nlvelo: an R package for RNA velocity estimation using nonlinear models

Investigators
Qing Nie
Contact info (email)
qnie@uci.edu
1. Define context(s)
reveal new biological insights
Current Conformance Level / Target Conformance Level
Extensive
Primary goal of the model/tool/database

La Manno et al. used a linear model to relate abundance of pre-mRNA U(t) with abundance of mature mRNA S(t) (La Manno et al., Nature 2018). Given that the molecular regulatory mechanisms between pre-mRNA and mature mRNA are complicated, and in many molecular networks more commonly we observe non-linear (e.g. switch-like) responses, we proposed a nonlinear model of RNA velocity for the effects of pre-mRNA on the abundance of mature mRNA based on Michaelis–Menten kinetics.

Biological domain of the model
RNA velocity for scRNA-seq data
Structure(s) of interest in the model
Temporal trajectory in scRNA-seq data
Spatial scales included in the model
cellular to tissue
Time scales included in the model
seconds to weeks
2. Data for building and validating the model
Data for building the model Published? Private? How is credibility checked? Current Conformance Level / Target Conformance Level
in vitro (primary cells cell, lines, etc.)
ex vivo (excised tissues)
in vivo pre-clinical (lower-level organism or small animal) Yes No The model was built in an unsupervised way on unbiased single-cell RNA sequencing data and spatial data. Extensive
in vivo pre-clinical (large animal)
Human subjects/clinical
Other: ________________________
Data for validating the model Published? Private? How is credibility checked? Current Conformance Level / Target Conformance Level
in vitro (primary cells cell, lines, etc.)
ex vivo (excised tissues)
in vivo pre-clinical (lower-level organism or small animal) Yes No By comparing to existing knowledge. Adequate
in vivo pre-clinical (large animal)
Human subjects/clinical
Other: ________________________
3. Validate within context(s)
Who does it? When does it happen? How is it done? Current Conformance Level / Target Conformance Level
Verification Students/postdocs/investigators Throughout the project The convergence of the algorithm is guaranteed. The method is tested on synthetic datasets. Extensive
Validation Students/postdocs/investigators As the unsupervised model was established The inferred developmental trajectory agrees with available knowledge. Extensive
Uncertainty quantification
Sensitivity analysis Students/postdocs/investigators As the unsupervised model was established By tuning key parameters and comparing to annotated data. Adequate
Other:__________
Additional Comments
4. Limitations
Disclaimer statement (explain key limitations) Who needs to know about this disclaimer? How is this disclaimer shared with that audience? Current Conformance Level / Target Conformance Level
Technical noise of scRNA-seq data Scientific community who intends to apply this method to raw scRNA-seq data. In discussion of the paper. Adequate
5. Version control
Current Conformance Level / Target Conformance Level
Extensive
Naming Conventions? Repository? Code Review?
individual modeler Yes Yes Peer
within the lab Yes Yes Peer
collaborators Yes Yes Peer
6. Documentation
Current Conformance Level / Target Conformance Level
Code commented? Extensive
Scope and intended use described? Extensive
User’s guide? Extensive
Developer’s guide? Partial
7. Dissemination
Current Conformance Level / Target Conformance Level
Extensive
Target Audience(s): “Inner circle” Scientific community Public
Simulations
Models
Software R package: https://github.com/sqjin/nlvelo R package: https://github.com/sqjin/nlvelo
Results Shared folders Paper and tutorials
Implications of results
8. Independent reviews
Current Conformance Level / Target Conformance Level
Insufficient
Reviewer(s) name & affiliation:
When was review performed?
How was review performed and outcomes of the review?
9. Test competing implementations
Current Conformance Level / Target Conformance Level
Adequate
Yes or No (briefly summarize)
Were competing implementations tested? Yes. The advantage of the proposed method was demonstrated by comparing to the standard linear RNA velocity model.
Did this lead to model refinement or improvement? Yes
10. Conform to standards
Current Conformance Level / Target Conformance Level
Adequate
Yes or No (briefly summarize)
Are there operating procedures, guidelines, or standards for this type of multiscale modeling? Yes. There are several standard procedures for preprocessing scRNA-seq data.
How do your modeling efforts conform? Common data preprocessing procedures are followed.