Project description:This submission includes the raw data analyzed and search results described in our manuscript “Proteome-Scale Recombinant Standards And A Robust High-Speed Search Engine To Advance Cross-Linking MS-Based Interactomics”. In this study, we develop a strategy to generate a well-controlled XL-MS standard by systematically mixing and cross-linking recombinant proteins. The standard can be split into independent datasets, each of which has the MS2-level complexity of a typical proteome-wide XL-MS experiment. The raw datasets included in this submission were used to (1) guide the development of Scout, a machine learning-based search engine for XL-MS with MS-cleavable cross-linkers (batch 1), test different LC-MS acquisition methods (batch 2), and directly compare Scout to widely used XL-MS search engines (batches 3 and 4).
Project description:High resolution HiC libraries are usually lightly sequenced before investing in a deep sequencing. We modeled HiC resolution in function of the sequencing depth to predict accurately the resolution of any high resolution HiC library given a small sequnecing batch of the library. To test our tool, we used public datasets as well as a newly generated dataset using Arima kit on mouse purified rods photoreceptors.
Project description:Purpose: We compare small noncoding RNA (ncRNA) profiles between exosomes and whole plasma to test a better source of small ncRNA biomarkers. We hypothesize that exosome is a better source of small ncRNA biomarkers compared to whole plasma. Methods: Small ncRNA sequencings were done using Illumina NextSeq500. Single-end 76 bp reads were explored using FASTQC. GeneGlobe Data Analysis Center, an online platform from Qiagen was used for the small ncRNA-seq data analysis. The mapped read counts for miRNA, piRNA and tRNA were used for differential expression analysis using DESeq2 Bioconductor in R. The small RNA species with logFC > |1| and adj.P-value <0.05 were called differentially expressed. Conclusion: Small ncRNAs extracted from exosomes were found to have the most consistent profiles among healthy individuals. Whole plasma RNA profiles contain high concentrations of blood-derived miRNAs. These miRNA levels can create batch effects among samples due to different levels of hemolysis. Our finding suggests the importance of using purified exosomes as a better source of small ncRNA biomarkers to avoid the batch effect.
Project description:We developed a unique multi-batch benchmarking dataset. The design is based on a standard two-species dilution model3,18,19 with mouse plasma used to create a background of potentially interfering peptides at 1:1 ratios while yeast cultures are mixed across a range of known ratios. For the purposes of investigating how best to combine isobaric batches the experiment is designed with two main goals. First, we needed multiple batches of data containing a wide range of known changes, with some large enough to test the dynamic range of our instrument, and others small enough to probe our capacity for detecting small perturbations. Second, we need a wide variety of batch compositions to better reflect the full set of patterns that we might observe when studying a random assortment of genetically diverse samples. To this end, yeast proteomes were diluted at eleven different levels of known changes with a maximum dilution of 1/32 by the use of an automated liquid handler. To generate a diversity of batch compositions across the proteome, we cultured yeast in various carbon and nitrogen source combinations known to substantially alter the yeast proteome20. Both media groups and dilution levels were randomly assigned throughout six batches of TMT-labeled samples