RESUMO
BACKGROUND: Exploration and processing of FASTQ files are the first steps in state-of-the-art data analysis workflows of Next Generation Sequencing (NGS) platforms. The large amount of data generated by these technologies has put a challenge in terms of rapid analysis and visualization of sequencing information. Recent integration of the R data analysis platform with web visual frameworks has stimulated the development of user-friendly, powerful, and dynamic NGS data analysis applications. RESULTS: This paper presents FastqCleaner, a Bioconductor visual application for both quality-control (QC) and pre-processing of FASTQ files. The interface shows diagnostic information for the input and output data and allows to select a series of filtering and trimming operations in an interactive framework. FastqCleaner combines the technology of Bioconductor for NGS data analysis with the data visualization advantages of a web environment. CONCLUSIONS: FastqCleaner is an user-friendly, offline-capable tool that enables access to advanced Bioconductor infrastructure. The novel concept of a Bioconductor interactive application that can be used without the need for programming skills, makes FastqCleaner a valuable resource for NGS data analysis.
Assuntos
Biologia Computacional/métodos , Sequenciamento de Nucleotídeos em Larga Escala , Interface Usuário-Computador , Humanos , Controle de Qualidade , Software , Fluxo de TrabalhoRESUMO
We have generated 2771 expressed sequence tags (ESTs) from two cDNA libraries of Trypanosoma cruzi CL-Brener. The libraries were constructed from trypomastigote and amastigotes, using a spliced leader primer to synthesize the cDNA second strand, thus selecting for full-length cDNAs. Since the libraries were not normalized nor pre-screened, we compared the representation of transcripts between the two using a statistical test and identify a subset of transcripts that show apparent differential representation. A non-redundant set of 1619 reconstructed transcripts was generated by sequence clustering. This dataset was used to perform similarity searches against protein and nucleotide databases. Based on these searches, 339 sequences could be assigned a putative identity. One thousand one-hundred and sixteen sequences in the non-redundant clustered dataset (68.8 per cent) are new expression tags, not represented in the T, cruzi epimastigote ESTs that are in the public databases.
Assuntos
Doença de Chagas , Etiquetas de Sequências Expressas , Trypanosoma cruzi , Bolsas de EstudoRESUMO
We have generated 2771 expressed sequence tags (ESTs) from two cDNA libraries of Trypanosoma cruzi CL-Brener. The libraries were constructed from trypomastigote and amastigotes, using a spliced leader primer to synthesize the cDNA second strand, thus selecting for full-length cDNAs. Since the libraries were not normalized nor pre-screened, we compared the representation of transcripts between the two using a statistical test and identify a subset of transcripts that show apparent differential representation. A non-redundant set of 1619 reconstructed transcripts was generated by sequence clustering. This dataset was used to perform similarity searches against protein and nucleotide databases. Based on these searches, 339 sequences could be assigned a putative identity. One thousand one-hundred and sixteen sequences in the non-redundant clustered dataset (68.8 per cent) are new expression tags, not represented in the T, cruzi epimastigote ESTs that are in the public databases.
Assuntos
Doença de Chagas , Etiquetas de Sequências Expressas , Trypanosoma cruzi , Bolsas de EstudoRESUMO
We have generated 2771 expressed sequence tags (ESTs) from two cDNA libraries of Trypanosoma cruzi CL-Brener. The libraries were constructed from trypomastigote and amastigotes, using a spliced leader primer to synthesize the cDNA second strand, thus selecting for full-length cDNAs. Since the libraries were not normalized nor pre-screened, we compared the representation of transcripts between the two using a statistical test and identify a subset of transcripts that show apparent differential representation. A non-redundant set of 1619 reconstructed transcripts was generated by sequence clustering. This dataset was used to perform similarity searches against protein and nucleotide databases. Based on these searches, 339 sequences could be assigned a putative identity. One thousand one-hundred and sixteen sequences in the non-redundant clustered dataset (68.8 per cent) are new expression tags, not represented in the T, cruzi epimastigote ESTs that are in the public databases.
