MANILA is an interactive tool for optimal design and analysis of preclinical in vivo studies

Optimal matching of animals guarantees balanced intervention groups

Matched modelling of intervention effects improves statistical power

Model-based power analysis enables tailoring sufficient sample sizes

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Features

Data input and processing

Various input formats (CSV, TXT, Excel files)

Data transformations (log-transformation, matrix transpose, etc)

Pre-intervention analysis

Computation of dissimilarities and optimal matching

Random group allocation and intervention assignment

Visualizations, i.e. scatterplots, hierarchical clustering and heatmaps

Post-intervention analysis

Mixed-effects modeling (MEM)

Power analysis on a fitted MEM

Installation

To use and tailor the features of the hamlet R-package in your own analysis scripts it can be easily installed locally. The latest version of the package is available at CRAN

Install by invoking, e.g., install.packages("hamlet", dep=TRUE) in an R terminal.

Reference

Laajala TD, Jumppanen M, Huhtaniemi R, Fey V, Kaur A, Knuuttila M, Aho E, Oksala R, Westermarck J, Mäkelä S, Poutanen M, Aittokallio T. (2016). Optimized design and analysis of preclinical intervention studies in vivo. Scientific Reports 6, 30723. doi:10.1038/srep30723 [Free full text at PubMed Central (PMC4969752)]

Input
Select data

Select data

Name for this selection (sub-set) of the data:

Select slice

Select method

Standardize measurements

Name for this selection (sub-set) of the data:

Select distance matrix

Number of members in a group

Advanced options

Click **Match** to proceed!

Please allow the matching process to complete before pressing one of the 'Save' buttons. You can monitor the progress in the bottom right corner of the interface.

Number of generations

Population size

Add dummy variables

Add

Remove dummy variables from data

Yes

Name for this selection (sub-set) of the data:

Select data for randomisation

Advanced options

Select a seed value for RNG:

Click **Randomise** to proceed!

Please allow the randomisation process to complete before pressing continuing. You can monitor the progress in the bottom right corner of the interface.

Select data for boxplot

Data values:

Grouping variable:

Advanced options

Choose color theme:

**Please click **Plot** to generate the first graph!**

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Select distance matrix

Advanced options

Choose color theme:

Download

Select data for mixplot

Select variables:

Download

Mixed-effects modelling

Please select a data table in ‘long’ format, select suitable columns for the analysis and then click Fit to start the analysis!

Selected data frame

Fixed effects

Random effects

ID column

Response column

Time column

Intervention group

Control group

Download report:

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Change line type:

l b

Number of bootstraps per N

Model contains grouping information

Select group

Smooth curve

Legend