Gautier bosc2010 pythonbioconductor

Bioconductor with Python, What else ?ISMB / BOSC

Laurent Gautier [laurent@cbs.dtu.dk]

DMAC / CBS

July 10th, 2010

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Disclaimer• This is not about the comparative merits of scripting

languages• This is about being able to access natively libraries

implemented in a different language

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About Bioconductor

• Set of open-source packages for R• Started circa 2002 with a focus on microarrays• Rooted in statistics, data analyis, and visualization• Several hundred packages, addresses NGS, HTS, flow

cytometry, protein-protein interactions, . . .• Biannual releases• Presence on the publication circuit ( > 2, 300 citations for

the BioC publication, > 600 for limma, > 500 for affy )

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About Python

• Simple and clear all-purpose scripting language• Sometimes used in introductions to programming• Popular for agile development• Bioinformatics libraries:

• biopython (libraries for bioinformatics)• galaxy (web front-end to pipelines)• PyCogent, pygr, bx-python (biological sequences-oriented)

• Large selection of libraries:• Web development: Zope, Django, Google App Engine• Scientific computing: Scipy / Numpy• Cloud computing: Disco, execnet• Interface with C: ctypes, Cython

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A view on R/bioconductor and Python in bioinformatics

Bioinformaticsdata

Automation

Storage /Retrieval

SamplesMicroarray

NGS

Annotation

Flow-cytometry,

proteomics,other

assays. . .

R/BioconductorStatisticalanalysis

Visualization

Interactiveprogram-

ming

Python

Non-interactive

abilitiesData

storage /retrieval

Web

Algorithmdevelopment

Scientificcomputing

Python is an all-purpose scriptinglanguage.

Communities

ComputerScientists

Physicists

Biologists

Statisticians

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Bioinformaticsdata

Automation

Storage /Retrieval

SamplesMicroarray

NGS

Annotation

Flow-cytometry,

proteomics,other

assays. . .

R/BioconductorStatisticalanalysis

Visualization

Interactiveprogram-

ming

Python

Non-interactive

abilitiesData

storage /retrieval

Web

Algorithmdevelopment

Scientificcomputing

Python is an all-purpose scriptinglanguage.

Communities

ComputerScientists

Physicists

Biologists

Statisticians

Bioinformaticsdata

Automation

Storage /Retrieval

SamplesMicroarray

NGS

Annotation

Flow-cytometry,

proteomics,other

assays. . .

R/BioconductorStatisticalanalysis

Visualization

Interactiveprogram-

ming

Python

Non-interactive

abilitiesData

storage /retrieval

Web

Algorithmdevelopment

Scientificcomputing

Python is an all-purpose scriptinglanguage.

Communities

ComputerScientists

Physicists

Biologists

Statisticians

Running R code from Python (an example)AimRunning edgeR from Python

MethodRobinson MD, McCarthy DJ and Smyth GK (2010). edgeR:a Bioconductor package for differential expression analysisof digital gene expression data. Bioinformatics 26, 139-140

DataControl Treated

lane1 lane2 lane3 lane4 lane5 lane6 lane8ENSG00000230758 0 0 1 0 0 0 0ENSG00000182463 0 2 4 1 5 5 0ENSG00000124208 82 124 102 136 90 120 40ENSG00000230753 0 0 0 3 0 0 0ENSG00000224628 7 8 8 18 8 7 1ENSG00000125835 138 209 227 295 281 220 54ENSG00000125834 25 31 48 56 67 61 15ENSG00000197818 17 27 16 26 41 39 9ENSG00000243473 0 0 0 2 0 0 0ENSG00000226325 0 0 2 0 3 1 0

. . . . . . . . . . . . . . . . . . . . . . . .

