ArticleBMC bioinformatics2009
Novel software package for cross-platform transcriptome analysis (CPTRA).
Article in BMC bioinformatics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed, 18 citations in OpenAlex.
- METTL3 inhibits LINC00312 to suppress osteoporosis progression in a YTHDF2‑dependent manner.International journal of molecular medicine · 2026Article
- De novo genome assembly of the economically important weed horseweed using integrated data from multiple sequencing platforms.Plant physiology · 2014Article
- Comprehensive transcriptional profiling of NaHCOPlant molecular biology · 2013Article
- Systematically characterizing and prioritizing chemosensitivity related gene based on Gene Ontology and protein interaction network.BMC medical genomics · 2012Article
- RNA-Seq reveals genotype-specific molecular responses to water deficit in eucalyptus.BMC genomics · 2011Article
- Community genetics: what have we accomplished and where should we be going?Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2011Review
- Ecological genetics and genomics of plant defenses: Evidence and approaches.Functional ecology · 2011Article
- AnyExpress: integrated toolkit for analysis of cross-platform gene expression data using a fast interval matching algorithm.BMC bioinformatics · 2011Article
- Proceedings of the 2010 MidSouth Computational Biology and Bioinformatics Society (MCBIOS) conference.BMC bioinformatics · 2010Article
- Proceedings of the 2009 MidSouth Computational Biology and Bioinformatics Society (MCBIOS) conference. Introduction.BMC bioinformatics · 2009Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundNext-generation sequencing techniques enable several novel transcriptome profiling approaches. Recent studies indicated that digital gene expression profiling based on short sequence tags has superior performance as compared to other transcriptome analysis platforms including microarrays. However, the transcriptomic analysis with tag-based methods often depends on available genome sequence. The use of tag-based methods in species without genome sequence should be complemented by other methods such as cDNA library sequencing. The combination of different next generation sequencing techniques like 454 pyrosequencing and Illumina Genome Analyzer (Solexa) will enable high-throughput and accurate global gene expression profiling in species with limited genome information. The combination of transcriptome data acquisition methods requires cross-platform transcriptome data analysis platforms, including a new software package for data processing.
resultsHere we presented a software package, CPTRA: Cross-Platform TRanscriptome Analysis, to analyze transcriptome profiling data from separate methods. The software package is available at http://people.tamu.edu/approximately syuan/cptra/cptra.html. It was applied to the case study of non-target site glyphosate resistance in horseweed; and the data was mined to discover resistance target gene(s). For the software, the input data included a long-read sequence dataset with proper annotation, and a short-read sequence tag dataset for the quantification of transcripts. By combining the two datasets, the software carries out the unique sequence tag identification, tag counting for transcript quantification, and cross-platform sequence matching functions, whereby the short sequence tags can be annotated with a function, level of expression, and Gene Ontology (GO) classification. Multiple sequence search algorithms were implemented and compared. The analysis highlighted the importance of transport genes in glyphosate resistance and identified several candidate genes for down-stream analysis.
conclusionCPTRA is a powerful software package for next generation sequencing-based transcriptome profiling in species with limited genome information. According to our case study, the strategy can greatly broaden the application of the next generation sequencing for transcriptome analysis in species without reference genome sequence.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.