syn_example_p

A dataset containing the differential expression parameters between different
pathotype groups for 81 synovial biopsies from the PEAC cohort.

datasets

Differential expression (DE) analysis can be used to discover quantitative changes in expression levels between experimental groups. Such results are typically visualised using volcano plots, however in cases where more than two experimental groups are involved, visualising results can become convoluted and it quickly becomes difficult to see the wood for the trees. This package provides easy-to-use functions to extract and visualise outputs from DE between three groups (primarily aimed at 'limma' and 'DESeq2' outputs). We present novel methods to map DE results into polar coordinates to enable users to combine and simultaneously view three sets of results. These graphics also possess optional 'plotly' outputs for interactive and three-dimensional functionality, as seen in Lewis et. al. (2019) <doi:10.1016/j.celrep.2019.07.091>.

Katriona Goldmann

volcano3D

Interactive Plotting of Three-Way Differential Expression
Analysis

Myles Lewis

syn_example_p function

A data frame with 100 rows representing the most significant 
genes/probes and 13 columns for each statistical parameter:<dl class="dl-horizontal">
 <dt>Gene</dt><dd>The gene name</dd>
 <dt>Fibroid_Lymphoid_pvalue</dt><dd>pvalue from fibroid vs lymphoid 
 comparison</dd>
 <dt>Fibroid_Lymphoid_padj</dt><dd>adjusted pvalue from fibroid vs lymphoid 
 comparison</dd>
 <dt>Fibroid_Lymphoid_log2FoldChange</dt><dd>logarithmic fold change from 
 fibroid vs lymphoid comparison</dd>
 <dt>Lymphoid_Myeloid_pvalue</dt><dd>pvalue from lymphoid vs myeloid 
 comparison</dd>
 <dt>Lymphoid_Myeloid_padj</dt><dd>adjusted pvalue from lymphoid vs myeloid 
 comparison</dd>
 <dt>Lymphoid_Myeloid_log2FoldChange</dt><dd>logarithmic fold change from 
 lymphoid vs myeloid comparison</dd>
 <dt>Myeloid_Fibroid_pvalue</dt><dd>pvalue from myeloid vs fibroid comparison</dd>
 <dt>Myeloid_Fibroid_padj</dt><dd>adjusted pvalue from myeloid vs fibroid 
 comparison</dd>
 <dt>Myeloid_Fibroid_log2FoldChange</dt><dd>logarithmic fold change from 
 myeloid vs fibroid comparison</dd>
 <dt>LRT_pvalue</dt><dd>pvalue from three-way likelihood ratio comparison</dd>
 <dt>LRT_padj</dt><dd>adjusted pvalue from three-way likelihood ratio 
 comparison</dd>
</dl>

Format

Synovial differential expression of genes across pathotypes in PEAC cohort — syn_example_p

A data frame with 100 rows representing the most significant 
genes/probes and 13 columns for each statistical parameter:<dl class='dl-horizontal'>
 <dt>Gene</dt><dd>The gene name</dd>
 <dt>Fibroid_Lymphoid_pvalue</dt><dd>pvalue from fibroid vs lymphoid 
 comparison</dd>
 <dt>Fibroid_Lymphoid_padj</dt><dd>adjusted pvalue from fibroid vs lymphoid 
 comparison</dd>
 <dt>Fibroid_Lymphoid_log2FoldChange</dt><dd>logarithmic fold change from 
 fibroid vs lymphoid comparison</dd>
 <dt>Lymphoid_Myeloid_pvalue</dt><dd>pvalue from lymphoid vs myeloid 
 comparison</dd>
 <dt>Lymphoid_Myeloid_padj</dt><dd>adjusted pvalue from lymphoid vs myeloid 
 comparison</dd>
 <dt>Lymphoid_Myeloid_log2FoldChange</dt><dd>logarithmic fold change from 
 lymphoid vs myeloid comparison</dd>
 <dt>Myeloid_Fibroid_pvalue</dt><dd>pvalue from myeloid vs fibroid comparison</dd>
 <dt>Myeloid_Fibroid_padj</dt><dd>adjusted pvalue from myeloid vs fibroid 
 comparison</dd>
 <dt>Myeloid_Fibroid_log2FoldChange</dt><dd>logarithmic fold change from 
 myeloid vs fibroid comparison</dd>
 <dt>LRT_pvalue</dt><dd>pvalue from three-way likelihood ratio comparison</dd>
 <dt>LRT_padj</dt><dd>adjusted pvalue from three-way likelihood ratio 
 comparison</dd>
</dl>

syn_example_p: Synovial differential expression of genes across pathotypes in PEAC cohort

Description

Usage

Arguments

Format