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WBS Document:
Delegates tasks in a temporal manner with actionable items. The tasks are split into activities that are feasible and accomplishable.
Makes use of multiple packages ( SCENIC, RSHINY, BITFAM, Dorothea)
Details the output of each analysis with use friendliness in mind
Data visualizations are also taken into account
Comment: Workflow is clear and concise, activities are split into manageable tasks.
Materials:
Working with scRNA-Seq data, specifically 4 datasets ( breast cancer, colon cancer, lung cancer, ovarian cancer).
Three different software requirement specification documents. Document SRS doc 3 is the most detailed document, introducing the software package and its utilization for a user.
Comments:
Very well thought out project, WBS document and SDS documents are informative and clear.
I recommend making a single document consisting of the necessary inputs for all the different packages you will run and their outputs. This will enable the user to identify different data types necessary to use your package and ascertain what outputs they will be comparing. This is a small detail but one page takeaway might help the user feel prepared to begin analysis if they can check what they need.
Progress has been made on subsetting the data, writing a function and testing that it works.
Are there transcription that are known to be dysregulated across all cancers (cancer agnostic) and some that specific to each cancer you are investigating? Very cool to test the accuracy of the different trancription inference programs and converge on the output that is the same across programs ( computational). From a biology perspective are you able to identify a transcription factor network that is common in all 4 cancer datasets you are utilizing ( a cancer transcription factor network signature ?) Potentially look into Chip-Seq data as a validation step of findings?
Code and Test File:
R code reading in data, normalization of data, initial run of BITFAM
Test Code: Checking raw counts of scRNA-seq is present and that normalization of data was performe
)
The goals of this project can be achieved and progress has been made :)
The text was updated successfully, but these errors were encountered:
WBS Document:
Delegates tasks in a temporal manner with actionable items. The tasks are split into activities that are feasible and accomplishable.
Makes use of multiple packages ( SCENIC, RSHINY, BITFAM, Dorothea)
Details the output of each analysis with use friendliness in mind
Data visualizations are also taken into account
Comment: Workflow is clear and concise, activities are split into manageable tasks.
Materials:
Working with scRNA-Seq data, specifically 4 datasets ( breast cancer, colon cancer, lung cancer, ovarian cancer).
Three different software requirement specification documents. Document SRS doc 3 is the most detailed document, introducing the software package and its utilization for a user.
Comments:
Very well thought out project, WBS document and SDS documents are informative and clear.
I recommend making a single document consisting of the necessary inputs for all the different packages you will run and their outputs. This will enable the user to identify different data types necessary to use your package and ascertain what outputs they will be comparing. This is a small detail but one page takeaway might help the user feel prepared to begin analysis if they can check what they need.
Progress has been made on subsetting the data, writing a function and testing that it works.
Are there transcription that are known to be dysregulated across all cancers (cancer agnostic) and some that specific to each cancer you are investigating? Very cool to test the accuracy of the different trancription inference programs and converge on the output that is the same across programs ( computational). From a biology perspective are you able to identify a transcription factor network that is common in all 4 cancer datasets you are utilizing ( a cancer transcription factor network signature ?) Potentially look into Chip-Seq data as a validation step of findings?
Code and Test File:
R code reading in data, normalization of data, initial run of BITFAM
Test Code: Checking raw counts of scRNA-seq is present and that normalization of data was performe
)
The text was updated successfully, but these errors were encountered: