Project description:Dataset for the manuscript: https://doi.org/10.3390/metabo10030101
"Lipid Annotator: Towards Accurate Annotation in Non-Targeted Liquid Chromatography High-Resolution Tandem Mass Spectrometry (LC-HRMS/MS) Lipidomics Using a Rapid and User-Friendly Software"
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.
Project description:Dataset for the manuscript: https://doi.org/10.3390/metabo10030101
"Lipid Annotator: Towards Accurate Annotation in Non-Targeted Liquid Chromatography High-Resolution Tandem Mass Spectrometry (LC-HRMS/MS) Lipidomics Using a Rapid and User-Friendly Software"
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.
Project description:Chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) is an invaluable tool for mapping chromatin-associated proteins. Processing of samples still remains largely individual and labor-intensive, hindering the assay throughput and comparability across samples. Here we present a novel method for ultra-parallelized high-throughput ChIP-seq for the systematic mapping of histone modifications and transcription factors. The method, called RELACS (Restriction Enzyme-based Labeling of Chromatin in Situ), barcodes chromatin within intact nuclei extracted from different tissutal sources. Barcoded nuclei are pooled and processed within the same ChIP, for maximal comparability and drastical workload reduction. The choice of user-friendly, straightforward, enzymatic steps for chromatin fragmentation and barcoding makes RELACS particularly suitable for implementation in any clinical laboratory settings, for scarce samples, and large-scale studies.
Project description:Anal cancer is a leading neoplasia in people with immune impartments populations, and the lack of an accurate screening test challenges its prevention. Because the bacteria living in the anal epithelium the anal microbiota seems to influence and be influenced by cancer development, specific patterns of anal microbes could help in the diagnosis of precancerous anal lesions. We aimed to discover microbial biomarkers of anal precancer in high-risk populations. We discovered 12 proteins, previously reported to be associated with cancer progression, that were more abundant in the anal bacterial from subjects with precancerous lesions.
Project description:A comparison of rectal mucosal RNA transcriptome findings between transgender women using feminizing hormone therapy, men who have sex with men engaging in receptive anal intercourse, and males who had never engaged in anal intercourse demonstrates differential gene expression involving pathways critical for mucosal inflammation, suggesting the urgent need for further exploration into the immunologic effects of cross-sex hormone therapy in the rectal mucosa and the potential impact on HIV transmission risk at this site.