Applying Saezlab Tools to Covid-19 related Datasets

This repository contains the scripts used to apply some of our tools to Covid-19 related datasets. In particular, we take the RNAseq data from the study:

"SARS-CoV-2 launches a unique transcriptional signature from in vitro, ex vivo, and in vivo systems"

https://www.biorxiv.org/content/10.1101/2020.03.24.004655v1

https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE147507

We first focused in analysing the effect of SARS-CoV-2 infection in different human lung-related cells.

• Human lung epithelial cells (NHBE): mock treated vs infected with SARS-CoV-2.

• A549 alveolar cancer cell line: mock treated vs infected with SARS-CoV-2.

• A549 cell line does not express ACE2, the receptor used by SARS-CoV-2 to penetrate into human cells. Therefore A549 were also transduced with ACE2 and then mock treated or infected with SARS-CoV-2

• Calu-3 human lung epithelial cancer cell line: mock treated vs infected with SARS-CoV-2.

Then, we analysed the effects at the transcriptomic level of different viral infections:

• A549 alveolar cancer cell line: mock treated vs infected with SARS-CoV-2.

• A549 alveolar cancer cell line: mock treated vs infected with RSV.

• A549 alveolar cancer cell line: mock treated vs infected with HPIV3.

Effect of SARS-CoV-2 infection in different cell lines

We detail below the different scripts and analysis performed in this section:

• We first applied a traditional differential expression analysis using the DESeq2 R package. This is aligned with the script of Agatha Treveil from Tamas' group.

https://github.com/saezlab/Covid19/blob/master/DifferentialExpressionAnalysis.md

• Then, we used the normalised counts and the stastics generated in the previous script to run Dorothea and Progeny. Doing so, we estimated Transcription factors activity and pathway activity in the SARS-CoV-2 infected lines in comparison with the mock treated.

https://github.com/saezlab/Covid19/blob/master/ProgenyDorothea.md

• We run CARNIVAL using different perturbations conditions related to the virus action. In order to do so, we used TF and Pathway activity scores generated in the previous script. CARNIVAL also requires a prior knowledge network that was extracted from Omnipath using OmnipathR in line with the network used by Dezso from Tamas' group.

https://github.com/saezlab/Covid19/blob/master/runCARNIVAL.md

• We perform a pathway enrichment analysis taking into account the nodes from CARNIVAL output.

https://github.com/saezlab/Covid19/blob/master/CarnivalEnrichment.md

• We are also exploring the cell cycle phase of the different samples.

https://github.com/saezlab/Covid19/blob/master/CellCycleStage.md

Effect of different viral infections on A549 cell line

We detail below the different scripts and analysis performed in this section:

• We first applied a traditional differential expression analysis using the DESeq2 R package:

https://github.com/saezlab/Covid19/blob/master/ComparativeInfection/DifferentialExpressionAnalysis.md

• Then, we used the normalised counts and the stastics generated in the previous script to run Dorothea and Progeny. Doing so, we estimated Transcription factors activity and pathway activity in the SARS-CoV-2 infected lines in comparison with the mock treated.

https://github.com/saezlab/Covid19/blob/master/ComparativeInfection/ProgenyDorothea.md

• We run CARNIVAL using different perturbations conditions related to the virus action. In order to do so, we used TF and Pathway activity scores generated in the previous script. CARNIVAL also requires a prior knowledge network that was extracted from Omnipath using OmnipathR in line with the network used by Dezso from Tamas' group.

https://github.com/saezlab/Covid19/blob/master/ComparativeInfection/runCARNIVAL.md

• We perform a pathway enrichment analysis taking into account the nodes from CARNIVAL output.

https://github.com/saezlab/Covid19/blob/master/ComparativeInfection/CarnivalEnrichment.md

License Info

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

Please check http://www.gnu.org/licenses/.