inGAP (Integrated Next-gen Genome Analysis Platform)
Please refer to the following link for detail.
http://sites.google.com/site/nextgengenomics/ingap
inGAP is an integrated platform for next-generation sequencing project, the core function of which is to detect SNPs and indels using a Bayesian algorithm.
(1) It does not have any read length restriction. It can handle 454 sequencing and/or Illumina Solexa sequencing and/or Sanger sequencing data sets.
(2) It can detect most small indels in either single-end or paired-end data sets. Using the simulated data sets, inGAP could successfully identify 85%-98% of small indels with high accuracy (>99%).
(3) It has a strong capability to identify variants based on a relatively divergent reference genome, which bring it to a much wider application other than resequencing projects.
(4) It provides a user-friendly graphic interface, through which users can browse, search, check, classify, and even edit the identified variants.
(5) It can be used to detect intraspecific polymorphisms (including SNPs and indels) based on a pairwise comparison of multiple whole genomes.
(6) It employs a global heuristic searching approach to layout contigs based on one or more reference genomes.
(7) It also provides a handful of bioinformatic tools for read simulation, mutation incorporation, format conversion, etc.
(8) It's slower than other SNP detection programs (e.g. MAQ, SOAP, Bowtie), because it employs BLAST or BLAT to map reads. It generally takes about 220 minutes for comparing 10 million 75bp Illumina reads against a 12Mb yeast reference genome on an 8-core DELL machine.
Any comments and suggestions are welcome.
Please refer to the following link for detail.
http://sites.google.com/site/nextgengenomics/ingap
inGAP is an integrated platform for next-generation sequencing project, the core function of which is to detect SNPs and indels using a Bayesian algorithm.
(1) It does not have any read length restriction. It can handle 454 sequencing and/or Illumina Solexa sequencing and/or Sanger sequencing data sets.
(2) It can detect most small indels in either single-end or paired-end data sets. Using the simulated data sets, inGAP could successfully identify 85%-98% of small indels with high accuracy (>99%).
(3) It has a strong capability to identify variants based on a relatively divergent reference genome, which bring it to a much wider application other than resequencing projects.
(4) It provides a user-friendly graphic interface, through which users can browse, search, check, classify, and even edit the identified variants.
(5) It can be used to detect intraspecific polymorphisms (including SNPs and indels) based on a pairwise comparison of multiple whole genomes.
(6) It employs a global heuristic searching approach to layout contigs based on one or more reference genomes.
(7) It also provides a handful of bioinformatic tools for read simulation, mutation incorporation, format conversion, etc.
(8) It's slower than other SNP detection programs (e.g. MAQ, SOAP, Bowtie), because it employs BLAST or BLAT to map reads. It generally takes about 220 minutes for comparing 10 million 75bp Illumina reads against a 12Mb yeast reference genome on an 8-core DELL machine.
Any comments and suggestions are welcome.
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