CoMA
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB32269 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:LotuS: an efficient and user-friendly OTU processing pipeline
| PRJNA259602 | ENA
Project description:Background Single-cell RNA-sequencing (scRNA-seq) experiments typically analyze hundreds or thousands of cells after amplification of the cDNA. The high throughput is made possible by the early introduction of sample-specific bar codes (BCs), and the amplification bias is alleviated by unique molecular identifiers (UMIs). Thus, the ideal analysis pipeline for scRNA-seq data needs to efficiently tabulate reads according to both BC and UMI. Findings zUMIs is a pipeline that can handle both known and random BCs and also efficiently collapse UMIs, either just for exon mapping reads or for both exon and intron mapping reads. If BC annotation is missing, zUMIs can accurately detect intact cells from the distribution of sequencing reads. Another unique feature of zUMIs is the adaptive downsampling function that facilitates dealing with hugely varying library sizes but also allows the user to evaluate whether the library has been sequenced to saturation. To illustrate the utility of zUMIs, we analyzed a single-nucleus RNA-seq dataset and show that more than 35% of all reads map to introns. Also, we show that these intronic reads are informative about expression levels, significantly increasing the number of detected genes and improving the cluster resolution. Conclusions zUMIs flexibility makes if possible to accommodate data generated with any of the major scRNA-seq protocols that use BCs and UMIs and is the most feature-rich, fast, and user-friendly pipeline to process such scRNA-seq data.
2018-06-22 | GSE99822 | GEO
Project description:Detection of Volatile Organic Compounds (VOC) directly from tissue by headspace analysis (skin, surgery material, other tissue) and exhaled breath is feasible using affordable user-friendly novel nano-chemo sensors that can accurately be used for screening and monitoring purpose
| 2250131 | ecrin-mdr-crc
Project description:Here, we present ChromSCape, a user-friendly interactive Shiny/R application that processes single-cell epigenomic data to help the biological interpretation of chromatin landscapes within cell populations. ChromSCape successfully analyses the distribution of repressive and active histone modifications as well as chromatin accessibility landscapes from single-cell datasets.
2020-06-16 | GSE152502 | GEO
Project description:We present Proline (http://www.profiproteomics.fr/proline/), a robust software suite for analysis of MS-based proteomics data; it provides high performance in a user-friendly interface for all data set sizes from small to very large
2020-03-03 | PXD009815 | Pride
Project description:An Easy Operating Pathogen Microarray (EOPM) was designed to detect almost all known pathogens and related species based on their genomic sequences. For effective identification of pathogens from EOPM data, a statistical enrichment algorithm has been proposed and further implemented in a user-friendly interface.
2013-07-01 | GSE45860 | GEO
Project description:PeptideShaker is a user friendly tool for shotgun proteomic data interpretation and reprocessing. The present dataset is the example dataset and consists of a single run HeLa measurement.
2014-01-27 | PXD000674 | Pride
Project description:Pseudouridine (Ψ) is an abundant RNA modification that is present in and impacts the functions of diverse non-coding RNA species, including rRNA, tRNA, snRNA, etc. Pseudouridine also exists in mammalian mRNA and likely exhibits functional roles; however, functional investigations of pseudouridine in mammalian mRNA have been hampered by the lack of a quantitative method that detects Ψ at base precision. We have recently developed Bisulfite-Induced Deletion sequencing (BID-seq), which provides the community with a quantitative method to map RNA Ψ distribution transcriptome-wide at single-base resolution. Here, we describe an optimized BID-seq protocol to generate highly reproducible results, displaying nearly zero background deletions at unmodified uridines after bisulfite treatment and uncovering 8,407 Ψ sites starting from as little as 10 ng mouse embryonic stem cell (mESC) polyA+ RNA, with the steps that are fast in both library preparation and data analysis. This optimized BID-seq workflow takes 5 days to complete and includes four main sections: RNA preparation, library construction, next-generation sequencing (NGS), and data analysis. The library construction can be completed by researchers who have basic knowledge and skills in molecular biology and genetics. In addition to the experimental protocol, we provide BID-pipe (https://github.com/y9c/pseudoU-BIDseq), a user-friendly data analysis pipeline for BID-seq, requiring only basic bioinformatic and computational skills to uncover Ψ signatures from NGS data.
2023-08-07 | GSE238245 | GEO
Project description:A user-friendly chromatographic method to purify small regulatory RNAs
| PRJNA174816 | ENA