clc_mapper
clc_mapper maps sequencing reads to reference sequences and assembles them into transcriptome contigs to support analysis of high-throughput sequencing data such as Roche 454 pyrosequencing.
Key Features:
- Read mapping and assembly: Maps short sequencing reads (250-450 base pairs) from Roche 454 pyrosequencing onto reference sequences and assembles them into contigs representing transcripts.
- High-throughput data handling: Processes and analyzes high-throughput sequencing datasets for transcriptome reconstruction.
- Comparative evaluation: Has been systematically compared with assemblers CAP3, MIRA, Newbler, and SeqMan to evaluate assembly performance.
- Assembly merging: Merges assemblies from different programs to improve alignment accuracy with reference sequences and to increase consistency in contig number and size.
- Integration with CLC Genomics Workbench: Operates as part of the CLC Genomics Workbench suite.
Scientific Applications:
- Transcriptome assembly for non-model organisms: Enables assembly and identification of known and novel transcripts where reference genomes are limited or absent.
- Biomedical sequencing analysis: Supports analysis of large next-generation sequencing datasets by producing longer contigs and aligning them to reference sequences.
- Assembler evaluation and optimization: Facilitates evaluation and optimization of assembler combinations and merging strategies to improve final assembly credibility.
Methodology:
Computational methods explicitly include mapping reads to reference sequences, assembling reads into contigs, merging assemblies from different programs, and systematic comparisons with other assemblers.
Topics
Collections
Details
- Maturity:
- Mature
- Tool Type:
- web application
- Operating Systems:
- Linux, Windows, Mac
- Added:
- 12/19/2016
- Last Updated:
- 11/25/2024
Operations
Data Inputs & Outputs
Read mapping
Outputs
Publications
Kumar S, Blaxter ML. Comparing de novo assemblers for 454 transcriptome data. BMC Genomics. 2010;11(1). doi:10.1186/1471-2164-11-571. PMID:20950480. PMCID:PMC3091720.
Afgan E, Baker D, van den Beek M, Blankenberg D, Bouvier D, Čech M, Chilton J, Clements D, Coraor N, Eberhard C, Grüning B, Guerler A, Hillman-Jackson J, Von Kuster G, Rasche E, Soranzo N, Turaga N, Taylor J, Nekrutenko A, Goecks J. The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update. Nucleic Acids Research. 2016;44(W1):W3-W10. doi:10.1093/nar/gkw343. PMID:27137889. PMCID:PMC4987906.
Mareuil F, Doppelt-Azeroual O, Ménager H. A public Galaxy platform at Pasteur used as an execution engine for web services. Unknown Journal. 2017. doi:10.7490/f1000research.1114334.1.