20 Added bash pipeline
html bc12101 Steve Ped 2020-01-20 Added bash pipeline
html f65bf66 Steve Ped 2020-01-20 Removed License & updated text for PCA
Rmd 39d0381 Steve Ped 2020-01-20 Finished QC
html 39d0381 Steve Ped 2020-01-20 Finished QC
Rmd acb4f8a Steve Ped 2020-01-19 Start workflowr project.

library(tidyverse)
library(tidygraph)
library(ggraph)
samples <- read_csv("data/samples.csv") %>%
    distinct(sampleName, .keep_all = TRUE) %>%
    dplyr::select(sample = sampleName, sampleID, genotype) %>%
    mutate(genotype = factor(genotype, levels = c("WT", "Het", "Hom")))

This dataset is an analysis of RNASeq data from a 3-way comparison of WT zebrafish with Heterozygous mutants (psen2S4Ter/+) and Homozygous mutants psen2S4Ter/S4Ter. The psen2S4Ter mutant allele is expected to be a premature termination of the psen2 gene, but instead an alternate downstream start site resulted in a near full-length transcript with significant similarity to a conventional Early Onset Familial Alzhemier’s Disease mutation.

The expected comparisons are shown below:

create_ring(3) %>% 
  mutate(
    name = paste0(levels(samples$genotype), "\n(n = 4)"),
    name = factor(name, levels = name)
  ) %>% 
  activate(edges) %>%
  mutate(comparison = c("Het Vs WT", "Hom Vs Het", "Hom Vs WT")) %>% 
  ggraph(layout = "kk") + 
  geom_edge_link2(
    aes(label = comparison),
    angle_calc = "along",
    label_dodge = unit(0.02, "npc"),
    start_cap = circle(0.09, "npc"),
    end_cap = circle(0.09, "npc"),
    label_size = 5,
    arrow = arrow(
      length = unit(0.06, "npc"),
      ends = "both", 
      type = "closed"
    )
  ) +
  geom_node_label(
    aes(label = name, colour = name),
    size = 5,
    fill = rgb(1,1,1,0.7),
    label.padding = unit(0.4, "lines")
  ) + 
  scale_y_continuous(expand = expand_scale(0.1)) +
  scale_x_continuous(expand = expand_scale(0.1)) +
  theme_void() +
  theme(
    legend.position = "none"
  ) 

Version Author Date
10a285b Steve Ped 2020-01-22

All samples were female, 6 months old and raised in the same tank as a family, to minimise variability. This age represents sexual maturity and is expected to model a pre-symptomatic brain. Fish were all killed and genotyped by tail-clipping on 07-07-2016.

RNAseq was performed on total RNA (i.e. ribo-reduced) from whole brain tissue, with \(n=4\) samples in each group. Sequencing was performed by the sequencing facility at the Centre for Cancer Biology in Adelaide, using an Illimuna NextSeq. Reads were provided in as paired-end, 150bp reads.

  1. Bash Pipeline
  2. Quality Assesment
  3. Differential Expression Analysis
  4. Enrichment Analysis
    1. Mutant Vs Wild Type

devtools::session_info()
─ Session info ───────────────────────────────────────────────────────────────
 setting  value                       
 version  R version 3.6.2 (2019-12-12)
 os       Ubuntu 18.04.3 LTS          
 system   x86_64, linux-gnu           
 ui       X11                         
 language en_AU:en                    
 collate  en_AU.UTF-8                 
 ctype    en_AU.UTF-8                 
 tz       Australia/Adelaide          
 date     2020-01-28                  

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