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
scAI is an unsupervised approach that integrates parallel single-cell transcriptomic and epigenomic profiles, which enables the dissection of cellular heterogeneity within both transcriptomic and epigenomic layers and the understanding of transcriptional regulatory mechanisms.
Biological domain of the model
scRNA-seq and scATAC-seq data for various tissues
Structure(s) of interest in the model
cellular heterogeneity within both transcriptomic and epigenomic layers
Spatial scales included in the model
cellular to tissue
Time scales included in the model
seconds to hours
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) | ||||
| in vivo pre-clinical (large animal) | Yes | No | The model was built in an unsupervised way on unbiased single-cell RNA sequencing data. | Extensive |
| 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) | ||||
| in vivo pre-clinical (large animal) | Yes | No | By 1) comparing the identified cell clusters to the known heterogenity in epigenomic profiles and 2) comparing the inferred differentiation trajectory to known developmental processes. | Adequate |
| Human subjects/clinical | ||||
| Other: ________________________ | Yes | No | By comparing to simulated data. | Adequate |
3. Validate within context(s)
| Who does it? | When does it happen? | How is it done? | Current Conformance Level / Target Conformance Level | |
|---|---|---|---|---|
| Verification | Postdocs/Investigators | Throughout the project | By 1) making sure the convergence and correctness of algorithm and 2) checking the expected heterogeneity level in transcriptomics and epigenomics. | Extensive |
| Validation | Postdocs/Investigators | As the unsupervised model was established | 1) The inferred differentiation trajectory was compared to known knowledge and simulated data. 2) The identified key transcription factors was confirmed by TF databases. 3) The cell clustering from the integrated data agrees well with knowledge. | Extensive |
| Uncertainty quantification | ||||
| Sensitivity analysis | Postdocs/investigators | As the unsupervised model was established | 1) Parallel runs with different random initializations gave similar results. 2) Altering the key parameters delivered robust observations. | 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 |
|---|---|---|---|
| The technical noise in single-cell data might cause inaccuracy. | Scientific community who intends to apply this method to raw single-cell data. | Adequate | |
5. Version control
| Current Conformance Level / Target Conformance Level |
|---|
| Extensive |
| Naming Conventions? | Repository? | Code Review? | |
|---|---|---|---|
| individual modeler | Yes | Yes | peers |
| within the lab | Yes | Yes | peers |
| collaborators | Yes | Yes | via regular meetings |
6. Documentation
| Current Conformance Level / Target Conformance Level | |
|---|---|
| Code commented? | Adequate |
| 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 | package: https://github.com/sqjin/scAI | package: https://github.com/sqjin/scAI | |
| Results | Shared folders | Paper and tutorials | |
| Implications of results |
8. Independent reviews
| Current Conformance Level / Target Conformance Level |
|---|
| To be done |
| 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 method has been compared to several other commonly used methods on benchmark datasets. |
| 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 single-cell data. |
| How do your modeling efforts conform? | Common data preprocessing procedures are followed. |