Project description:As part of the ENCODE consortium the GENCODE project is producing a reference gene set through manual and automated gene prediction. Selected transcript models are verified experimentally by RT-PCR amplification of at least one of their unique splice junctions followed by sequencing. The experiment targets are manually annotated transcripts with novel or putative status, non-pseudogene biotype and unique splice junctions not validated previously. For Batch XI 966 splice junctions from GENCODE13 (released July 2012) and 640 splice junctions from GENCODE14 (released October 2012) were chosen for experimental verification.
Project description:As part of the ENCODE consortium, the GENCODE project is producing a reference gene set through manual and automated gene prediction. Selected transcript models are verified experimentally by RT-PCR amplification of at least one of their unique splice junctions, followed by high-throughput sequencing (RT-PCR-seq). The experimental targets are manually annotated transcripts with novel or putative status, non-pseudogene biotype, and unique splice junctions which have not been validated previously and are not supported by RNAseq data from the ENCODE and GTEx projects. For Batch XVII, 1159 splice junctions which failed this experimental verification in previous experiments were tested again. On this occasion, newly designed PCR primers were used and compared with the original ones. In addition, the original tissue panel was widened with the inclusion of eight new tissues.
Project description:As part of the ENCODE consortium the GENCODE project is producing a reference gene set through manual and automated gene prediction. Selected transcript models are verified experimentally by RT-PCR amplification of at least one of their unique splice junctions followed by sequencing. The experiment targets are manually annotated transcripts with novel or putative status, non-pseudogene biotype and unique splice junctions not validated previously. For Batch XII 416 splice junctions from GENCODE15 (released January 2013) were chosen for experimental verification.
Project description:As part of the ENCODE consortium the GENCODE project is producing a reference gene set through manual and automated gene prediction. Selected transcript models are verified experimentally by RT-PCR amplification of at least one of their unique splice junctions followed by sequencing. The experiment targets are manually annotated transcripts with novel or putative status, non-pseudogene biotype and unique splice junctions not validated previously. For Batch XIV 271 splice junctions from GENCODE16 (released April 2013) were chosen for experimental verification.
Project description:As part of the ENCODE consortium the GENCODE project is producing a reference gene set through manual and automated gene prediction. Selected transcript models are verified experimentally by RT-PCR amplification of at least one of their unique splice junctions followed by high-throughput sequencing. The experiment targets are manually annotated transcripts with novel or putative status, non-pseudogene biotype and unique splice junctions which have not been validated previously and are not supported by RNAseq data from the ENCODE and GTEx projects. For Batch XV 1243 splice junctions from GENCODE19 (released in December 2013) were chosen for experimental verification.
Project description:As part of the ENCODE consortium the GENCODE project is producing a reference gene set through manual and automated gene prediction. Selected transcript models are verified experimentally by RT-PCR amplification of at least one of their unique splice junctions followed by high-throughput sequencing. The experiment targets are manually annotated transcripts with novel or putative status, non-pseudogene biotype and unique splice junctions which have not been validated previously and are not supported by mouse RNAseq data from the ENCODE project. In Batch M2, 808 splice junctions from GENCODE version M4 (released in December 2014) were chosen for experimental verification.
Project description:As part of the ENCODE consortium the GENCODE project is producing a reference gene set through manual and automated gene prediction. Selected transcript models are verified experimentally by RT-PCR amplification of at least one of their unique splice junctions followed by sequencing. Batch X targets manually annotated transcripts from GENCODE v11 (released Feb 2012) with novel or putative status, non-pseudogene biotype and unique splice junctions not validated previously.
Project description:As part of the ENCODE consortium the GENCODE project is producing a reference gene set through manual and automated gene prediction. Selected transcript models are verified experimentally by RT-PCR amplification of at least one of their unique splice junctions followed by high-throughput sequencing. The experiment targets are manually annotated transcripts with novel or putative status, non-pseudogene biotype and unique splice junctions which have not been validated previously and are not supported by mouse RNAseq data from the ENCODE project. In Batch M1, which is the first GENCODE validation experiment in mouse, 3148 splice junctions from GENCODE version M2 (released in December 2013) were chosen for experimental verification.
Project description:We present primary results from the Sequencing Quality Control (SEQC) project, coordinated by the United States Food and Drug Administration. Examining Illumina HiSeq, Life Technologies SOLiD and Roche 454 platforms at multiple laboratory sites using reference RNA samples with built-in controls, we assess RNA sequencing (RNA-seq) performance for sequence discovery and differential expression profiling and compare it to microarray and quantitative PCR (qPCR) data using complementary metrics. At all sequencing depths, we discover unannotated exon-exon junctions, with >80% validated by qPCR. We find that measurements of relative expression are accurate and reproducible across sites and platforms if specific filters are used. In contrast, RNA-seq and microarrays do not provide accurate absolute measurements, and gene-specific biases are observed, for these and qPCR. Measurement performance depends on the platform and data analysis pipeline, and variation is large for transcriptlevel profiling. The complete SEQC data sets, comprising >100 billion reads (10Tb), provide unique resources for evaluating RNA-seq analyses for clinical and regulatory settings.
Project description:We present primary results from the Sequencing Quality Control (SEQC) project, coordinated by the United States Food and Drug Administration. Examining Illumina HiSeq, Life Technologies SOLiD and Roche 454 platforms at multiple laboratory sites using reference RNA samples with built-in controls, we assess RNA sequencing (RNA-seq) performance for sequence discovery and differential expression profiling and compare it to microarray and quantitative PCR (qPCR) data using complementary metrics. At all sequencing depths, we discover unannotated exon-exon junctions, with >80% validated by qPCR. We find that measurements of relative expression are accurate and reproducible across sites and platforms if specific filters are used. In contrast, RNA-seq and microarrays do not provide accurate absolute measurements, and gene-specific biases are observed, for these and qPCR. Measurement performance depends on the platform and data analysis pipeline, and variation is large for transcriptlevel profiling. The complete SEQC data sets, comprising >100 billion reads (10Tb), provide unique resources for evaluating RNA-seq analyses for clinical and regulatory settings.