Leibniz-Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH opm – an R package to analyse OmniLog Phenotype MicroArray data Dr. Johannes Sikorski, Dr. Lea Vaas, Dr. Markus Göker Leibniz-Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH www.dsmz.de An introduction to opm
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How to use opm [Kompatibilitätsmodus]€¦ · Leibniz-Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH Batch-export of OmniLog kinetic data as CSV files
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Leibniz-Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH
opm – an R package to analyse
OmniLog Phenotype MicroArray data
Dr. Johannes Sikorski, Dr. Lea Vaas, Dr. Markus Göker
Leibniz-Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH
www.dsmz.de
An introduction to opm
Leibniz-Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH
You have numerous OmniLog Phenotype MicroArray data
and you want to explore them full-fledged and quantitatively
into diverse directions of analysis frameworks.
• of closely related organisms or cell lines
• of numerous well-defined mutants
• obtained under diverse physiological
test conditions
www.biolog.com
Leibniz-Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH
� to organize your PM data, curve parameters and metadata
� to subset and query your data
� graphical display of raw kinetics or aggregated curve parameters
� exploit the full statistics implemented in R
� export to third-party software using YAML
opm: Tools for analysing OmniLog(R) Phenotype Microarray data
enables you:
Leibniz-Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH
http://www.rstudio.org/
RStudio™ is a free and open source
integrated development environment (IDE) for R.
http://www.r-project.org/
R is a free software environment for statistical computing and graphics.
Feel free to contact us in case of any questions regarding usage of opm.
Leibniz-Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH
opm
enables you:
� to organize your PM data, curve parameters and metadata
� to subset and query your data
� graphical display of raw kinetics or aggregated curve parameters
� exploit the full statistics implemented in R
� export to third-party software using YAML
Leibniz-Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH
OPM
organizes your PM data in OPMS objects:
Plate 1 Plate 2 Plate 3
Plate 4 Plate 5 Plate 6
Plate 7 Plate 8 Plate 9
Plate 1 Plate 2 Plate 3
Plate 4 Plate 5 Plate 6
Plate 7 Plate 8 Plate 9
Plate 1 Plate 2 Plate 3
Plate 4 Plate 5 Plate 6
Plate 7 Plate 8 Plate 9
raw kinetic data
aggregated curve
parameters
metadata
An OPMS object stores:
Example: a set of 9 PM plates of the same
plate type
The size of the OPMS object is only limited by the amount of RAM memory
Hour00.0000.2500.50.30.00.60.00
lysin353337.
102.
328Hour
inte
nsity
per well:raw kinetic data
metadata Plate 3
Taxonomy Bacillus subtilis.habitat soilsampling place GPS coord.sampling date 2011-06-15sampling season summerhabitat [°C] 27.sporulation yes.PCR (gene xyz) positive.... as much and what you wish...
per plate:any metadata of interest to the user
lysin
mu 15.559078 lambda 5.798210A 305.989319AUC 23308.269348mu CI95 low 3.803466lambda CI95 low 1.080333A CI95 low 305.642353AUC CI95 low 23125.092442mu CI95 high 140.841704lambda CI95 high 11.819251A CI95 high 306.986123AUC CI95 high 23411.648024
per well:aggregated curve parameters, confidence-intervals from bootstrapping
Lag = lambda, Slope = mu, Max = A, Area Under the Curve = AUC
Leibniz-Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH
Leibniz-Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH
Leibniz-Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH
Batch-export of OmniLog kinetic data as CSV files for opm
(1) Change WINDOWS software language settings to American English.
Leibniz-Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH
�
�
Leibniz-Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH
OPM
organizes your PM data in OPMS objects:
Plate 1 Plate 2 Plate 3
Plate 4 Plate 5 Plate 6
Plate 7 Plate 8 Plate 9
Plate 1 Plate 2 Plate 3
Plate 4 Plate 5 Plate 6
Plate 7 Plate 8 Plate 9
Plate 1 Plate 2 Plate 3
Plate 4 Plate 5 Plate 6
Plate 7 Plate 8 Plate 9
raw kinetic data
aggregated curve
parameters
metadata
An OPMS object stores:
Example: a set of 9 PM plates of the same
plate type
You need to provide
the metadata
separately
Hour00.0000.2500.50.30.00.60.00
lysin353337.
102.
328Hour
inte
nsity
per well:raw kinetic data
metadata Plate 3
Taxonomy Bacillus subtilis.habitat soilsampling place GPS coord.sampling date 2011-06-15sampling season summerhabitat [°C] 27.sporulation yes.PCR (gene xyz) positive.... as much and what you wish...
per plate:any metadata of interest to the user
lysin
mu 15.559078 lambda 5.798210A 305.989319AUC 23308.269348mu CI95 low 3.803466lambda CI95 low 1.080333A CI95 low 305.642353AUC CI95 low 23125.092442mu CI95 high 140.841704lambda CI95 high 11.819251A CI95 high 306.986123AUC CI95 high 23411.648024
per well:aggregated curve parameters, confidence-intervals from bootstrapping
Lag = lambda, Slope = mu, Max = A, Area Under the Curve = AUC
Leibniz-Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH
We use as identifier the Setup Time and Position of the plate in the reader.
Good news:
opm allows to export these informations as a start for the metadata file
using the function:
collect_template()
You need to provide the metadata separately
One Problem Arises:
Imagine, you have numerous plates with numerous metadata to each plate.
How can we make sure that the metadata are matched CORRECTLY to the
specific raw kinetic data?
Solution:
We need an identifier that perfectly matches metadata to raw kinetic data.
Leibniz-Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH
collect_template()
data frame
add further metadata columns
metadata <- collect_template(files, include = "*Example_?.csv.xz")
Unique identifier to merge metadata and raw kinetic data
Leibniz-Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH
collect_template()
data frame
add further metadata columns
CSV file (or *.txt, *.dat)
add further metadata columns
in a spreadsheed application
collect_template(files, include = "*Example_?.csv.xz", outfile = "template.csv")
note the FORMAT:
columns are tab separated, fields protected by quotation marks
Leibniz-Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH
collect_template()
data frame
add further metadata columns
CSV file (or *.txt, *.dat)
add further metadata columns
save tab separated and use
quotation marks as field protector
load file into R environment using
to_metadata()
Leibniz-Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH