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White papers

Reports and benchmarks containing our software and algorithms.

White Papers

  • readmapping_thumbnailexecsum_readmapping

    White paper on CLC read mapper

    10 October, 2012

    This is a white paper on the read mapping algorithm introduced in CLC Genomics Workbench 5.5, CLC Genomics Server 4.5 and CLC Assembly Cell 4.0.

    Download the full White paper or the executive summary here.

  • probabilistic_thumbnailexecsum_variant_caller

    White paper on Probabilistic Variant Caller 1.1

    13 July, 2012

    This is a White Paper on the Probabilistic Variant Detection analysis tool available for CLC Genomics Workbench. The tool can run on CLC Genomics Workbench as well as on CLC Genomics Server.

    Download the full White paper here.

  • imb_thumbnail

    IBM Solution Brief using CLC Assembly Cell

    1 May, 2012

    The explosive growth of sequence data from next-generation sequencing (NGS) technologies presents great challenges in need of fast and reliable sequence assembly and mapping.

    Download the full White paper here.

  • denovo_thumbnailexecsum_denovo

    White paper on CLC de novo assembler

    6 February, 2012

    This is a white paper on the de novo assembler in CLC Assembly Cell 4.0. Note that the same algorithm is used by CLC Genomics Workbench and CLC Genomics Server, and except for the performance benchmarks (speed and memory), this white paper applies to these products as well.

    Download the full White paper here.

  • readmapping_thumbnail

    Legacy version: White paper on CLC read mapper

    10 May, 2010

    This is a white paper on the read mapper in CLC Assembly Cell 3.0. Please note that this is not the latest version of the read mapper.

    Download the full White paper here.

  • alignspeedquality_thumbnail

    CLC bio’s proprietary alignment algorithm*

    1 February, 2006

    The alignment algorithms used in the software from CLC bio A/S have some unique features including the option of adjusting the cost of gaps in the end of the alignment to suit the sequences being aligned. Until now, however, the algorithms have also been relatively slow and not as accurate as the leading alignment programs.

    Download the full White paper here.

*Special note about the white paper on CLC bio’s proprietary alignment algorithm:

The alignment algorithms used in the software from CLC bio A/S has some unique features including the option of adjusting the cost of gaps in the end of the alignment to suit the sequences being aligned.

We have two alignments: A standard algorithm that is 10 times faster than our previous alignment in most scenarios, and an additional alignment that is even faster, but less accurate than the standard algorithm.

The White Paper forms the basis for these 5 conclusions:

  • On large data sets of sequences that are not too divergent, our alignment is significantly faster than the standard CLUSTAL W alignment, and around the same speed as the fast CLUSTAL W alignment.
  • Performing an alignment of 28 HIV genomes, our fast alignment is more than 10 times (55 minutes) faster than the standard CLUSTAL W alignment.
  • We have benchmarked our new algorithms on the BAliBASE 3.0 database of accurate protein alignments (Thompson et al., 2005). This shows that our alignment algorithm is about 1% more accurate than the latest version of the standard CLUSTAL W on protein alignments.
  • We have bechmarked our new algorithms on the BRaliBase II database of structurally aligned RNA. Here, our new algorithm is about 3.5% more accurate than the standard CLUSTAL W.
  • Our standard algorithm is still a little slower than the standard CLUSTAL W on the fairly divergent alignments in BAliBASE and BRaliBase. Our fast alignment is as precise and as fast as the standard CLUSTAL W on these data sets.