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A compilation and categorization of next-generation sequencing resources : ChIP seq analysis
Resources Important features / utilities*CitationsYear of publicationRank by usage frequency Click to Edit / Add comments
Avadis NGS
http://www.avadis-ngs.com/
1. It is used for data analysis, visualization, and management of data generated by next-generation sequencing (NGS) platforms. 2. It has the following features integrated with the software: a) Genome browser (visualize sequenced reads on complete genome). b) Variant support view (which lists the SNPs and small InDels that were detected during SNP analysis). c) Pathway analysis (how genes interact with each other). d) Alternative splicing analysis e) SNP detection f) BIOBASE genome Trax (can be accessed within Avadis NGS).
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96
Free trial version is available for 20 days.
NPS - Nucleosome Positioning from Sequencing
http://liulab.dfci.harvard.edu/NPS/
1. It is a software which can identify nucleosome position of a histone modification at the nucleosome level from the chip seq data. 2. It uses poisson distribution for the p-value estimation for histone modification.
Zhang Y, Shin H, Song JS, Lei Y, Liu XS. Identifying positioned nucleosomes with epigenetic marks in human from ChIP-Seq. BMC Genomics. 2008 Nov 13;9:537. PubMed PMID: 19014516; PubMed Central PMCID: PMC2596141.
2008
96
PeakSeq
http://info.gersteinlab.org/PeakSeq
It is used to identify and rank the peak regions in chip seq analysis.
Rozowsky J, Euskirchen G, Auerbach RK, Zhang ZD, Gibson T, Bjornson R,Carriero N, Snyder M, Gerstein MB. PeakSeq enables systematic scoring of ChIP-seq experiments relative to controls. Nat Biotechnol. 2009 Jan;27(1):66-75. Epub 2009 Jan 4. PubMed PMID: 19122651; PubMed Central PMCID: PMC2924752.
2009
96
Batman - A Bayesian Tool for Methylation Analysis
http://td-blade.gurdon.cam.ac.uk/software/batman/
1) It is a new, robust algorithm which relies on the effect of varying densities of methylated CpGs on MeDIP enrichment. 2) It performs DNA methylome analyses, as it will allow more effective profiling, including CpG-poor regions.
Down TA, Rakyan VK, Turner DJ, Flicek P, Li H, Kulesha E, Gräf S, Johnson N, Herrero J, Tomazou EM, Thorne NP, Bäckdahl L, Herberth M, Howe KL, Jackson DK, Miretti MM, Marioni JC, Birney E, Hubbard TJ, Durbin R, Tavaré S, Beck S. A Bayesian deconvolution strategy for immunoprecipitation-based DNA methylome analysis. Nat Biotechnol. 2008 Jul;26(7):779-85. PubMed PMID: 18612301; PubMed Central PMCID: PMC2644410.
2008
100
BayesPeak
http://www.compbio.group.cam.ac.uk/Resources/BayesPeak/csbayespeak.html
1. It is used to find transcription factor binding site and histone data. 2. It uses Markov model to detect certain locations.
Cairns J, Spyrou C, Stark R, Smith ML, Lynch AG, Tavaré S. BayesPeak- an R package for analysing ChIP-seq data. Bioinformatics. 2011 Mar 1;27(5):713-4. Epub 2011 Jan 17. PubMed PMID: 21245054; PubMed Central PMCID: PMC3042177.
2011
100
CisGenome Browser
http://www.stanford.edu/group/wonglab/jiangh/browser/
1. An open source, platform independent tool, called CisGenome Browser, which can work together with any other data analysis program to serve as a flexible component for genomic data visualization. 2. It can also work by itself as a standalone genome browser. CisGenome Browser is a convenient tool for data sharing between labs. 3. It has features that are specifically designed for ultra high-throughput sequencing data visualization. 4. CisGenome Browser is suitable for visualizing microarray/sequencing/other biological data. It runs locally so that there is no need to upload the user data via internet like adding custom tracks when using UCSC Genome Browser or any other online browsers.
Jiang H, Wang F, Dyer NP, Wong WH. CisGenome Browser: a flexible tool for genomic data visualization. Bioinformatics. 2010 Jul 15;26(14):1781-2. Epub 2010 May 30. PubMed PMID: 20513664; PubMed Central PMCID: PMC2894522.
2010
100
edgeR - Empirical analysis of digital gene expression data in R
http://www.bioconductor.org/packages/release/bioc/html/edgeR.html
It can be used to find differential gene expression and count data from next generation sequencing platforms.
