Tantalus
An R package for exploration of Serratus data.
Upgrade in Progress
We are currently upgrading to a new database server. Some functions may be broken. Please open an issue if a problem arises.
Installation
To install directly from the repo:
install.packages("devtools")
library(devtools)
install_github("serratus-bio/tantalus")
(Optional) For more efficient data-access, install aws-cliand input your credentials with aws-cli. Then add the system environmental variables from your R workspace, be sure to use us-east-1.
Sys.setenv(
"AWS_ACCESS_KEY_ID" = "my_public_key",
"AWS_SECRET_ACCESS_KEY" = "my_secret_key",
"AWS_DEFAULT_REGION" = "us-east-1"
)
Note, if you install tantalus with R version <3.6.0, then you first need to install older version of pbkrtest:
packageurl <- "http://cran.r-project.org/src/contrib/Archive/pbkrtest/pbkrtest_0.4-7.tar.gz"
install.packages(packageurl, repos=NULL, type="source")
Usage example
To load data with tantalus you should import RPostgresSQL and dbplyr packages (the login details might change; in this case check the following link):
library("tantalus")
library("dbplyr")
library("RPostgres")
# Connect to Serratus Database
drv <- DBI::dbDriver("PostgreSQL")
con <- DBI::dbConnect(drv,
user="public_reader",
password="serratus",
host="serratus-aurora-20210406.cluster-ro-ccz9y6yshbls.us-east-1.rds.amazonaws.com",
port=5432,
dbname="summary")
# Retrieve nucleotide family table, and Coronaviridae family
# specific columns
cov.nt <- readDfSQL(con,
table = "nfamily",
family = "Coronaviridae",
columns = c('run_id', 'score', 'percent_identity', 'family_name'),
score = 24,
dataframe = T)
# Retrieve a sub-set of SRA by accessions
sra.accessions <- c("SRR10144611", "SRR6906297", "SRR6906298", "SRR6906299",
"SRR6906300", "SRR6906303", "SRR3229029", "SRR3229077",
"SRR3229078", "SRR3229081")
cov.nt.sra <- readDfSQL(con,
table = "nfamily",
family = "Coronaviridae",
sras = sra.accessions,
columns = c('run_id', 'score', 'percent_identity', 'family_name'),
dataframe = T)
# Retrieve rdrp-search results for Coronaviridae
cov.rdrp <- readDfSQL(con,
table = "rfamily",
family = "Coronaviridae-1",
columns = c('run_id', 'score', 'percent_identity', 'family_name'),
score = 24,
dataframe = T)
Plot examples:
# Plot Nucleotide Identity vs. Abundance histogram with identification scores
nt.hist <- pctidInScoreIntervals(cov.nt, family_name = "Coronaviridae", title="Coronaviridae",
scale_log = F, bin_scores = T)
nt.hist
#plot pctid histogram with family score intervals
score.dist <- scoreInPctidIntervals(cov.nt, title="Coronaviridae",
scale_log = F, bin_percent = T)
score.dist
# Plot RdRP Identity vs. Abundance histogram with identification scores
rdrp.hist <- pctidInScoreIntervals(cov.rdrp, family_name = "Coronaviridae-1", title="Coronaviridae",
scale_log = F, bin_scores = T, nucleotide = F)
rdrp.hist
# This data can be explored at a granular level
cov.rdrp[(cov.rdrp$percent_identity < 60), ]run_id score percent_identity family_name
1765 SRR10221771 100 57 Coronaviridae-1
1922 SRR10402288 100 54 Coronaviridae-1
1923 SRR10402289 100 54 Coronaviridae-1
1924 SRR10402291 100 54 Coronaviridae-1
1926 SRR10481990 42 50 Coronaviridae-1
1931 SRR10481992 42 50 Coronaviridae-1
4271 SRR12184956 100 59 Coronaviridae-1
5327 SRR12532037 24 50 Coronaviridae-1
8220 SRR5512543 43 51 Coronaviridae-1
8340 SRR6233344 29 55 Coronaviridae-1
...