Cover Letter#
A strong cover letter introduces your manuscript, highlights its importance, and explains why it fits the journal.
Keep it concise and aligned with the journal’s scope. Your goal is to communicate:
- What the study is about
- Why it matters
- Why it fits the journal and its readership
What to Include#
- Greeting: Address the editor by name if known.
- Opening: Date, journal name, manuscript title, and article type (e.g., research, review).
- Summary: Briefly describe the research question, key methods, and main findings.
- Impact: Explain how your study advances the field and aligns with the journal’s scope.
- Closing: Identify the corresponding author and confirm compliance with journal policies.
Paragraph Breakdown#
First paragraph: include the title of your manuscript and the type of manuscript it is (e.g. review, research, case study). Then briefly explain the background to your study, the question you sought out to answer and why.
Second paragraph: you should concisely explain what was done, the main findings and why they are significant.
Third paragraph: here you should indicate why the readers of the journal would be interested in the work. Take your cues from the journal’s aims and scope. For example if the journal requires that all work published has broad implications explain how your study fulfills this. It is also a good idea to include a sentence on the importance of the results to the field.
Required Statements#
- “This manuscript has not been published elsewhere and is not under consideration by another journal.”
- “All authors have approved the manuscript and agree with its submission to [Journal Name].”
Use the letter to confidently position your work. Editors often read it before the manuscript itself.
Example Structure#
Example
March 18, 2021
Dear Editors,
We are pleased to submit our manuscript entitled “Orchestrating and sharing large multimodal data for transparent and reproducible research” as an Article in the Nature Communications Journal.
One of the fundamental challenges in research is ensuring that a study is fully reproducible, from data retrieval, to processing and subsequent analysis. With the continuous advances in biotechnology, including high-throughput molecular, pharmacological and radiological profiling, the intrinsic complexity of the data increased, making the computational pipelines used to process these data more intricate and difficult to replicate. Moreover, the development of new processing pipelines is allowing researchers to process the data in multiple ways, often extracting complementary information from the same assay. Importantly, with biotechnologies getting easier and cheaper to use, datasets are growing fast and are often updated, making it challenging for the community to keep track of all versions of the data. Therefore, there is a need for greater transparency, reproducibility and flexibility in the processing of large multimodal data to realize their full potential for research.
To address these issues, we developed ORCESTRA (www.orcestra.ca), a cloud-based platform that provides a transparent, reproducible, and flexible computational framework for processing and sharing large multimodal data. The ORCESTRA platform integrates genomic, pharmacological and radiological profiles of biological samples through the orchestration of automated processing pipelines to curate customized and fully documented data objects for future analyses. Our workflows utilize a data processing and versioning tool enabling curation, standardization and flexible normalization of large multimodal data, focusing on, but not limited to, cancer research using high-throughput biotechnologies. Users can customize their data object generation by selecting different versions of a dataset and molecular profile data that is processed with multiple genomic tools, all with full transparency, as the data provenance of each data object is fully documented and objects are automatically assigned a Digital Object Identifier (DOI).
We believe ORCESTRA will be a valuable contribution to the biomedical field, and will be of great interest to the readers of the Nature Communications journal. All authors have read and approved the final version of the manuscript. I confirm that the content of this manuscript has not been published previously and has not been submitted to another Journal. We have made our research fully reproducible by sharing all the data and documented code. We thank you in advance for considering our manuscript for publication in the Journal.
Sincerely, Benjamin Haibe-Kains
Senior Scientist, Princess Margaret Cancer Centre
Associate Professor, University of Toronto University Health Network