ready to go live

app.py

@@ -98,7 +98,7 @@ if __name__ == '__main__':
         st.session_state.off_target = None
 
     # title and documentation
-    st.markdown(Path('tiger.md').read_text())
+    st.markdown(Path('tiger.md').read_text(), unsafe_allow_html=True)
     st.divider()
 
     # mode selection

tiger.md

@@ -1,17 +1,17 @@
-## TIGER Tool for Cas13 Efficacy Prediction
+## TIGER Online Tool for Cas13 Efficacy Prediction
 
-Welcome to TIGER! This online tool accompanies our *Nature Biotechnology* article.
+Welcome to TIGER!
+This online tool accompanies our recent study from the labs of [David Knowles](https://daklab.github.io/) and [Neville Sanjana](http://sanjanalab.org/).
 TIGER's ability to make accurate on- and off-target predictions enables users to 1) design highly effective gRNAs and 2) precisely modulate transcript expression by engineered gRNA-target mismatches. 
 
-If you use TIGER, please consider citing our study:
-> Wessels, H.-H., Stirn, A., Méndez-Mancilla, A., Kim, E. J., Hart, S. K., Knowles, D. A., & Sanjana, N. E. (2023). Prediction of on-target and off-target activity of CRISPR–Cas13d guide RNAs using deep learning. Nature Biotechnology. https://doi.org/10.1038/s41587-023-01830-8
-
+If you use the TIGER Online Tool in your study, please consider citing:
+> **[Prediction of on-target and off-target activity of CRISPR–Cas13d guide RNAs using deep learning](http://sanjanalab.org/reprints/WesselsStirn_NBT_2023.pdf).** Wessels, H.-H.<sup>\*</sup>, Stirn, A.<sup>\*</sup>, Méndez-Mancilla, A., Kim, E. J., Hart, S. K., Knowles, D. A.<sup>#</sup>, & Sanjana, N. E.<sup>#</sup> *Nature Biotechnology* (2023).  [https://doi.org/10.1038/s41587-023-01830-8](https://doi.org/10.1038/s41587-023-01830-8)
 
 Please note that this precompiled, online tool differs from the manuscript slightly.
-First, this version of TIGER predicts using just target and guide sequence (see Figure 3c). Second, we map TIGER's predictions to the unit interval to make estimates more interpretable: a Guide Score close to 1 corresponds to high gRNA activity (i.e. desirable for on-target guides).
-A Guide Score near 0 denotes no/minimal activity (i.e. desirable for off-target effects).
+First, this version of TIGER predicts using just target and guide sequence (see [Figure 3c](http://sanjanalab.org/reprints/WesselsStirn_NBT_2023.pdf)). Second, we map TIGER's predictions to the unit interval (0,1) to make estimates more interpretable: A `Guide Score` close to 1 corresponds to high gRNA activity (i.e. desirable for on-target guides).
+A `Guide Score` near 0 denotes no/minimal activity (i.e. desirable for predicted off-targets to minimize the activity of these gRNAs on unintended targets).
 This transformation is monotonic and therefore preserves Spearman, AUROC, and AUPRC performance.
-These estimates (transformations of log-fold-change predictions from TIGER) appear in the "Guide Score" column of this online tool’s output.
+These estimates (transformations of log-fold-change predictions from TIGER) appear in the `Guide Score` column of this online tool’s output.
 
 ### Using the TIGER Online Tool
 
@@ -20,11 +20,12 @@ The tool supports two methods for transcript entry:
 2) Uploading a FASTA file that can contain one or more transcripts. Each transcript **must** have a unique ID.
 
 The tool has three run modes:
-- Report all on-target gRNAs for each provided transcript. This mode does not support off-target identification.
-- Report the top 10 most active, on-target gRNAs for each provided transcript. This mode allows for the optional identification of off-target effects.
-- Report the top 10 most active, on-target gRNAs for each provided transcript and their titration candidates (all possible single mismatches). Larger guide scores correspond to more transcript knockdown. This mode also does not support off-target identification.
+1) Report all on-target gRNAs for each provided transcript.
+2) Report the top 10 most active, on-target gRNAs for each provided transcript. This mode allows for the optional identification of off-target effects. For off-target avoidance, please note that higher a `Guide Score` (closer to 1) corresponds to *more* likely off-target effects.
+3) Report the top 10 most active, on-target gRNAs for each provided transcript and their titration candidates (all possible single mismatches). A higher `Guide Score` (closer to 1) corresponds to greater transcript knockdown. 
 
-The tool uses version 19 of Gencode (protein-coding and lncRNA) to identify off-target candidates.
+The tool uses Gencode v19 (protein-coding and non-coding RNAs) to identify potential off-target transcripts.
+Due to computational limitations, the online tool only supports off-target predictions for the top 10 most active, on-target gRNAs per transcript.
 
 ### Future Development Plans
 
@@ -34,4 +35,9 @@ The tool uses version 19 of Gencode (protein-coding and lncRNA) to identify off-
 - Incorporate non-scalar features (target accessibility, hybridization energies, etc...)
 
 To report bugs or to request additional features, please click the "Community" button in the top right corner of this screen and start a new discussion.
-Alternatively, please email [Andrew Stirn](mailto:andrew.stirn@cs.columbia.edu).
+Alternatively, please email [Andrew Stirn](mailto:andrew.stirn@cs.columbia.edu).
+
+#### Version
+You are using version 1.0 of this tool.
+We will increment the major number when a change causes a difference in predictions (e.g. retraining the model).
+We will otherwise increment the minor number (e.g. changes to the user interface, speed improvements, etc...).