Not available
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100
ERANGE
http://woldlab.caltech.edu/rnaseq/
1. It can perform both RNA seq analysis and ChIP seq analysis. 2. It can also perform allele specific transcription.
Mortazavi A, Williams BA, McCue K, Schaeffer L, Wold B. Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat Methods. 2008 Jul;5(7):621-8. Epub 2008 May 30. PubMed PMID: 18516045.
2008
100
FindPeaks
http://sourceforge.net/apps/mediawiki/vancouvershortr/index.php?title=FindPeaks
1. Used for genomics, SNP discovery. 2. Contains the 'FindPeaks' application for Chip-Seq and RNA-Seq analysis. 3. It has a nascent database for storing SNPs across multiple libraries.
Fejes, AP, Robertson, G, Bilenky, M, Varhol, R, Bainbridge, M, Jones, SJ (2008). FindPeaks 3.1: a tool for identifying areas of enrichment from massively parallel short-read sequencing technology. Bioinformatics, 24, 15:1729-30.[PMID: 18599518]
2008
100
Galaxy
http://main.g2.bx.psu.edu/
1. It is an open web based software to perform computational analysis of genomic data. 2. It allows user to repeat, store and annotate the analysized data in an interactive web based format. 3. It has tools for QC and manipulation, mapping tools like Bowtie (Illumina, SOLiD), LASTZ, Megablast (Roche 454), BWA (Illumina, SOLiD), SAMTools, TopHat, Cufflinks for RNA analysis. 4. It doesn't need any programming knowledge.
Taylor J, Schenck I, Blankenberg D, Nekrutenko A. Using galaxy to perform large-scale interactive data analyses. Curr Protoc Bioinformatics. 2007 Sep;Chapter 10:Unit 10.5. PubMed PMID: 18428782.
2007
100
GenoMiner
http://www.astridbio.com/genominer.html
1. GenoMiner comes with a great number of software tools for de novo and reference assembly, as well as many other applications for secondary and tertiary analysis of NGS data. 2. It also has a user friendly graphical interface with wizard-like pipelines for preprocessing, reference assembly, de novo assembly, ChIPSeq analysis and other miscellaneous bioinformatics tasks.
Castrignano T, De Meo PD, Grillo G, Liuni S, Mignone F, Talamo IG, Pesole G. GenoMiner: a tool for genome-wide search of coding and non-coding conserved sequence tags. Bioinformatics. 2006 Feb 15;22(4):497-9. Epub 2005 Nov 2. PubMed PMID: 16267081.
2006
100
GMS - Genomatix Mining Station
http://www.genomatix.de/en/index.html
1. It has highest quality results within shortest time. 2. Used in RNA-Seq, non-coding RNA-Seq, assembly, SNP discovery and ChIP-Seq analysis. 3. Allows multiple insertions or deletions, maps genomes and transcriptomes of 25 organisms. 4. It supports sequence and color-based tags from Illumina (Genome Analyzer and HiSeq), SOLiD, Helicos and 454 Life Sciences Sequencers.
Not available
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100
HPeak
http://www.sph.umich.edu/csg/qin/HPeak
1. It is a tool used to find DNA regions where proteins bind. 2. It has better preference over other ChIP seq analysis tools. 3. It is highly sensitive and specific.
Qin ZS, Yu J, Shen J, Maher CA, Hu M, Kalyana-Sundaram S, Yu J, Chinnaiyan AM. HPeak: an HMM-based algorithm for defining read-enriched regions in ChIP-Seq data. BMC Bioinformatics. 2010 Jul 2;11:369. PubMed PMID: 20598134; PubMed Central PMCID: PMC2912305.
2010
100
MACS - Model based Analysis of ChIP-Seq
http://liulab.dfci.harvard.edu/MACS/
1. MACS is Model based Analysis of ChIP Seq. 2. It is used to find the binding site on DNA fragments.
Zhang Y, Liu T, Meyer CA, Eeckhoute J, Johnson DS, Bernstein BE, Nusbaum C, Myers RM, Brown M, Li W, Liu XS. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 2008;9(9):R137. Epub 2008 Sep 17. PubMed PMID: 18798982; PubMed Central PMCID: PMC2592715.
