Latest preprint reviews

1. Molecular Property Diagnostic Suite for COVID-19 (MPDS ^COVID-19 ): An open access disease specific drug discovery portal

   This article has 19 authors:

   1. Lipsa Priyadarsinee
   2. Esther Jamir
   3. Selvaraman Nagamani
   4. Hridoy Jyoti Mahanta
   5. Nandan Kumar
   6. Lijo John
   7. Himakshi Sarma
   8. Asheesh Kumar
   9. Anamika Singh Gaur
   10. Rosaleen Sahoo
   11. S. Vaikundamani
   12. N. Arul Murugan
   13. U. Deva Priyakumar
   14. G.P.S. Raghava
   15. Prasad V. Bharatam
   16. Ramakrishnan Parthasarathi
   17. V. Subramanian
   18. G. Madhavi Sastry
   19. G. Narahari Sastry

   This article has been curated by 1 group:

   • Curated by GigaByte

     Editors Assessment:

     MPDSCOVID-19 has been developed as a one-stop solution for drug discovery research for COVID-19, running on the Molecular Property Diagnostic Suite (MPDS) platform. This is built upon the open-source Galaxy workflow system, integrating many modules and data specific to COVID-19. Data integrated includes SARS-CoV-2 targets, genes and their pathway information; information on repurposed drugs against various targets of SARS-CoV-2, mutational variants, polypharmacology for COVID-19, drug-drug interaction information, Protein-Protein Interaction (PPI), host protein information, epidemiology, and inhibitors databases. After improvements to the technical description of the platform, testing helped demonstrate the potential to drive open-source computational drug discovery with the platform.

     This evaluation refers to version 1 of the preprint

   Reviewed by GigaByte

2. Molecular Property Diagnostic Suite for COVID-19 (MPDS ^COVID-19 ): An open access disease specific drug discovery portal

   This article has 19 authors:

   1. Lipsa Priyadarsinee
   2. Esther Jamir
   3. Selvaraman Nagamani
   4. Hridoy Jyoti Mahanta
   5. Nandan Kumar
   6. Lijo John
   7. Himakshi Sarma
   8. Asheesh Kumar
   9. Anamika Singh Gaur
   10. Rosaleen Sahoo
   11. S. Vaikundamani
   12. N. Arul Murugan
   13. U. Deva Priyakumar
   14. G.P.S. Raghava
   15. Prasad V. Bharatam
   16. Ramakrishnan Parthasarathi
   17. V. Subramanian
   18. G. Madhavi Sastry
   19. G. Narahari Sastry

   This article has been curated by 1 group:

   • Curated by GigaByte

     Editors Assessment:

     MPDSCOVID-19 has been developed as a one-stop solution for drug discovery research for COVID-19, running on the Molecular Property Diagnostic Suite (MPDS) platform. This is built upon the open-source Galaxy workflow system, integrating many modules and data specific to COVID-19. Data integrated includes SARS-CoV-2 targets, genes and their pathway information; information on repurposed drugs against various targets of SARS-CoV-2, mutational variants, polypharmacology for COVID-19, drug-drug interaction information, Protein-Protein Interaction (PPI), host protein information, epidemiology, and inhibitors databases. After improvements to the technical description of the platform, testing helped demonstrate the potential to drive open-source computational drug discovery with the platform.

     This evaluation refers to version 1 of the preprint

   Reviewed by GigaByte

3. An improved chromosome-level genome assembly of perennial ryegrass ( Lolium perenne L.)

   This article has 7 authors:

   1. Yutang Chen
   2. Roland Kölliker
   3. Martin Mascher
   4. Dario Copetti
   5. Axel Himmelbach
   6. Nils Stein
   7. Bruno Studer

   This article has been curated by 1 group:

   • Curated by GigaByte

     Editors Assessment:

     This Data Release paper presents an updated genome assembly of the doubled haploid perennial ryegrass (Lolium perenne L.) genotype Kyuss (Kyuss v2.0). To correct for structural the authors de novo assembled the genome again with ONT long-reads and generated 50-fold coverage high-throughput chromosome conformation capture (Hi-C) data to assist pseudo-chromosome construction. After being asked for some more improvements to gene and repeat annotation the authors now demonstrate the new assembly is more contiguous, more complete, and more accurate than Kyuss v1.0 and shows the correct pseudo-chromosome structure. This more accurate data have great potential for downstream genomic applications, such as read mapping, variant calling, genome-wide association studies, comparative genomics, and evolutionary biology. These future analyses being able to benefit forage and turf grass research and breeding.

