12. GiniClust: a method for detecting rare cell types from single-cell gene expression data

Reference (tentative): Jiang L, Chen H, Pinello L, Yuan GC. GiniClust: Detecting rare cell types from single-cell gene expression data with Gini Index. Genome Biology (in press).

[Link to GitHub]

11. New Version! CRISPResso: a software package for analyzing deep-sequencing CRISPR-Cas9 genome editing outcome data

Reference (tentative): Pinello L, Canver MC, Hoban MD, Orkin SH, Kohn DB, Bauer DE#, Yuan GC#. CRISPResso: sequencing analysis toolbox for CRISPR-Cas9 genome editing. bioRxiv. doi: http://dx.doi.org/10.1101/031203. [ paper ]

[Link to GitHub]

[Link to Web Application]

10. ECLAIR: a method for robust lineage reconstruction from single-cell gene expression data

Reference: Giecold G, Marco E, Trippa L, Yuan GC. Robust Lineage Reconstruction from High-Dimensional Single-Cell Data. Nucleic Acids Res. 2016 May 20. pii: gkw452. [ paper ]

[Link to GitHub]

9. HubPredictor: a method for predicting chromatin interaction hubs using histone marks information.

Reference: Huang J, Marco E, Pinello L, Yuan GC. Predicting chromatin organization using histone marks.Genome Biol. 2015 Aug 14;16(1):162. [ paper ]

[Link to GitHub]

8. SCUBA: a method for extracting lineage relationships and modeling gene expression dynamics from single-cell gene expression data.

Reference: Marco E, Karp RL, Guo G, Robson P, Hart AH, Trippa L, Yuan GC. Bifurcation analysis of single-cell gene expression data reveals epigenetic landscape. Proc Natl Acad Sci U S A. 2014 Dec 30;111(52):E5643-50. [paper]

[Link to GitHub]

7. Haystack: A method for quantifying epigenetic variability and prediction of driving transcription factors

Reference: Pinello L, Xu J, Orkin SH, Yuan GC. Analysis of chromatin-state plasticity identifies cell-type-specific regulators of H3K27me3 patterns.Proc Natl Acad Sci U S A. 2014 Jan 21;111(3):E344-53. [ paper ]

[ Link to Github ]

6. PANDA: a message-passing method for gene regulatory network reconstruction

Reference: Glass K, Huttenhower C, Quackenbush J, Yuan GC. Passing Messages between Biological Networks to Refine Predicted Interactions. PLOS ONE. 2013 May 31, 8(5), e64832. [paper]

[Link to SourceForge]

5. MAnorm: a robust model for quantitative comparison of ChIP-seq datasets

Reference: Shao Z, Zhang Y, Yuan GC., Orkin SH, Waxman DJ. MAnorm: a robust model for quantitative comparison of ChIP-Seq data sets. Genome Biology. 2012 Mar 16;13(3):R16. [paper]

[Software page]

4. MIM (Motif-Independent Metric) for sequence specificity

Reference: Pinello L, Lo Bosco G, Hanlon B, Yuan GC. A motif-independent metric for DNA sequence specificity. BMC Bioinformatics. 2011 Oct 21;12:408. [paper]

[Link to Github].

3. A hidden Markov model for identifying chromatin domains from multiple histone modificaiton data

Reference: Larson JL, Yuan GC. Epigenetic domains found in mouse embryonic stem cells via a hidden Markov model. BMC Bioinformatics. 2010 Nov 12;11:557. [paper]

[ Download Matlab and R codes].

2. N-score: a wavelet analysis based model for predicting nucleosome positions from DNA sequence information.


2a) Yuan GC, Liu JS. Genomic sequence is highly predictive of local nucleosome depletion. PLoS Computational Biology 2008. doi:10.1371/journal.pcbi.0040013.eor) [paper]

2b) Yuan GC. Targeted recruitment of histone modifications in humans predicted by genomic sequences. J Comput Biol 2009 Feb;16(2):341-355. [paper]

Download the latest and faster version in python (written by Yijing Zhang and Luca Pinello)

Download MATLAB source code

Download predicted nucleosome position: This is based on the 2003 version of yeast genome (Download fasta files)

1. A hidden Markov model for extracting nucleosome positions from tiling array data.

Reference: Yuan GC, Liu YJ, Dion MF, Slack MD, Wu LF, Altschuler SJ, Rando OJ.  Genome-scale identification of nucleosome positions in S. Cerevisiae.  Science 2005;309(5734):626-630 [paper]

Download MATLAB source code