This Month in Bioinformatics- Research Updates of April 2021

In this article, we summarize the latest interesting findings made this month in bioinformatics.

1. A single-cell lung atlas of lethal covid-19

A molecular single-cell lung atlas of lethal covid-19 is proposed [1]. In this work, the authors have found the reason for lung impairment caused by Alveolar type-2 cells that fail to undergo a transition into alveolar type-1 cells. They have also identified the expansion of recently described CTHRC1+ pathological fibroblasts that contribute to pulmonary fibrosis in covid-19.

For more information, read here.

2. A New Platform for Microbiome Analysis

A new bioinformatics tool called “EzMAP” is developed for the easy analysis of the microbiome [2]. It is a user-friendly platform allowing users to perform microbiome analysis from raw sequence processing to downstream analysis. Downstream analyses include relative abundances, differential abundances, community comparison, and functional prediction. EzMAP provides a graphical user interface for easy access to different functionalities of QIIME2 (Quantitative Insights Into Microbial Ecology).

For more information, read here.

3. A new database of tumor T-cell antigens & epitopes

A new database called TANTIGEN is a comprehensive database consisting of 1000 T cell epitopes and HLA ligands from 292 different tumor T-cell antigens [3]. A new version of TANTIGEN is introduced this month, known as TANTIGEN 2.0. The latest version, TANTIGEN 2.0 consists of 4,296 antigen variants from 403 unique tumor antigens and more than 1500 T-cell epitopes and HLA ligands [4]. It also contains TCR sequences extracted from Human Pathology Atlas. The new data is incorporated from the Cancer Antigenic Peptide Database [5] and recent publications.

For more information, click here.

4. A new GPU-based pipeline for primer design for qPCR experiments

A GPU-based pipeline for primer design for qPCR experiments is developed, known as GPrimer [6]. It takes the same input and provides the same output with MRPrimer without using any additional tools such as BLAST. GPrimer takes an entire database as input and provides all feasible and valid primer pairs present in the input database as output. The software is freely accessible at https://github.com/qhtjrmin/GPrimer.git.

For more information, read here.

5. An advanced version of GRAPES for index-driven search in biological graph databases

GRAPES has shown good performance in terms of speed but it suffers in the size of the built index. Therefore, a new version called GRAPES-DD is proposed [7]. In this version, decision diagrams are used instead of indexing structures. After testing it on some biomedical structures and synthetic graphs, GRAPES-DD has been found to reduce memory utilization within less searching time.

For more information, read here.

6. A new tool for functional prediction from gene co-expression correlations

A new tool called Correlation AnalyzeR is developed for functional prediction from gene co-expression correlations [8]. It is a user-friendly web interface that allows users to explore co-expression correlations, gene-gene relationships, gene set topology, and predict gene functions. Correlation AnalyzeR helps to gain novel biological insights by exploring poorly characterized genes and gene relationships. The web interface is freely accessible at https://gccri.bishop-lab.uthscsa.edu/correlation-analyzer/ and the software can be downloaded from Github.

For more information, read here.

References

1. Melms, J.C., Biermann, J., Huang, H. et al. (2021). A molecular single-cell lung atlas of lethal COVID-19. Nature.
2. Shanmugam, G., Lee, S.H. & Jeon, J. (2021). EzMAP: Easy Microbiome Analysis Platform. BMC Bioinformatics 22, 179.
3. Olsen, L. R., Tongchusak, S., Lin, H., Reinherz, E. L., Brusic, V., & Zhang, G. L. (2017). TANTIGEN: a comprehensive database of tumor T cell antigens. Cancer Immunology, Immunotherapy, 66(6), 731-735.
4. Zhang, G., Chitkushev, L., Olsen, L.R. et al. (2021). TANTIGEN 2.0: a knowledge base of tumor T cell antigens and epitopes. BMC Bioinformatics 22, 40.
5. Vigneron, N., Stroobant, V., Van den Eynde, B. J., & van der Bruggen, P. (2013). Database of T cell-defined human tumor antigens: the 2013 update. Cancer Immunity Archive, 13(3).
6. Bae, J., Jeon, H. & Kim, MS. (2021). GPrimer: a fast GPU-based pipeline for primer design for qPCR experiments. BMC Bioinformatics 22, 220.
7. Licheri, N., Bonnici, V., Beccuti, M. et al. (2021). GRAPES-DD: exploiting decision diagrams for index-driven search in biological graph databases. BMC Bioinformatics 22, 209.
8. Miller, H.E., Bishop, A.J.R. (2021). Correlation AnalyzeR: functional predictions from gene co-expression correlations. BMC Bioinformatics 22, 206.