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MUFFIN: a suite of tools for the analysis of functional sequencing data

机译:MUFFIN:一套用于分析功能测序数据的工具

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摘要

The large diversity of functional genomic assays allows for the characterization of non-coding and coding events at the tissue level or at a single-cell resolution. However, this diversity also leads to protocol differences, widely varying sequencing depths, substantial disparities in sample sizes, and number of features. In this work, we have built a Python package, MUFFIN, which offers a wide variety of tools suitable for a broad range of genomic assays and brings many tools that were missing from the Python ecosystem. First, MUFFIN has specialized tools for the exploration of the non-coding regions of genomes, such as a function to identify consensus peaks in peak-called assays, as well as linking genomic regions to genes and performing Gene Set Enrichment Analyses. MUFFIN also possesses a robust and flexible count table processing pipeline, comprising normalization, count transformation, dimensionality reduction, Differential Expression, and clustering. Our tools were tested on three widely different scRNA-seq, ChIP-seq and ATAC-seq datasets. MUFFIN integrates with the popular Scanpy ecosystem and is available on Conda and at https://github.com/pdelangen/Muffin.
机译:功能基因组分析的多样性允许在组织水平或单细胞分辨率下表征非编码和编码事件。然而,这种多样性也导致了方案差异、测序深度差异很大、样本量和特征数量的巨大差异。在这项工作中,我们构建了一个 Python 包 MUFFIN,它提供了适用于各种基因组分析的各种工具,并带来了 Python 生态系统中缺少的许多工具。首先,MUFFIN 拥有用于探索基因组非编码区域的专用工具,例如在称为峰的分析中识别共有峰的功能,以及将基因组区域与基因联系起来并执行基因集富集分析。MUFFIN 还拥有强大而灵活的计数表处理管道,包括归一化、计数转换、降维、差分表达式和聚类。我们的工具在三个截然不同的 scRNA-seq、ChIP-seq 和 ATAC-seq 数据集上进行了测试。MUFFIN 与流行的 Scanpy 生态系统集成,可在 Conda 和 https://github.com/pdelangen/Muffin 上使用。

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