Reports and benchmarks containing our software and algorithms.
|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|
|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|
|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|
|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|
|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|
|CLC Bioinformatics Cell|
30 March, 2009
|CLC Bioinformatics Cell is a highly specialized combination of software and hardware for high performance bioinformatics. It currently includes three accelerated algorithms: • Smith-Waterman BLAST which combines the accuracy and sensitivity from the Smith- Waterman algorithm with the well-known input and output formats of BLAST. • The popular ClustalW alignment algorithm. • The domain searching hmmpfam and hmmsearch algorithms from the HMMER software package.||Download|
|MPI Support for CLC Bioinformatics Cell|
6 March, 2008
|This white-paper describes how the performance of the algorithms on the CLC Bioinformatics Cell scale when running on a computer cluster. With version 2.1, the CLC Bioinformatics Cell has MPI support, which means that its high performance can now be utilized on a larger scale by installing it on a computer cluster.||Download|
|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|
*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.