RNAi

Cancer gene dependency maps help reveal proteins' relationships

tulrich@broadinstitute.org — Wed, 16 May 2018 15:15:29 +0000

Upgraded computational tool boosts search for cancer vulnerabilities

By Tom Ulrich November 5, 2018

Upgraded computational tool boosts search for cancer vulnerabilities

Using a new model dubbed DEMETER2, the ӳ��ý's Cancer Dependency Map team has compiled the largest dataset of genetic dependencies in cancer to date.

By Tom Ulrich

November 5, 2018

DEMETER2 improves on the original DEMETER model in three significant ways:

It controls for technical differences between screening experiments, which otherwise complicate efforts to merge data across cell lines and different screening datasets.
It provides metrics for assessing the confidence of identified genetic dependencies.
Instead of grading each gene's dependency scores on a curve (relative to other cell lines for each gene), it reports them in absolute terms that can be more readily compared.

The unified dataset is openly available to the cancer research community via the DepMap portal. The code for DEMETER2 is available on GitHub.

This work received support from the Slim Initiative in Genomic Medicine for the Americas (SIGMA), a joint U.S.-Mexico project funded by the Carlos Slim Foundation, and other sources.

Paper(s) cited

Tags:

The transformative power of CRISPR in the lab, with John Doench and Ruth Hanna

kzusi@broadinstitute.org — Tue, 27 Mar 2018 17:06:39 +0000

Upgraded computational tool boosts search for cancer vulnerabilities

By Tom Ulrich November 5, 2018

Upgraded computational tool boosts search for cancer vulnerabilities

Using a new model dubbed DEMETER2, the ӳ��ý's Cancer Dependency Map team has compiled the largest dataset of genetic dependencies in cancer to date.

By Tom Ulrich

November 5, 2018

DEMETER2 improves on the original DEMETER model in three significant ways:

It controls for technical differences between screening experiments, which otherwise complicate efforts to merge data across cell lines and different screening datasets.
It provides metrics for assessing the confidence of identified genetic dependencies.
Instead of grading each gene's dependency scores on a curve (relative to other cell lines for each gene), it reports them in absolute terms that can be more readily compared.

The unified dataset is openly available to the cancer research community via the DepMap portal. The code for DEMETER2 is available on GitHub.

This work received support from the Slim Initiative in Genomic Medicine for the Americas (SIGMA), a joint U.S.-Mexico project funded by the Carlos Slim Foundation, and other sources.

Paper(s) cited

Tags:

Here there be dependencies: Putting cancers’ vulnerabilities on the map

tulrich@broadinstitute.org — Thu, 27 Jul 2017 16:05:26 +0000

Upgraded computational tool boosts search for cancer vulnerabilities

By Tom Ulrich November 5, 2018

Upgraded computational tool boosts search for cancer vulnerabilities

Using a new model dubbed DEMETER2, the ӳ��ý's Cancer Dependency Map team has compiled the largest dataset of genetic dependencies in cancer to date.

By Tom Ulrich

November 5, 2018

DEMETER2 improves on the original DEMETER model in three significant ways:

It controls for technical differences between screening experiments, which otherwise complicate efforts to merge data across cell lines and different screening datasets.
It provides metrics for assessing the confidence of identified genetic dependencies.
Instead of grading each gene's dependency scores on a curve (relative to other cell lines for each gene), it reports them in absolute terms that can be more readily compared.

The unified dataset is openly available to the cancer research community via the DepMap portal. The code for DEMETER2 is available on GitHub.

This work received support from the Slim Initiative in Genomic Medicine for the Americas (SIGMA), a joint U.S.-Mexico project funded by the Carlos Slim Foundation, and other sources.

Paper(s) cited

Tags: