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Cellpanelr: identify predictive biomarkers from cell line panel response data

Wassarman, D. R.; Wu, T.; Shokat, K.

2022-11-04 bioinformatics
10.1101/2022.11.02.514913 bioRxiv
Show abstract

SummaryCellpanelr is an open-source R package and web application for analyzing user-generated cell panel screens using DepMap data sets. Cellpanelr can be used to identify mutation and expression biomarkers of cell line response, increasing the value and accessibility of cell panel experiments such as relative sensitivities to cancer drugs. Availability and implementationHosted web application is available from shinyapps.io (https://dwassarman.shinyapps.io/cellpanelr). Source code and installation instructions are available from GitHub (https://github.com/dwassarman/cellpanelr). Contactdwassar@gmail.com

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The top 9 journals account for 50% of the predicted probability mass.

1
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4.0%
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Top 4%
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9
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Top 10%
2.6%
50% of probability mass above
10
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◐ 242 papers in training set
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2.6%
11
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Top 2%
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12
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2.4%
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14
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Top 42%
2.1%
15
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Top 8%
2.1%
16
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Top 1%
1.9%
17
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Top 0.3%
1.7%
18
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Top 4%
1.7%
19
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Top 2%
1.1%
20
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Top 0.3%
1.1%
21
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○ 53 papers in training set
Top 1%
1.1%
22
PLOS ONE
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Top 55%
1.0%
23
eLife
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1.0%
24
Nature Methods
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Top 6%
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Top 0.7%
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● 130 papers in training set
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GigaScience
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Top 5%
0.6%
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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.