TABLE OF CONTENTS

• Introduction
• 1 Creating a plot 
• 2 Selecting data
• 3 Setting parameters
  • 1.1 Bruteforce customization
    • 1.1.1 Parameters
    • 1.1.2 Advanced
• 4 Performing the brute force analysis
• 5Bruteforce analysis visualization 

Introduction

In computer science, brute force is a very general problem-solving technique and algorithmic paradigm that consists of systematically enumerating all possible candidates for the solution and checking whether each candidate satisfies the problem’s statement. Think about checking the gene expression of a gene in a certain dataset. Is that gene expression part of a broader pattern that identifies a phenotype, or is it an isolated event?

In datasets with a high number of observations (like single cell RNA-seq datasets), one of the main objectives is to identify clusters in the data that correspond to distinct phenotypes. When the biological differences between these clusters are stark, then it is easy to understand which cluster belongs to a specific cell phenotype. The problem arises when the differences between these clusters are not stark,but is a continuum in which the clusters blend into each other. In this situation, assessing the number of clusters (with the Dimensionality reduction analysis plot) present in the data becomes problematic. Even though these clusters blend into each other, they should have a distinc expression signature that differentiate them (otherwise they would be the same cluster).

To find this distinct expression signature, or these patterns, the UniApp plots all the features available in the data using the current Dimensionality reduction plot,and arranges them in an easy-to-use table that can be consulted and scrolled through very quickly. By consulting and exploring this table, you can guess the number of clusters that are present in your data.

In short, the brute force plotting analysis helps you in finding the true number of clusters in your data, which you will then use in the Clustering analysis.

The input for the bruteforce analysis is the currently selected dimensionality reduction analysis step. 

1 Creating a plot 

As a first step of the analysis, a plot must be created by clicking on the create plot icon in your analysis track. This will lead to a section where the analysis of interest can be selected.

In order to ensure efficient organisation, a name and description must be assigned to the analysis under the appropriate fields. Subsequently under "Choose algorithm to run your analysis" Bruteforce must be selected.

2 Selecting data

In the field "Choose track element", the input analysis can be selected. In the cell selection tab you can choose the observations to use as input. For more information see the section on Cell/sample selection. Note that subsetting at the pretreatment step is a "hard" subset meaning that excluded cells/samples at this step will not be present in the downstream steps.

5Bruteforce analysis visualization 

In the visualization tab you can adjust the number of rows, columns and the size of the individual plots in the bruteforce analysis results panel.