A multi-omics based anti-inflammatory immune signature characterizes Long COVID Syndrome - Kovarik et al.
Description
Supplementary Table S1 related to Figure 1: Student's t-test statistics between long-covid and recovered, long-covid and healthy as well as recovered and healthy are shown. For each identified protein, log2 label-free quantification (LFQ) intensities, numbers of identified peptides, numbers of identified unique peptides as well as the sequence coverage is listed. Supplementary Table S2 related to Figure 2: Student's t-test statistics between long-covid and recovered, long-covid and healthy as well as recovered and healthy are shown. For each identified eicosanoid normalized area under the curve (nAUC) values are listed. Supplementary Table S3 related to Figure 3: Student's t-test statistics between long-covid and recovered, long-covid and healthy as well as recovered and healthy are shown. For each identified metabolite log2 concentrations in µM are listed. Supplementary Table S4 related to Figure 3: Heatmap data matrix. Normalized values generated by dividing the concentration of each lipid through the average concentration of this lipid over all samples.
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Institutions
- Universitat Wien Massenspektrometriezentrum