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from rpy2.robjects.packages import importrfrom bioc import edger

base = importr(’base’)

summarized = edger.DGEList.new(counts = counts,lib_size = base.colSums(counts),group = grp)

disp = edger.estimateCommonDisp(summarized)

tested = edger.exactTest(disp)

results = edger.topTags(tested)

logConc logFC PValue FDRENSG00000127954 -31.03 37.97 0.00 0.00ENSG00000151503 -12.96 5.40 0.00 0.00ENSG00000096060 -11.78 4.90 0.00 0.00ENSG00000091879 -15.36 5.77 0.00 0.00ENSG00000132437 -14.15 -5.90 0.00 0.00ENSG00000166451 -12.62 4.57 0.00 0.00ENSG00000131016 -14.80 5.27 0.00 0.00ENSG00000163492 -17.28 7.30 0.00 0.00ENSG00000113594 -12.25 4.05 0.00 0.00ENSG00000116285 -13.02 4.11 0.00 0.00

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R code / Python codelibrary(edgeR)summarized <- DGEList(counts = counts,

lib.size = colSums(counts),group = grp)

disp <- estimateCommonDisp(summarized)

from rpy2.robjects.packages import importrbase = importr(’base’)from bioc import edger

summarized = edger.DGEList.new(count = counts,lib_size = base.colSums(counts),group = grp)

disp = edger.estimateCommonDisp(summarized)

Note:• explicit in searching through namespaces• call R functions as native Python functions• use R objects as Python objects

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Bioconductor library IRanges

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Bioconductor library Biostrings

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Separate communities

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Bilingual community

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Interpreters/Translators

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Cost of translation

R package Python modulelines of code

AnnotationDbi 168 annotationdbi.pyBiobase 341 biobase.pyBiostrings 591 biostrings.pyBSgenome 112 bsgenome.pyedgeR 107 edger.pyGEOquery 102 geoquery.pyGGbase 104 ggbase.pyGGtools 77 ggtools.pygoseq 43 goseq.pyGSEABase 149 gseabase.pyIRanges 295 iranges.pyShortRead 301 shortread.py

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R within Python• R is running as embedded into Python• R objects remain in the R workspace, but can be accessed

from Python• Python-level shells to access the R objects• The rpy2 package is used to achieve so

biostrings = importr(’Biostrings’)class AAString(XString):

_aastring_constructor = biostrings.AAString

@classmethoddef new(cls, x):

""" :param x: a string of amino-acids """res = cls(cls._aastring_constructor(conversion.py2ri(x)))_setExtractDelegators(res)return res

aas = AAString("PROTEIN")

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What is needed to continue

More interpreters/translators• Many bioconductor packages.• Keep up-to-date existing translations.

Keeping up-to-date• Frequent API-breaking changes in bioconductor• Taylored interfaces increase maintenance• Meta-programming and reflexivity can alleviate this

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Example with meta-programming:

class AssayData(rpy2.robjects.methods.RS4):""" Abstract class. That class in a ClassUnionRepresentationin R, that a is way to create a parent class for existingclasses. This is currently not modelled in Python. """__rname__ = ’AssayData’__metaclass__ = rpy2.robjects.methods.RS4_Type

__accessors__ = ((’featureNames’, ’Biobase’, ’featurenames’,True, ’maps Biobase::featureNames’),(’sampleNames’, ’Biobase’, ’samplenames’,True, ’maps Biobase::samplenames’),(’storageMode’, ’Biobase’, ’storagemode’,True, ’maps Biobase::storageMode’))

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Example of a complete applicationA web-server to run EdgeR.

from bottle import route, runfrom my_edger import get_toptags, make_results_page@route(’/’)def index():

return ’’’<html> <body><form action="/edger" method="post" enctype="multipart/form-data"><input type="file" name="data" /> </form></body> </html>’’’

@route(’/edger’, method=’POST’)def run_edger():

data = request.files.get(’data’)if data:

counts, grp = read_count_data(data.file.name)top_tags = get_toptags(counts, grp)return make_result_page(top_tags)

else:abort(404, "Invalid count file.")

run(host=’localhost’, port=8080)

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Acknowledgements• Users, and communities from R, Bioconductor, Python,

Biopython• (Vincent Davis, Nicolas Rapin, Brad Chapman)

URLshttp://pypi.python.org/pypi/rpy2-bioconductor-extensions/

http://bitbucket.org/lgautier/rpy2-bioc-extensions

http://packages.python.org/rpy2-bioconductor-extensions/ http://rpy2.sourceforge.net/

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