abiotic_stresses: Combined abiotic stresses

In OceaneCsn/DIANE: DIANE

Combined abiotic stresses

Description

This dataset contians the transcriptome of Arabidopsis thaliana plants exposed to global warming induced conditions. It was generated in the article "Molecular plant responses to combined abiotic stresses put a spotlight on unknown and abundant genes", by Sewelam et Al. in Journal of experimental Botany, 2020. The experimental perturbations studied are high tempreature, hight salinity and osmotic changes in the soil. Each factors has two levels, one of them considered as the reference, and the other one as the stress level.

Usage

abiotic_stresses

Format

A named list with the following elements:

raw_counts

Dataframe of positive values. Raw transcript aboundances as obtained after mapping and quantifying RNASeq reads. Rows are transcripts, and columns are experimental triplicate conditions

normalized_counts

Dataframe of positive values. Normalized transcript aboundances Rows are transcripts, and columns are experimental triplicate conditions

design

Dataframe. Describes for each condition, the level of each factor.

conditions

Character vector. Gives the condition corresponding to each column of the raw_counts element

heat_DEGs

Character vector. 692 genes detected as differentially expressed between control and heat stress, with adjusted pavlue of 0.01 and absolute log fold change of 2.

heat_DEGs_coseq_membership

Named character vector. Cluster of the 692 genes detected as differentially expressed between control and heat stress, This membership was obtained after running coseq expression based clustering on those genes, on all the dataset conditions, and resulted in 9 clusters.

heat_DEGs_regulatory_links

Matrix of size 25*654 genes. The matrix contains the importances of the 25 regulators on the 654 genes, and was infered with the network_inference method. Those gens are the ones detected as differentially expressed between control and heat stress, and the regulators among them were grouped when correlated over 0.9.

heat_edge_tests

Statistical testing from the edge_testing function, applied to the heat_DEGs_regulatory_links element. It contains the pvalue for each edge of a prior network built on a desired density.

Source

Data download :

GEO accession

Publication :

Molecular plant responses to combined abiotic stresses put a spotlight on unknown and abundant genes

Examples

{
 print(head(abiotic_stresses$raw_counts))
 print(abiotic_stresses$design)
 print(abiotic_stresses$conditions)
}

OceaneCsn/DIANE documentation built on Jan. 10, 2024, 6:43 p.m.