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Update to student-edited file locations

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hyginn 2020-09-28 17:49:45 +10:00
parent 744e762dc2
commit 12213b73a4
1 changed files with 47 additions and 26 deletions
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BIN-Storing_data.R
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@ -3,11 +3,13 @@
# Purpose: A Bioinformatics Course:
# R code accompanying the BIN-Storing_data unit
#
# Version: 1.2
# Version: 1.3
#
# Date: 2017-10 - 2020-09
# Author: Boris Steipe (boris.steipe@utoronto.ca)
#
# V 1.3 Made file locations more consistent. All student-edited files
# go into the myScripts directory
# V 1.2 2020 updates. Finally removed stringAsFactors :-)
# V 1.1 Add instructions to retrieve UniProt ID from ID mapping service.
# V 1.0 First live version, complete rebuilt. Now using JSON data sources.
@ -32,26 +34,26 @@
#TOC>
#TOC> Section Title Line
#TOC> -----------------------------------------------------------------------
#TOC> 1 A Relational Datamodel in R: review 59
#TOC> 1.1 Building a sample database structure 99
#TOC> 1.1.1 completing the database 205
#TOC> 1.2 Querying the database 238
#TOC> 1.3 Task: submit for credit (part 1/2) 269
#TOC> 2 Implementing the protein datamodel 291
#TOC> 2.1 JSON formatted source data 317
#TOC> 2.2 "Sanitizing" sequence data 358
#TOC> 2.3 Create a protein table for our data model 380
#TOC> 2.3.1 Initialize the database 382
#TOC> 2.3.2 Add data 394
#TOC> 2.4 Complete the database 414
#TOC> 2.4.1 Examples of navigating the database 441
#TOC> 2.5 Updating the database 473
#TOC> 3 Add your own data 485
#TOC> 3.1 Find a protein 493
#TOC> 3.2 Put the information into JSON files 523
#TOC> 3.3 Create an R script to create your own database 546
#TOC> 3.3.1 Check and validate 569
#TOC> 3.4 Task: submit for credit (part 2/2) 614
#TOC> 1 A Relational Datamodel in R: review 61
#TOC> 1.1 Building a sample database structure 101
#TOC> 1.1.1 completing the database 207
#TOC> 1.2 Querying the database 240
#TOC> 1.3 Task: submit for credit (part 1/2) 271
#TOC> 2 Implementing the protein datamodel 293
#TOC> 2.1 JSON formatted source data 319
#TOC> 2.2 "Sanitizing" sequence data 360
#TOC> 2.3 Create a protein table for our data model 382
#TOC> 2.3.1 Initialize the database 384
#TOC> 2.3.2 Add data 396
#TOC> 2.4 Complete the database 416
#TOC> 2.4.1 Examples of navigating the database 443
#TOC> 2.5 Updating the database 475
#TOC> 3 Add your own data 487
#TOC> 3.1 Find a protein 495
#TOC> 3.2 Put the information into JSON files 525
#TOC> 3.3 Create an R script to create your own database 567
#TOC> 3.3.1 Check and validate 590
#TOC> 3.4 Task: submit for credit (part 2/2) 635
#TOC>
#TOC> ==========================================================================
@ -523,23 +525,42 @@ myDB$taxonomy$species[sel]
# == 3.2 Put the information into JSON files ===============================
# - Next make a copy of the file "./data/MBP1_SACCE.json" in your project
# - Next make a copy of the file "./data/MBP1_SACCE.json" in the "data"
# directory and give it a new name that corresponds to MYSPE - e.g. if
# MYSPE is called "Crptycoccus neoformans", your file should be called
# "MBP1_CRYNE.json"; in that case "MBP1_CRYNE" would also be the
# "name" of your protein. Open the file in the RStudio editor and replace
# all of the MBP1_SACCE data with the corresponding data of your protein.
#
# The UniProt ID may not be discoverable from the NCBI page. To retrieve
# Note: The UniProt ID may not be listed on the NCBI page. To retrieve
# it, navigate to http://www.uniprot.org/mapping/ , paste your RefSeq ID
# into the query field, make sure "RefSeqProtein" is selected for "From"
# and "UniProtKB" is selected for "To", and click "Go". In case this does
# not retrieve a single UniProt ID, contact me.
#
# Save your .json file into your myScripts directory.
#
# Confirm this step:
if (file.exists(sprintf("./myScripts/MBP1_%s.json", biCode(MYSPE)))) {
cat("Excellent - all good to continue.\n")
} else {
stop(sprintf(" The file \"./myScripts/MBP1_%s.json\" does not exist",
biCode(MYSPE)))
}
#
#
# - Do a similar thing for the MYSPE taxonomy entry. Copy
# "./data/refTaxonomy.json" and make a new file named "MYSPEtaxonomy.json".
# Create a valid JSON file with only one single entry - that of MYSPE.
#
# Confirm this step:
if (file.exists(sprintf("./myScripts/%staxonomy.json", biCode(MYSPE)))) {
cat("Excellent - all good to continue.\n")
} else {
stop(sprintf(" The file \"./myScripts/%staxonomy.json\" does not exist",
biCode(MYSPE)))
}
# - Validate your two files online at https://jsonlint.com/
@ -552,14 +573,14 @@ myDB$taxonomy$species[sel]
# source("./scripts/ABC-createRefDB.R")
# - than add the two commands that add your protein and taxonomy data,
# they should look like:
# myDB <- dbAddProtein( myDB, fromJSON("MBP1_<code>.json"))
# myDB <- dbAddTaxonomy( myDB, fromJSON("MYSPEtaxonomy.json"))
# myDB <- dbAddProtein( myDB, fromJSON("./myScripts/MBP1_<MYSPE>.json"))
# myDB <- dbAddTaxonomy( myDB, fromJSON("./myScripts/MYSPEtaxonomy.json"))
#
# - save the file in the ./myScripts/ folder and source() it:
# source("./myScripts/makeProteinDB.R")
# This command needs to be executed whenever you recreate
# the database. In particular, whenver you have added or modified data
# the database. In particular, whenever you have added or modified data
# in any of the JSON files. Later you will add more information ...
# Remember this principle. Don't rely on objects in memory - you might