Antib Pept Array Tracks
Antibody Proteome Peptide Binding Microarray Raw Data from Wang et al, ACS 2020, Xiaobo Yu group, NCPSB Beijing tracks   (All Immunology tracks)

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Antib Pept Array Sum (IgG)  Antibody Proteome Peptide Binding Microarray, Wang et al 2020 - IgG, Covid - Sum of scores per nucleotide  
Antib Pept Array Sum (IgM)  Antibody Proteome Peptide Binding Microarray, Wang et al 2020 - IgM, Covid - Sum of scores per nucleotide  
IgG Z-score- early COVID-19 patients  Proteome Peptide Microarray - IgG - early COVID-19 patients  
IgM Z-score - early COVID-19 patients  Proteome Peptide Microarray - IgM - early COVID-19 patients  
Assembly: SARS-CoV-2 Jan. 2020 (NC_045512.2)


This track shows intensities of a microarray spotted with short peptides derived from the entire proteome of SARS-CoV-2. Sera from 10 COVID-19 patients (early stage) and 12 healthy controls were screened on the peptide microarray for both IgG and IgM responses. Note that the infections here were in the early stage, unlike the other microarray track shown on this genome browser.

Display Conventions and Configuration

Genomic locations of peptides that were spotted on the array are highlighted. Because these peptides overlap, the tracks default to dense mode and the sequence is shown as labels drawn onto the rectangles, but only visible on high zoom levels. Put any track into pack mode to fully see all probe sequences.

The color is assigned based on the Z-Score, without any other normalization. Blue with decreasing intensity is assigned to the values -5 to 0, white is 0, and red colors with increasing intensity are used for the values 0-3.5, exactly as in the original publication figures.

There are also two wiggle/signal style tracks to summary the information, they show the sum of Z-scores across all peptides, as one score per nucleotide.


Supplemental files were converted from Excel, rearranged and run through the command line script bigHeat to create a heatmap-like display, with multiplication factors of 2 for negative values, 0.285 for positive values. For better visibility, colormap seismic from matplotlib was used from 0.1 to 0.9 and the range of values after multiplication were restricted to the limits -1 to 1 to address outliers. Like all tracks, the exact commands are documented in our makeDoc text files.

Data Access

The raw data can be explored interactively with the Table Browser or combined with other datasets in the Data Integrator tool. For automated analysis, the genome annotation is stored in a bigBed file that can be downloaded from the download server.

Annotations can be converted from binary to ASCII text by our command-line tool bigBedToBed. Instructions for downloading this command can be found on our utilities page. The tool can also be used to obtain features within a given range without downloading the file, for example:

bigBedToBed -chrom=NC_045512v2 -start=0 -end=29902 stdout

Please refer to our mailing list archives for questions, or our Data Access FAQ for more information.


Hongye Wang, Xian Wu, Xiaomei Zhang, Xin Hou, Te Liang, Dan Wang, Fei Teng, Jiayu Dai, Hu Duan, Shubin Guo, Yongzhe Li, and Xiaobo Yu SARS-CoV-2 Proteome Microarray for Mapping COVID-19 Antibody Interactions at Amino Acid Resolution. ACS Central Science. 2020 DOI: 10.1021/acscentsci.0c00742