Dataset Information

PowerBLAST: a new network BLAST application for interactive or automated sequence analysis and annotation.

ABSTRACT: As the rate of DNA sequencing increases, analysis by sequence similarity search will need to become much more efficient in terms of sensitivity, specificity, automation potential, and consistency in annotation. PowerBLAST was developed, in part, to address these problems. PowerBLAST includes a number of options for masking repetitive elements and low complexity subsequences. It also has the capacity to restrict the search to any level of NCBI's taxonomy index, thus supporting "comparative genomics" applications. Postprocessing of the BLAST output using the SIM series of algorithms produces optimal, gapped alignments, and multiple alignments when a region of the query sequence matches multiple database sequences. PowerBLAST is capable of processing sequences of any length because it divides long query sequences into overlapping fragments and then merges the results after searching. The results may be viewed graphically, as a textual representation, or as an HTML page with links to GenBank and Entrez. For matching database sequences, annotated features are superimposed on the aligned query sequence in the output, thus greatly increasing the ease of interpretation. Such features may be used for automated annotation of new sequence because PowerBLAST output in ASN.1 form may be "dragged and dropped" into NCBI's Sequin program for sequence annotation and submission. PowerBLAST is capable of analyzing and annotating a 100-kb query in 60 min on NCBI's BLAST server.

SUBMITTER: Zhang J

PROVIDER: S-EPMC310664 | biostudies-literature | 1997 Jun

REPOSITORIES: biostudies-literature

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PowerBLAST: a new network BLAST application for interactive or automated sequence analysis and annotation.

Zhang J J Madden T L TL

Genome research 19970601 6

As the rate of DNA sequencing increases, analysis by sequence similarity search will need to become much more efficient in terms of sensitivity, specificity, automation potential, and consistency in annotation. PowerBLAST was developed, in part, to address these problems. PowerBLAST includes a number of options for masking repetitive elements and low complexity subsequences. It also has the capacity to restrict the search to any level of NCBI's taxonomy index, thus supporting "comparative genomi ...[more]

PMID: 9199938

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Project description:BackgroundTranscriptionally informed predictions are increasingly important for sub-typing cancer patients, understanding underlying biology and to inform novel treatment strategies. For instance, colorectal cancers (CRCs) can be classified into four CRC consensus molecular subgroups (CMS) or five intrinsic (CRIS) sub-types that have prognostic and predictive value. Breast cancer (BRCA) has five PAM50 molecular subgroups with similar value, and the OncotypeDX test provides transcriptomic based clinically actionable treatment-risk stratification. However, assigning samples to these subtypes and other transcriptionally inferred predictions is time consuming and requires significant bioinformatics experience. There is no "universal" method of using data from diverse assay/sequencing platforms to provide subgroup classification using the established classifier sets of genes (CMS, CRIS, PAM50, OncotypeDX), nor one which in provides additional useful functional annotations such as cellular composition, single-sample Gene Set Enrichment Analysis, or prediction of transcription factor activity.ResultsTo address this bottleneck, we developed classifieR, an easy-to-use R-Shiny based web application that supports flexible rapid single sample annotation of transcriptional profiles derived from cancer patient samples form diverse platforms. We demonstrate the utility of the " classifieR" framework to applications focused on the analysis of transcriptional profiles from colorectal (classifieRc) and breast (classifieRb). Samples are annotated with disease relevant transcriptional subgroups (CMS/CRIS sub-types in classifieRc and PAM50/inferred OncotypeDX in classifieRb), estimation of cellular composition using MCP-counter and xCell, single-sample Gene Set Enrichment Analysis (ssGSEA) and transcription factor activity predictions with Discriminant Regulon Expression Analysis (DoRothEA).ConclusionsclassifieR provides a framework which enables labs without access to a dedicated bioinformation can get information on the molecular makeup of their samples, providing an insight into patient prognosis, druggability and also as a tool for analysis and discovery. Applications are hosted online at https://generatr.qub.ac.uk/app/classifieRc and https://generatr.qub.ac.uk/app/classifieRb after signing up for an account on https://generatr.qub.ac.uk .

Dataset Information

PowerBLAST: a new network BLAST application for interactive or automated sequence analysis and annotation.

Publications

PowerBLAST: a new network BLAST application for interactive or automated sequence analysis and annotation.

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