Project description:This study demonstrates the usefulness of the API by generating a baseline gut microbiota profile of a healthy population and estimating reference intervals for the functional abundance of manually selected KEGG pathways. API facilitates microbiome research by providing dynamic and customizable tools for estimating reference intervals for gut microbiota functional abundances. Through the API, researchers can rapidly generate gut microbiota functional profiles of healthy populations to use as a baseline for comparison. The API also allows users to manually select specific KEGG pathways and estimate reference intervals for the functional abundance of those pathways. By generating these customized reference intervals, researchers can better understand the expected range of gut microbiota functions in healthy individuals. API enables microbiome studies to go beyond simple taxonomic profiling and delve deeper into the functional potential of gut microbiome communities. In summary, API represents a valuable tool for microbiome researchers that enhances the ability to elucidate connections between gut microbial functions and human health.
Project description:The Human Induced Pluripotent Stem Cells Initiative (HipSci) is generating a large, high-quality reference panel of human IPSC lines. This is a submission of mass-spectrometry analyses from 6 induced pluripotent stem cell lines generated by the HipSci project.
2017-05-12 | PXD005506 | Pride
Project description:Generating high quality reference genomes from field collected specimens by optimizing preservation
Project description:The Human Induced Pluripotent Stem Cells Initiative (HipSci) is generating a large, high-quality reference panel of human IPSC lines. This is a submission of mass-spectrometry analyses from 6 induced pluripotent stem cell lines generated by the HipSci project.
Project description:Accurate annotations of genes and their transcripts is a foundation of genomics, but no annotation technique presently combines throughput and accuracy. As a result, the GENCODE reference collection of long noncoding RNAs remains far from complete: many are fragmentary, while thousands more remain uncatalogued. To accelerate lncRNA annotation, we have developed RNA Capture Long Seq (CLS), combining targeted RNA capture with third generation long-read sequencing. We present an experimental re-annotation of the entire GENCODE intergenic lncRNA populations in matched human and mouse tissues. CLS approximately doubles the complexity of targeted loci, both in terms of validated splice junctions and transcript models. Through its identification of full-length transcript models, CLS allows the first definitive measurement of promoter features, gene structure and protein-coding potential of lncRNAs. Thus CLS removes a longstanding bottleneck of transcriptome annotation, generating manual-quality full-length transcript models at high-throughput scales.
Project description:This study utilized the HIT-ISOseq method for high-throughput sequencing of RNA isoforms across multiple lettuce samples, generating millions of long reads per PacBio Sequel II SMRT Cell. Analysis of six tissue types revealed tissue-specific gene expression and RNA isoforms, facilitating updates to the lettuce reference genome annotation with expanded functional annotations.