Person:
Lee, Soohyun

Loading...
Profile Picture

Email Address

AA Acceptance Date

Birth Date

Research Projects

Organizational Units

Job Title

Last Name

Lee

First Name

Soohyun

Name

Lee, Soohyun

Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    Publication
    A comparison of genetically matched cell lines reveals the equivalence of human iPSCs and ESCs
    (2016) Choi, Jiho; Lee, Soohyun; Clement, Kendell; Mallard, William; Tagliazucchi, Guidantonio Malagoli; Lim, Hotae; Choi, In Young; Ferrari, Francesco; Tsankov, Alex; Pop, Ramona; Lee, Gabsang; Rinn, John; Meissner, Alexander; Park, Peter; Hochedlinger, Konrad
  • Thumbnail Image
    Publication
    EMSAR: estimation of transcript abundance from RNA-seq data by mappability-based segmentation and reclustering
    (BioMed Central, 2015) Lee, Soohyun; Seo, Chae Hwa; Alver, Burak Han; Lee, Sanghyuk; Park, Peter
    Background: RNA-seq has been widely used for genome-wide expression profiling. RNA-seq data typically consists of tens of millions of short sequenced reads from different transcripts. However, due to sequence similarity among genes and among isoforms, the source of a given read is often ambiguous. Existing approaches for estimating expression levels from RNA-seq reads tend to compromise between accuracy and computational cost. Results: We introduce a new approach for quantifying transcript abundance from RNA-seq data. EMSAR (Estimation by Mappability-based Segmentation And Reclustering) groups reads according to the set of transcripts to which they are mapped and finds maximum likelihood estimates using a joint Poisson model for each optimal set of segments of transcripts. The method uses nearly all mapped reads, including those mapped to multiple genes. With an efficient transcriptome indexing based on modified suffix arrays, EMSAR minimizes the use of CPU time and memory while achieving accuracy comparable to the best existing methods. Conclusions: EMSAR is a method for quantifying transcripts from RNA-seq data with high accuracy and low computational cost. EMSAR is available at https://github.com/parklab/emsar Electronic supplementary material The online version of this article (doi:10.1186/s12859-015-0704-z) contains supplementary material, which is available to authorized users.