Dataset Information

A Long Fragment Aligner called ALFALFA.

ABSTRACT: BACKGROUND: Rapid evolutions in sequencing technology force read mappers into flexible adaptation to longer reads, changing error models, memory barriers and novel applications. RESULTS: ALFALFA achieves a high performance in accurately mapping long single-end and paired-end reads to gigabase-scale reference genomes, while remaining competitive for mapping shorter reads. Its seed-and-extend workflow is underpinned by fast retrieval of super-maximal exact matches from an enhanced sparse suffix array, with flexible parameter tuning to balance performance, memory footprint and accuracy. CONCLUSIONS: ALFALFA is open source and available at http://alfalfa.ugent.be .

SUBMITTER: Vyverman M

PROVIDER: S-EPMC4449525 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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A Long Fragment Aligner called ALFALFA.

Vyverman Michaël M Baets Bernard De BD Fack Veerle V Dawyndt Peter P

BMC bioinformatics 20150515

<h4>Background</h4>Rapid evolutions in sequencing technology force read mappers into flexible adaptation to longer reads, changing error models, memory barriers and novel applications.<h4>Results</h4>ALFALFA achieves a high performance in accurately mapping long single-end and paired-end reads to gigabase-scale reference genomes, while remaining competitive for mapping shorter reads. Its seed-and-extend workflow is underpinned by fast retrieval of super-maximal exact matches from an enhanced spa ...[more]

PMID: 25971785

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Project description:Clonogenic assays are powerful tools for testing cell reproductive death after biological damage caused by, for example, ionizing radiation. Traditionally, the methods require a cumbersome, slow and eye-straining manual counting of viable colonies under a microscope. To speed up the counting process and minimize those issues related to the subjective decisions of the scoring personnel, we developed a semi-automated, image-based cell colony counting setup, named CoCoNut (Colony Counter developed by the Nutech department at the Technical University of Denmark). It consists in an ImageJ macro and a photographic 3D-printed light-box, conceived and demonstrated to work together for Crystal Violet-stained colonies. Careful attention was given to the image acquisition process, which allows background removal (i.e. any unwanted element in the picture) in a minimally invasive manner. This is mainly achieved by optimal lighting conditions in the light-box and dividing the image of a flask that contains viable colonies by the picture of an empty flask. In this way, CoCoNut avoids using aggressive background removal filters that usually lead to suboptimal colony count recovery. The full method was tested with V79 and HeLa cell survival samples. Results were compared to other freely available tools. CoCoNut proved able to successfully distinguish between single and merged colonies and to identify colonies bordering on flask edges. CoCoNut software calibration is fast; it requires the adjustment of a single parameter that is the smallest colony area to be counted. The employment of a single parameter reduces the risk of subjectivity, providing a robust and user-friendly tool, whose results can be easily compared over time and among different bio-laboratories. The method is inexpensive and easy to obtain. Among its advantages, we highlight the possibility of combining the macro with a perfectly reproducible 3D-printed light-box. The CoCoNut software and the 3D-printer files are provided as supporting information (S1 CoCoNut Files).

Dataset Information

A Long Fragment Aligner called ALFALFA.

Publications

A Long Fragment Aligner called ALFALFA.

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