1 / 16

L1KProcs: an R package for L1000 data processing and analysis

L1KProcs: an R package for L1000 data processing and analysis. Chenglin Liu , Kun Wei and Jing Su Center for Bioinformatics and Systems Biology Wake Forest School of Medicine. Overview. L1KProcs.

jela
Download Presentation

L1KProcs: an R package for L1000 data processing and analysis

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. L1KProcs: an R package for L1000 data processing and analysis Chenglin Liu , Kun Wei and Jing Su Center for Bioinformatics and Systems Biology Wake Forest School of Medicine

  2. Overview

  3. L1KProcs • L1KProcs is an R package and interface for LINCS L1000 data preprocessing and compound signature detection in both text-mode and graphic-mode way. • Additionally, it is a library for existing L1000 processed expression data and their connections (EGEM library).

  4. L1KProcs • Operating system: • Windows XP, Windows 7, Linux, Mac OS X • Open source • R language based (R>=3.0) • Parallel computing • Require doParallel package • Access • download, web

  5. Function I: preprocessing

  6. How to Use • Required Input: the location of raw L1000 data • Optional Input: • target: quantile normalization • ifAll: if convert the landmark gene expression to whole genome data • nthread: number of parallel computing • plot: data quality visualization • Output: • The processed data saved in outpath. • The information of the data including the qualities and the control wells in class listlstPlateInfo.

  7. data quality visualization

  8. Single well peak calling and visualization

  9. Function II: EGEM matrix • Required Input • cpdata: LFC after compound treatments • Optional Input • LINCS: • if TRUE, specify the name of the existing EGEM library lib.name • otherwise, provide the LFC after knockdown treatments • nthread: number of parallel computing • Output • The EGEM matrix and annotations

  10. Function II: EGEM matrix

  11. Function III: Compound Signature Discovery • Required Input • The output of Function II egem.info. • The range of signature number pNo. • Optional Input • nthread: number of parallel computing • Output: • Signature number k • Compounds and signature genes.

  12. Function III: Compound Signature Discovery

  13. L1KProcs Interface

  14. L1000 preprocessing Choose one raw L1000 data Upload and start computing

  15. Compound Signature Discovery nthread • start computing

  16. Single well peak calling visualization

More Related