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Running
on
CPU Upgrade
Andrew Stirn
commited on
Commit
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8932957
1
Parent(s):
7c86dc4
numpy fix
Browse files- requirements.txt +1 -0
- tiger.md +1 -1
requirements.txt
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@@ -1,4 +1,5 @@
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biopython==1.80
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pandas==1.5.2
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tensorflow==2.11.0
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tensorflow-probability==0.19.0
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biopython==1.80
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pandas==1.5.2
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numpy==1.26.4
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tensorflow==2.11.0
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tensorflow-probability==0.19.0
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tiger.md
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@@ -24,7 +24,7 @@ The tool has three run modes:
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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 a higher `Guide Score` (closer to 1) corresponds to *more* likely off-target effects.
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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.
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The tool uses Gencode
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Due to computational limitations, the online tool only supports off-target predictions for the top 10 most active, on-target gRNAs per transcript.
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### Future Development Plans
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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 a higher `Guide Score` (closer to 1) corresponds to *more* likely off-target effects.
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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.
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The tool uses Gencode v47 (protein-coding and non-coding RNAs) to identify potential off-target transcripts.
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Due to computational limitations, the online tool only supports off-target predictions for the top 10 most active, on-target gRNAs per transcript.
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### Future Development Plans
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