Bioinformatics

Longitudinal fundus imaging and its genome-wide association analysis provide evidence for a human retinal aging clock

1. Sara Ahadi
2. Kenneth A Wilson
3. Boris Babenko
4. Cory Y McLean
5. Drew Bryant
6. Orion Pritchard
7. Ajay Kumar
8. Enrique M Carrera
9. Ricardo Lamy
10. Jay M Stewart
11. Avinash Varadarajan
12. Marc Berndl
13. Pankaj Kapahi
14. Ali Bashir

• Curated by eLife

  eLife assessment

  This paper is an important contribution to the biological aging field using eye image data to create an aging clock of the retina in data from eyePACS with validation in the UK Biobank. The authors provide compelling evidence that the clock correlates with chronological and phenotypic age, predicting mortality independently of chronological age. The work identifies novel genetic loci with a top site located in the ALKAL2 region, which is functionally validated in a Drosophila model.

Reviewed by eLife

Generating colorblind-friendly scatter plots for single-cell data

1. Tejas Guha
2. Elana J Fertig
3. Atul Deshpande

• Curated by eLife

  eLife assessment

  This manuscript is extremely useful for describing an R package that provides a valuable pattern and overlay framework for producing colorblind-friendly scatter plots for the field. The utility of this tool for making plots more accessible was demonstrated compellingly. This work will be of broad interest to many biomedical scientists, especially to viewers with color-vision deficiency.

Reviewed by eLife

Applying causal discovery to single-cell analyses using CausalCell

1. Yujian Wen
2. Jielong Huang
3. Shuhui Guo
4. Yehezqel Elyahu
5. Alon Monsonego
6. Hai Zhang
7. Yanqing Ding
8. Hao Zhu

• Curated by eLife

  eLife assessment

  The paper describes an online tool, CausalCell, intended for the analysis of causal links in single-cell datasets. Regarding its significance, this work is timely and important, with potentially broad applications as a generally useful tool. However, there are major concerns about the suitability of the tool for its intended purpose, and the extent of validation in the current manuscript is incomplete.

Reviewed by eLife

Identify Non-mutational p53 Functional Deficiency in Human Cancers

1. Qianpeng Li
2. Yang Zhang
3. Sicheng Luo
4. Zhang Zhang
5. Ann L Oberg
6. David E Kozono
7. Hua Lu
8. Jann N Sarkaria
9. Lina Ma
10. Liguo Wang

• Curated by eLife

  eLife assessment:

  This study by Li et al describes an interesting attempt to predict the functional status of the p53 tumor suppressor in tumors where no DNA mutations in p53 could be identified. To this end, the authors employed SVM models to train the algorithm for the detection of 'p53 inactivation' features contrasting normal and tumor tissues. The approach could be a valuable tool for attributing tumors with unknown p53 status. The authors provide solid evidence supporting their findings and the concept of the study is solid, but in its current formulation, some of the bioinformatic analyses are incomplete, particularly related to the selection of associated genes and the potential mechanism(s).

Reviewed by eLife

Recommendations for Uniform Variant Calling of SARS-CoV-2 Genome Sequence across Bioinformatic Workflows

1. Ryan Connor
2. Migun Shakya
3. David A. Yarmosh
4. Wolfgang Maier
5. Ross Martin
6. Rebecca Bradford
7. J. Rodney Brister
8. Patrick S. G. Chain
9. Courtney A. Copeland
10. Julia di Iulio
11. Bin Hu
12. Philip Ebert
13. Jonathan Gunti
14. Yumi Jin
15. Kenneth S. Katz
16. Andrey Kochergin
17. Tré LaRosa
18. Jiani Li
19. Po-E Li
20. Chien-Chi Lo
21. Sujatha Rashid
22. Evguenia S. Maiorova
23. Chunlin Xiao
24. Vadim Zalunin
25. Lisa Purcell
26. Kim D. Pruitt

Reviewed by Arcadia Science

Neuroendocrinology of the lung revealed by single-cell RNA sequencing

1. Christin S Kuo
2. Spyros Darmanis
3. Alex Diaz de Arce
4. Yin Liu
5. Nicole Almanzar
6. Timothy Ting-Hsuan Wu
7. Stephen R Quake
8. Mark A Krasnow

• Curated by eLife

  eLife assessment

  This study delineates the transcriptomics of lung neuroendocrine cells and provides important new information on the nature of these cells in normal mouse lungs and in a sample of a human lung carcinoid. It will inform future studies investing the roles of PNECs in health and disease.

Reviewed by eLife

Taxonium, a web-based tool for exploring large phylogenetic trees

1. Theo Sanderson

• Curated by eLife

  eLife assessment

  Sanderson developed novel interactive software for visualizing phylogenetic trees representing millions of sequences. This is a fundamental advance over previous software that is typically limited to trees with a few thousand tips. Taxonium has been used intensively by the virus evolution community over the past months and has thus already proven its utility and performance.

Reviewed by eLife

A highly contiguous, scaffold-level nuclear genome assembly for the fever tree (Cinchona pubescens Vahl) as a novel resource for Rubiaceae research

1. Nataly Allasi Canales
2. Oscar A. Pérez-Escobar
3. Robyn F. Powell
4. Mats Töpel
5. Catherine Kidner
6. Mark Nesbitt
7. Carla Maldonado
8. Christopher J. Barnes
9. Nina Rønsted
10. Natalia A. S. Przelomska
11. Ilia J. Leitch
12. Alexandre Antonelli

Reviewed by GigaByte

svaRetro and svaNUMT: modular packages for annotating retrotransposed transcripts and nuclear integration of mitochondrial DNA in genome sequencing data

1. Ruining Dong
2. Daniel Cameron
3. Justin Bedo
4. Anthony T. Papenfuss

Reviewed by GigaByte

T cell receptor convergence is an indicator of antigen-specific T cell response in cancer immunotherapies

1. Mingyao Pan
2. Bo Li

• Curated by eLife

  eLife assessment

  This manuscript reports an association between TCR convergence and involvement in an antigen-specific response. TCR convergence is assessed as a potential biomarker of response to immune checkpoint blockade (ICB). From jointly analyzing TCR-seq data, single-cell RNA-seq data, and antigen-specific TCR information, the authors provided evidence that convergence is a potential indicator for ongoing T cell antigen-specific response. Overall, the analyses are sound the manuscript is well-written, and the study provides the first evidence that TCRseq alone could be used to predict clinical outcomes.

Reviewed by eLife