     This evaluation refers to version 1 of the preprint

   Reviewed by GigaByte

4. Citizen science data on urban forageable plants: a case study in Brazil

   This article has 21 authors:

   1. Filipi Miranda Soares
   2. Luís Ferreira Pires
   3. Maria Carolina Garcia
   4. Lidio Coradin
   5. Natalia Pirani Ghilardi-Lopes
   6. Rubens Rangel Silva
   7. Aline Martins de Carvalho
   8. Anand Gavai
   9. Yamine Bouzembrak
   10. Benildes Coura Moreira dos Santos Maculan
   11. Sheina Koffler
   12. Uiara Bandineli Montedo
   13. Debora Pignatari Drucker
   14. Raquel Santiago
   15. Maria Clara Peres de Carvalho
   16. Ana Carolina da Silva Lima
   17. Hillary Dandara Elias Gabriel
   18. Stephanie Gabriele Mendonça de França
   19. Karoline Reis de Almeida
   20. Bárbara Junqueira dos Santos
   21. Antonio Mauro Saraiva

   This article has been curated by 1 group:

   • Curated by GigaByte

     Editors Assessment:

     This is a Data Release paper describing data sets derived from the Pomar Urbano project cataloging edible fruit-bearing plants in Brazil. Including data sourced from the citizen science iNaturalist app, tracking the distribution and monitoring of these plants within urban landscapes (Brazilian state capitals). The data was audited and peer reviewed and put into better context, and there is a companion commentary in GigaScience journal better explaining the rationale for the study. Demonstrating this data providing a platform for understanding the diversity of fruit-bearing plants in select Brazilian cities and contributing to many open research questions in the existing literature on urban foraging and ecosystem services in urban environments.

     This evaluation refers to version 1 of the preprint

   Reviewed by GigaByte

5. SAW: An efficient and accurate data analysis workflow for Stereo-seq spatial transcriptomics

   This article has 17 authors:

   1. Chun Gong
   2. Shengkang Li
   3. Leying Wang
   4. Fuxiang Zhao
   5. Shuangsang Fang
   6. Dong Yuan
   7. Zijian Zhao
   8. Qiqi He
   9. Mei Li
   10. Weiqing Liu
   11. Zhaoxun Li
   12. Hongqing Xie
   13. Sha Liao
   14. Ao Chen
   15. Yong Zhang
   16. Yuxiang Li
   17. Xun Xu

   This article has been curated by 1 group:

   • Curated by GigaByte

     Editors Assessment:

     One limiting factor in the adoption of spatial omics research are workflow systems for data preprocessing, and to address these authors developed the SAW tool to process Stereo-seq data. The analysis steps of spatial transcriptomics involve obtaining gene expression information from space and cells. Existing tools face issues with large data sets, such as intensive spatial localization, RNA alignment, and excessive memory usage. These issues affect the process's applicability and efficiency. To address this, this paper presents a high-performance open-source workflow called SAW for Stereo-Seq. This includes mRNA position reconstruction, genome alignment, matrix generation, clustering, and result file generation for personalized analysis. During review the authors have added examples of MID correction in the article to make the process easier to understand. And In the future, more accurate algorithms or deep learning models may further improve the accuracy of this pipeline.

     *This evaluation refers to version 1 of the preprint

   Reviewed by GigaByte

6. Generating single-cell gene expression profiles for high-resolution spatial transcriptomics based on cell boundary images

   This article has 14 authors:

   1. Bohan Zhang
   2. Mei Li
   3. Qiang Kang
   4. Zhonghan Deng
   5. Hua Qin
   6. Kui Su
   7. Xiuwen Feng
   8. Lichuan Chen
   9. Huanlin Liu
   10. Shuangsang Fang
   11. Yong Zhang
   12. Yuxiang Li
   13. Susanne Brix
   14. Xun Xu

   This article has been curated by 1 group:

   • Curated by GigaByte

     Editors Assessment:

     This paper describes a new spatial transcriptomics method that that utilizes cell nuclei staining images and statistical methods to generate high-confidence single-cell spatial gene expression profiles for Stereo-seq data. STCellbin is an update of StereoCell, now using a more advanced cell segmentation technique, so more accurate cell boundaries can be obtained, allowing more reliable single-cell spatial gene expression profiles to be obtained. After peer review more comparisons were added and more description given on what was upgraded in this version to convince the reviewers. Demonstrating it is a more reliable method, particularly for analyzing high-resolution and large-field-of-view spatial transcriptomic data. And extending the capability to automatically process Stereo-seq cell membrane/wall staining images for identifying cell boundaries.

     This evaluation refers to version 2 of the preprint

   Reviewed by GigaByte

7. BatchEval Pipeline: Batch Effect Evaluation Workflow for Multiple Datasets Joint Analysis

   This article has 6 authors:

   1. Chao Zhang
   2. Qiang Kang
   3. Mei Li
   4. Hongqing Xie
   5. Shuangsang Fang
   6. Xun Xu

   This article has been curated by 1 group:

   • Curated by GigaByte

     Editors Assessment:

     For better data quality assessment of large spatial transcriptomics datasets this new BatchEval software has been developed as a batch effect evaluation tool. This generates a comprehensive report with assessment findings, including basic information of integrated datasets, a batch effect score, and recommended methods for removing batch effects. The report also includes evaluation details for the raw dataset and results from batch effect removal methods. Through peer review and clarification of a number of points it now looks convincing that this tool helps researchers identify and remove batch effects, ensuring reliable and meaningful insights from integrated datasets. Potentially making the tool valuable for researchers who need to analyze large datasets of this type, as it provides an easy and reliable way to assess data quality and ensures that downstream analyses are robust and reliable.

