Evidence map›Paper›PMID 35871895›Full record

ArticleAdvances in protein chemistry and structural biology2022

Exploring COVID-19 pathogenesis on command-line: A bioinformatics pipeline for handling and integrating omics data.

Janaina Macedo-da-Silva, João Victor Paccini Coutinho, Livia Rosa-Fernandes, Suely Kazue Nagahashi Marie, Giuseppe Palmisano

Open access · greenAbstract read
In one paragraph

Article in Advances in protein chemistry and structural biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.5field-weighted citation impact, top 41% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Janaina Macedo-da-SilvaGlycoProteomics Laboratory, Department of Parasitology, ICB, University of São Paulo, São Paulo, Brazil.
João Victor Paccini CoutinhoGlycoProteomics Laboratory, Department of Parasitology, ICB, University of São Paulo, São Paulo, Brazil.
Livia Rosa-FernandesGlycoProteomics Laboratory, Department of Parasitology, ICB, University of São Paulo, São Paulo, Brazil.
Suely Kazue Nagahashi MarieCellular and Molecular Biology Laboratory (LIM 15), Neurology Department, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, Brazil.
Giuseppe PalmisanoGlycoProteomics Laboratory, Department of Parasitology, ICB, University of São Paulo, São Paulo, Brazil; School of Natural Sciences, Macquarie University, Sydney, NSW, Australia. Electronic address: palmisano.gp@gmail.com.
Universidade de São Paulo · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first identified in late 2019 in Wuhan, China, and has proven to be highly pathogenic, making it a global public health threat. The immediate need to understand the mechanisms and impact of the virus made omics techniques stand out, as they can offer a holistic and comprehensive view of thousands of molecules in a single experiment. Mastering bioinformatics tools to process, analyze, integrate, and interpret omics data is a powerful knowledge to enrich results. We present a robust and open access computational pipeline for extracting information from quantitative proteomics and transcriptomics public data. We present the entire pipeline from raw data to differentially expressed genes. We explore processes and pathways related to mapped transcripts and proteins. A pipeline is presented to integrate and compare proteomics and transcriptomics data using also packages available in the Bioconductor and providing the codes used. Cholesterol metabolism, immune system activity, ECM, and proteasomal degradation pathways increased in infected patients. Leukocyte activation profile was overrepresented in both proteomics and transcriptomics data. Finally, we found a panel of proteins and transcripts regulated in the same direction in the lung transcriptome and plasma proteome that distinguish healthy and infected individuals. This panel of markers was confirmed in another cohort of patients, thus validating the robustness and functionality of the tools presented.

Indexed as

COVID-19Computational BiologyHumansProteomeProteomicsSARS-CoV-2ProteomeCOVID-19Data integrationProteomicsSARS-CoV-2Transcriptomics

Identifiers

PMID35871895
PMCPMC9095070
OpenAlexW4285208697

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.