ASV data
Below we will use the provided ASV data to combine two data frames and perform some typical calculations.
1 Compile ASV and metadata
library(tidyverse)
── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ──
✔ ggplot2 3.4.1 ✔ purrr 1.0.1
✔ tibble 3.1.8 ✔ dplyr 1.1.0
✔ tidyr 1.3.0 ✔ stringr 1.5.0
✔ readr 2.1.2 ✔ forcats 0.5.2
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag() masks stats::lag()
# head(metadata)
<- asv_table %>%
asv_long pivot_longer(starts_with("Gorda"), names_to = "SAMPLEID") %>%
left_join(metadata %>% select(SAMPLEID = SAMPLE, everything()))
Joining with `by = join_by(SAMPLEID)`
# View(asv_long)
2 Get temperature data from data frame
Isolate samples that have a temperature greater than 15 C.
%>%
asv_long filter(temp > 15)
# A tibble: 42,039 × 10
FeatureID Taxon SAMPL…¹ value VENT SITE Sampl…² SAMPL…³ DEPTH temp
<chr> <chr> <chr> <int> <chr> <chr> <chr> <chr> <chr> <dbl>
1 000562094e0ee78d… Euka… GordaR… 0 Cand… Gord… Sample Vent 2730 79
2 000562094e0ee78d… Euka… GordaR… 0 Sir … Gord… Sample Vent 2732 72
3 000562094e0ee78d… Euka… GordaR… 0 Cand… Gord… Sample Vent 2730 79
4 000562094e0ee78d… Euka… GordaR… 0 Sir … Gord… Sample Vent 2732 72
5 000562094e0ee78d… Euka… GordaR… 0 Mt E… Gord… Sample Vent 2707 40
6 000562094e0ee78d… Euka… GordaR… 0 Mt E… Gord… Sample Vent 2707 40
7 000562094e0ee78d… Euka… GordaR… 0 Sir … Gord… Sample Vent 2732 72
8 000562094e0ee78d… Euka… GordaR… 0 Mt E… Gord… Sample Vent 2707 40
9 000562094e0ee78d… Euka… GordaR… 0 Cand… Gord… Sample Vent 2730 79
10 0009645516609bda… Euka… GordaR… 0 Cand… Gord… Sample Vent 2730 79
# … with 42,029 more rows, and abbreviated variable names ¹SAMPLEID,
# ²Sample_or_Control, ³SAMPLETYPE
# Make a list of vent sites from Gorda Ridge that had a temperature greater than 15 C.
What are the average temperatures at the vent, plume, versus background samples? And how many of each sample are there?
%>% asv_long
3 Parse taxon names
%>% asv_long
4 Calculate relative abundance
Create a table with sequence counts and ASV counts by supergroup.
%>% asv_long
4.1 Make a bar plot
%>% asv_long