2008
100
MICSA - Motif Identication for Chip-Seq Analysis
http://bioinfo-out.curie.fr/projects/micsa/
1. MICSA is a motif identification for chip seq analysis tool which identifies functional binding sites of transcription factors of a consensus motif. 2. It can find the motifs from de novo TFBS and functional binding sites using information on motif occurrence in peaks with coverage depth. 3. It can allow users to significantly reduce the false positive predictions for TFBSs in chip seq analysis.
Boeva V, Surdez D, Guillon N, Tirode F, Fejes AP, Delattre O, Barillot E. De novo motif identification improves the accuracy of predicting transcription factor binding sites in ChIP-Seq data analysis. Nucleic Acids Res. 2010 Jun;38(11):e126. Epub 2010 Apr 7. PubMed PMID: 20375099; PubMed Central PMCID: PMC2887977.
2010
100
MochiView
http://johnsonlab.ucsf.edu/sj/mochiview-start/
1. MochiView is Java software that integrates browsing of genomic sequences, features, and data with DNA motif visualization and analysis. 2. It is a highly flexible and intuitive interface that allows one to easily import, visualize, explore, and analyze large sets of data, such as those generated from ChIP experiments. 3. MochiView uses an integrated local database to manage all of the data imported by the user, such as genome sequences and alignments, gene locations, microarray probe locations, expression data, ChIP data, and motif libraries.
Homann OR, Johnson AD. MochiView: versatile software for genome browsing and DNA motif analysis. BMC Biol. 2010 Apr 21;8:49. PubMed PMID: 20409324; PubMed Central PMCID: PMC2867778.
2010
100
Requires installation of Bowtie, SAMTools, TopHat, polyHap2 in the path.
Novoalign
http://www.novocraft.com/main/index.php
1. Alignment tool for aligning short sequences against an indexed set of reference sequences. 2. Aligning Illumina single-end and paired-end reads. 3. Gapped alignment on single-end reads and paired-end reads 4. Single pass alignment for Bisulphite treated DNA.
Not available
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100
QSeq
http://www.dnastar.com/t-nextgen-qseq.aspx
1. QSeq is DNASTAR's Next-Gen application for RNA-Seq, ChIP-Seq, and miRNA alignment and visualize Genomes with High Capacity, High Speed Assembler. 2. QSeq is fully integrated with ArrayStar, enabling you to take advantage of its powerful visualization and analytical tools, including, using Gene Ontology (GO) annotations for ontology comparisons and gene characterization. 3. Using QSeq, researchers can select gene sets and export associated reads through the rest of the DNASTAR software pipeline for sequence assembly, alignment, and detailed analysis.
Not available
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100
QuEST - Quantitative Enrichment of Sequence Tags
http://mendel.stanford.edu/sidowlab/downloads/quest/
1. It is an efficient tool for chip seq analysis for motif detection and peak calling. 2. It is a quantitative enrichment of short tags which can handle broad peak . 3. It can analyse results from ucsc genome browser for both raw data and enrichment profiles.
Valouev A, Johnson DS, Sundquist A, Medina C, Anton E, Batzoglou S, Myers RM, Sidow A. Genome-wide analysis of transcription factor binding sites based on ChIP-Seq data. Nat Methods. 2008 Sep;5(9):829-34. PubMed PMID: 19160518; PubMed Central PMCID: PMC2917543.
2008
100
SeqMINER
http://bips.u-strasbg.fr/seqminer/tiki-index.php
1. It is used to interpret data. 2. It does qualitative and quantitative analysis of reference and ChIP seq data. 3. First it collects the data, then clusters it and finally visualizes the data.
Ye T, Krebs AR, Choukrallah MA, Keime C, Plewniak F, Davidson I, Tora L. seqMINER: an integrated ChIP-seq data interpretation platform. Nucleic Acids Res. 2011 Mar;39(6):e35. Epub 2010 Dec 21. PubMed PMID: 21177645; PubMed Central PMCID: PMC3064796.
2011
100
SISSRs - Site Identification from Short Sequence Reads
http://sissrs.rajajothi.com/
1. It is Site Identification from Short Sequence Reads. 2. It identifies binding site from next generation ChIP seq reads.
Jothi R, Cuddapah S, Barski A, Cui K, Zhao K. Genome-wide identification of invivo protein-DNA binding sites from ChIP-Seq data. Nucleic Acids Res. 2008 Sep;36(16):5221-31. Epub 2008 Aug 6. PubMed PMID: 18684996; PubMed Central PMCID: PMC2532738.
2008
100
 
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