TY - JOUR
T1 - Slim-Filter
T2 - An interactive windows-based application for illumina genome analyzer data assessment and manipulation
AU - Golovko, Georgiy
AU - Khanipov, Kamil
AU - Rojas, Mark
AU - Martinez-Alcántara, Antonio
AU - Howard, Jesse J.
AU - Ballesteros, Efren
AU - Gupta, Sharu
AU - Widger, William
AU - Fofanov, Yuriy
N1 - Funding Information:
Slim-Filter was developed with the support of the Center for BioMedical and Environmental Genomics. Additional funding includes: Department of Homeland Security Science and Technology Directorate (awards HSHQDC-08-C-00183 and NBCHC070054 to Y.F) and Biomedical Informatics Research Training Grant (NLM Grant 5 T15 LM07093-18 to M.R.).
PY - 2012/7/16
Y1 - 2012/7/16
N2 - Background: The emergence of Next Generation Sequencing technologies has made it possible for individual investigators to generate gigabases of sequencing data per week. Effective analysis and manipulation of these data is limited due to large file sizes, so even simple tasks such as data filtration and quality assessment have to be performed in several steps. This requires (potentially problematic) interaction between the investigator and a bioinformatics/computational service provider. Furthermore, such services are often performed using specialized computational facilities.Results: We present a Windows-based application, Slim-Filter designed to interactively examine the statistical properties of sequencing reads produced by Illumina Genome Analyzer and to perform a broad spectrum of data manipulation tasks including: filtration of low quality and low complexity reads; filtration of reads containing undesired subsequences (such as parts of adapters and PCR primers used during the sample and sequencing libraries preparation steps); excluding duplicated reads (while keeping each read's copy number information in a specialized data format); and sorting reads by copy numbers allowing for easy access and manual editing of the resulting files. Slim-Filter is organized as a sequence of windows summarizing the statistical properties of the reads. Each data manipulation step has roll-back abilities, allowing for return to previous steps of the data analysis process. Slim-Filter is written in C++ and is compatible with fasta, fastq, and specialized AS file formats presented in this manuscript. Setup files and a user's manual are available for download at the supplementary web site (https://www.bioinfo.uh.edu/Slim_Filter/).Conclusion: The presented Windows-based application has been developed with the goal of providing individual investigators with integrated sequencing reads analysis, curation, and manipulation capabilities.
AB - Background: The emergence of Next Generation Sequencing technologies has made it possible for individual investigators to generate gigabases of sequencing data per week. Effective analysis and manipulation of these data is limited due to large file sizes, so even simple tasks such as data filtration and quality assessment have to be performed in several steps. This requires (potentially problematic) interaction between the investigator and a bioinformatics/computational service provider. Furthermore, such services are often performed using specialized computational facilities.Results: We present a Windows-based application, Slim-Filter designed to interactively examine the statistical properties of sequencing reads produced by Illumina Genome Analyzer and to perform a broad spectrum of data manipulation tasks including: filtration of low quality and low complexity reads; filtration of reads containing undesired subsequences (such as parts of adapters and PCR primers used during the sample and sequencing libraries preparation steps); excluding duplicated reads (while keeping each read's copy number information in a specialized data format); and sorting reads by copy numbers allowing for easy access and manual editing of the resulting files. Slim-Filter is organized as a sequence of windows summarizing the statistical properties of the reads. Each data manipulation step has roll-back abilities, allowing for return to previous steps of the data analysis process. Slim-Filter is written in C++ and is compatible with fasta, fastq, and specialized AS file formats presented in this manuscript. Setup files and a user's manual are available for download at the supplementary web site (https://www.bioinfo.uh.edu/Slim_Filter/).Conclusion: The presented Windows-based application has been developed with the goal of providing individual investigators with integrated sequencing reads analysis, curation, and manipulation capabilities.
UR - http://www.scopus.com/inward/record.url?scp=84870007007&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84870007007&partnerID=8YFLogxK
U2 - 10.1186/1471-2105-13-166
DO - 10.1186/1471-2105-13-166
M3 - Article
C2 - 22800377
AN - SCOPUS:84870007007
SN - 1471-2105
VL - 13
JO - BMC bioinformatics
JF - BMC bioinformatics
IS - 1
M1 - 166
ER -