     This evaluation refers to version 1 of the preprint

   Reviewed by GigaByte

8. Near chromosome-level and highly repetitive genome assembly of the snake pipefish Entelurus aequoreus (Syngnathiformes: Syngnathidae)

   This article has 20 authors:

   1. Magnus Wolf
   2. Bruno Lopes da Silva Ferrette
   3. Raphael T. F. Coimbra
   4. Menno de Jong
   5. Marcel Nebenfuehr
   6. David Prochotta
   7. Yannis Schöneberg
   8. Konstantin Zapf
   9. Jessica Rosenbaum
   10. Hannah A. Mc Intyre
   11. Julia Maier
   12. Clara C.S. de Souza
   13. Lucas M. Gehlhaar
   14. Melina J. Werner
   15. Henrik Oechler
   16. Marie Wittekind
   17. Moritz Sonnewald
   18. Maria A. Nilsson
   19. Axel Janke
   20. Sven Winter

   This article has been curated by 1 group:

   • Curated by GigaByte

     Editors Assessment:

     The snake pipefish, Entelurus aequoreus, is a species of fish that dwells in open seagrass habitats in the northern Atlantic. As a pipefish, it is a member of the Syngnathidae family of fish which also includes seahorses and seadragons. In recent years it has expanded its population size and range into arctic waters. To better understand these demographic changes genomic data is useful, and to address this a high-quality reference genome has been produced. Building on a previous short-read reference, a near chromosome-scale genome assembly for the snake pipefish was assembled using PacBio CLR and Hi-C reads. After revisions the authors provided more details on the assembly metrics, the final assembly has a length of 1.6 Gbp, with scaffold and contig N50s of 62.3 Mbp and 45.0 Mbp respectively. Demographic inference analysis of the snake pipefish genome using this data enables tracing of population changes over the past 1 million years, and this reference will allow further analyses and studies relating these to changes in climate.

     **This evaluation refers to version 1 of the preprint

   Reviewed by GigaByte

9. Species Composition and Distribution of Anopheles gambiae Complex Circulating in Kinshasa

   This article has 11 authors:

   1. Josue Zanga
   2. Emery Metelo
   3. Nono Mvuama
   4. Victoire Nsabatien
   5. Vanessa Mvudi
   6. Degani Banzulu
   7. Osée Mansiangi
   8. Maxwel Bamba
   9. Narcisse Basosila
   10. Rodrigue Agossa
   11. Roger Wumba

   This article has been curated by 1 group:

   • Curated by GigaByte

     Editors Assessment: Understanding the distribution of Anopheles mosquito species is essential for planning and implementing malaria control programmes, a task undertaken in this study that assesses the composition and distribution of the Anopheles in different districts of Kinshasa in the Democratic Republic of Congo. Mosquitoes were collected using CDC light traps, and then identified by morphological and molecular means. In total 3,839 Anopheles were collected, and data was digitised, validated and shared via the GBIF database under a CC0 waiver. The project monitoring the monthly dynamics of four species of Anopheles, showing a fluctuation in their respective frequencies during the study period. Review improved the metadata by adding more accurate date information, and this data can provide important information for further basic and advanced studies on the ecology and phenology of these vectors in West Africa.

     *This evaluation refers to version 1 of the preprint

   Reviewed by GigaByte

10. Nanopore adaptive sampling enriches for antimicrobial resistance genes in microbial communities

    This article has 2 authors:

    1. Danielle C. Wrenn
    2. Devin M. Drown

    This article has been curated by 1 group:

    • Curated by GigaByte

      Editors Assessment: Antimicrobial resistance (AMR) is a global public health threat, and environmental microbial communities can act as reservoirs for resistance genes. There is a need for genomic surveillance could provide insights into how these reservoirs change and impact public health. With that goal in mind this study tested the ability of nanopore sequencing and adaptive sampling to enrich for AMR genes in a mock community of environmental origin. On average adaptive sampling resulting in a target composition 4x higher than without adaptive sampling, and increased target yield in most replicates. The methods and scripts for this approach were reviewed and curated together, although the scope of this study was limited in terms of communities tested and AMR genes targeted. And the authors improved their analysis by conducting an additional analysis of a diverse microbial community. Demonstrating the method is reusable and its results are promising for developing a flexible, portable, and cost-effective AMR surveillance tool.

      *This evaluation refers to version 1 of the preprint

    Reviewed by GigaByte