Li Lab:Softwares

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* Whole Genome Phylogeny
 
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Phylogeny Based on Whole Genome as inferred from Complete Information Set Analysis
 
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*[http://genome.dfci.harvard.edu/~xsliu/HMMTiling/ HMMTiling]
 
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A Hidden Markov Model for Analyzing ChIP-chip Experiments on Genome Tiling Arrays
 
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*[http://chip.dfci.harvard.edu/~wli/MAT/ Model-based Analysis of Tiling-array (MAT)]
*[http://chip.dfci.harvard.edu/~wli/MAT/ Model-based Analysis of Tiling-array (MAT)]
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* [http://code.google.com/p/bsmap/ BSMAP: whole genome Bisulfite Sequence MAPping program]  
* [http://code.google.com/p/bsmap/ BSMAP: whole genome Bisulfite Sequence MAPping program]  
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Bisulfite sequencing is a powerful technique to study DNA cytosine methylation.  Bisulfite treatment followed by PCR amplification specifically converts unmethylated cytosines to thymine.  Coupled with next generation sequencing technology, it is able to detect the methylation status of every cytosine in the genome.  However, mapping high-throughput bisulfite reads to the reference genome remains a great challenge due to the increased searching space, reduced complexity of bisulfite sequence, asymmetric cytosine to thymine alignments, and multiple CpG heterogeneous methylation. We developed an efficient bisulfite reads mapping algorithm BSMAP to address the above issues.  BSMAP combines genome hashing and bitwise masking to achieve fast and accurate bisulfite mapping.  Compared with existing bisulfite mapping approaches, BSMAP is faster, more sensitive and more flexible.  BSMAP is the first general-purpose bisulfite mapping software.  It is able to map high-throughput bisulfite reads at whole genome level with feasible memory and CPU usage. It is freely available under GPL v3 license at http://code.google.com/p/bsmap/.<math>Insert formula here</math>
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BSMAP is the first general-purpose bisulfite mapping software.  It is able to map high-throughput bisulfite reads at whole genome level with feasible memory and CPU usage.
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* [http://code.google.com/p/rseqc/ RSeQC: Quality Control of RNA-seq experiments]
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RseQC comprehensively evaluatse different aspects of RNA-seq experiments, such as sequence quality, GC bias, PCR bias, nucleotide composition bias, sequencing depth, strand specificity, coverage uniformity, and read distribution over the genome structure.
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* [http://code.google.com/p/danpos/ DANPOS: Dynamic Analysis of Nucleosome Position and Occupancy by Sequencing]
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DANPOS is specifically developed for comparison between nucleosome maps generated based on high-throughput sequencing, it detects changes in nucleosome position, occupancy, or fuzziness at single nucleotide resolution.
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* [http://code.google.com/p/cpat/ CPAT: Coding-Potential Assessment Tool Using an Alignment-Free Logistic Regression Model]
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* [http://code.google.com/p/msuite/ BSMEAT: whole genome Bisulfite Sequencing based dna MEthylatino Analysis Tools]
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* [http://code.google.com/p/dychips/ DyChIPS: An integrate solution for dynamic analysis of ChIP-sequencing]
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DyChIPS is designed for comparative analysis of ChIPSeq data whose targets tend to be broad and are widely distributed across the genome,  such as histone modification or some chromatin-binding proteins.

Revision as of 22:29, 12 October 2012

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A model-based algorithm for finding enriched regions in ChIP-Chip experiments


An integrated webserver for analyzing ChIP-chip data


A intuitive and efficient algorithm for the mapping of millions of query oligonucleotide fragments to the genome of any given length, at least an order of magnitude faster than other popular existing tools


A model-based algorithm for finding enriched regions in ChIP-Seq experiments.


BSMAP is the first general-purpose bisulfite mapping software. It is able to map high-throughput bisulfite reads at whole genome level with feasible memory and CPU usage.


RseQC comprehensively evaluatse different aspects of RNA-seq experiments, such as sequence quality, GC bias, PCR bias, nucleotide composition bias, sequencing depth, strand specificity, coverage uniformity, and read distribution over the genome structure.


DANPOS is specifically developed for comparison between nucleosome maps generated based on high-throughput sequencing, it detects changes in nucleosome position, occupancy, or fuzziness at single nucleotide resolution.




DyChIPS is designed for comparative analysis of ChIPSeq data whose targets tend to be broad and are widely distributed across the genome, such as histone modification or some chromatin-binding proteins.
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