SQL, noSQL or no database at all?Are databases still a core skill?

Neil Saunders

COMPUTATIONAL INFORMATICSwww.csiro.au

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alternative title: should David Lovell learn databases?

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actual recent email request

Hi Neil,

I was wondering if you could help me with something. I am trying to puttogether a table but it is rather slow by hand. Do you know if you canhelp me with this task with a script? If it is too much of your time,don’t worry about it. Just thought I’d ask before I start.

The task is:

The targets listed in A tab need to be found in B tab then the entire rowcopied into C tab. Then the details in column C of C tab then need to bematched with the details in D tab so that the patients with the mutationsare listed in row AG and AH of C tab.

Again, if this isn’t an easy task for you then don’t worry about it.

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sounds like a database to me (c. 2004)

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database design is a profession in itself

-- KEGG_DB schema

CREATE TABLE ec2go (ec_no VARCHAR(16) NOT NULL, -- EC number (with "EC:" prefix)go_id CHAR(10) NOT NULL -- GO ID

);CREATE TABLE pathway2gene (pathway_id CHAR(8) NOT NULL, -- KEGG pathway long IDgene_id VARCHAR(20) NOT NULL -- Entrez Gene or ORF ID

);CREATE TABLE pathway2name (path_id CHAR(5) NOT NULL UNIQUE, -- KEGG pathway short IDpath_name VARCHAR(80) NOT NULL UNIQUE -- KEGG pathway name

);

-- Indexes.CREATE INDEX Ipathway2gene ON pathway2gene (gene_id);

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know your ORM from your MVC(do you DSL?)

http://en.wikipedia.org/wiki/Model%E2%80%93view%E2%80%93controller

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my one tip for today: use ORM= object relational mapping

#!/usr/bin/ruby

require ’sequel’

# connect to UCSC Genomes MySQL serverDB = Sequel.connect(:adapter => "mysql", :host => "genome-mysql.cse.ucsc.edu",

:user => "genome", :database => "hg19")

# instead of "SELECT count(*) FROM knownGene"DB.from(:knownGene).count

# => 82960

# instead of "SELECT name, chrom, txStart FROM knownGene LIMIT 1"DB.from(:knownGene).select(:name, :chrom, :txStart).first

# => {:name=>"uc001aaa.3", :chrom=>"chr1", :txStart=>11873}

# instead of "SELECT name FROM knownGene WHERE chrom == ’chrM’"DB.from(:knownGene).where(:chrom => "chrM").all

# => [{:name=>"uc004coq.4"}, {:name=>"uc022bqo.2"}, {:name=>"uc004cor.1"}, {:name=>"uc004cos.5"},# {:name=>"uc022bqp.1"}, {:name=>"uc022bqq.1"}, {:name=>"uc022bqr.1"}, {:name=>"uc031tga.1"},# {:name=>"uc022bqs.1"}, {:name=>"uc011mfi.2"}, {:name=>"uc022bqt.1"}, {:name=>"uc022bqu.2"},# {:name=>"uc004cov.5"}, {:name=>"uc031tgb.1"}, {:name=>"uc004cow.2"}, {:name=>"uc004cox.4"},# {:name=>"uc022bqv.1"}, {:name=>"uc022bqw.1"}, {:name=>"uc022bqx.1"}, {:name=>"uc004coz.1"}]

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don’t want to CREATE? you still might want to SELECT

Question: How to map a SNP to a gene around +/- 60KB ?

I am looking at a bunch of SNPs. Some of them are part of genes,but other are not. I am interested to look up +60KB or -60KB ofthose SNPs to get details about some nearby genes. Please shareyour experience in dealing with such a situation or thoughts onany methods that can do this. Thanks in advance.

http://www.biostars.org/p/413/

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example SELECT

mysql --user=genome --host=genome-mysql.cse.ucsc.edu -A -D hg19 -e ’

selectK.proteinID, K.name, S.name,S.avHet, S.chrom, S.chromStart,K.txStart, K.txEnd

from snp130 as Sleft join knownGene as K on(S.chrom = K.chrom and not(K.txEnd + 60000 < S.chromStart or

S.chromEnd + 60000 < K.txStart))where

S.name in ("rs25","rs100","rs75","rs9876","rs101")

’

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example SELECT result

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let’s talk about noSQL

http://www.infoivy.com/2013/07/nosql-database-comparison-chart-only.html

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(potentially) a good fit for biological data

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many data sources are “key-value ready”(or close enough)

http://togows.dbcls.jp/entry/pathway/hsa00030/genes.json

[{

"2821": "GPI; glucose-6-phosphate isomerase [KO:K01810] [EC:5.3.1.9]","2539": "G6PD; glucose-6-phosphate dehydrogenase [KO:K00036] [EC:1.1.1.49]","25796": "PGLS; 6-phosphogluconolactonase [KO:K01057] [EC:3.1.1.31]",..."5213": "PFKM; phosphofructokinase, muscle [KO:K00850] [EC:2.7.1.11]","5214": "PFKP; phosphofructokinase, platelet [KO:K00850] [EC:2.7.1.11]","5211": "PFKL; phosphofructokinase, liver [KO:K00850] [EC:2.7.1.11]"

}]

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schema-free: save first, worry later(= agile)

#!/usr/bin/rubyrequire "mongo"require "json/pure"require "open-uri"

db = Mongo::Connection.new.db(’kegg’)col = db.collection(’genes’)j = JSON.parse(open("http://togows.dbcls.jp/entry/pathway/hsa00030/genes.json").read)

j.each do |g|gene = Hash.newg.each_pair do |key, val|gene[:_id] = keygene[:desc] = valcol.save(gene)

endend

Ruby code to save JSON from the TogoWS REST service

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example application - PMRetractask later if interested

http://pmretract.heroku.com/https://github.com/neilfws/PubMed/tree/master/retractions

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when rows + columns != database

- sometimes a database is overkill

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example 1 - R/IRanges

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example 2 - bedtools

http://bedtools.readthedocs.org/en/latest/

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example 3 - unix join (and the shell in general)

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when are databases good?

- when data are updated frequently

- when multiple users do the updating

- when queries are complex or ever-changing

- as backends to web applications

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when are databases not/less good?

- for basic “set operations”

- for sequence data [1] (?)

[1] no time to discuss BioSQL, GBrowse/Bio::DB::GFF, BioDAS etc.

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so how did I answer that email?

options(java.parameters = "-Xmx4g")library(XLConnect)

wb <- loadWorkbook("˜/Downloads/NGS Target list Tumour for Neil.xlsx")

s1 <- readWorksheet(wb, sheet = 1, startCol = 1, endCol = 1, header = F)s2 <- readWorksheet(wb, sheet = 2, startCol = 1, endCol = 32, header = T)s4 <- readWorksheet(wb, sheet = 4, startCol = 1, endCol = 3, header = T)

# then use gsub, match, %in% etc. to clean and join the data# ...

Read spreadsheet into R using the XLConnect package, then “munge”

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let’s vote!

so, should David learn databases?