1. 微生物质量控制（MBQC）项目联盟对微生物群落扩增子测序方法评估

Assessment of variation in microbial community amplicon sequencing by the Microbiome Quality Control (MBQC) project consortium (Nature Biotechnology)

Abstract

In order for human microbiome studies to translate into actionable outcomes for health, meta-analysis of reproducible data from population-scale cohorts is needed. Achieving sufficient reproducibility in microbiome research has proven challenging. We report a baseline investigation of variability in taxonomic profiling for the Microbiome Quality Control (MBQC) project baseline study (MBQC-base). Blinded specimen sets from human stool, chemostats, and artificial microbial communities were sequenced by 15 laboratories and analyzed using nine bioinformatics protocols. Variability depended most on biospecimen type and origin, followed by DNA extraction, sample handling environment, and bioinformatics. Analysis of artificial community specimens revealed differences in extraction efficiency and bioinformatic classification. These results may guide researchers in experimental design choices for gut microbiome studies.

2. 宏基因组分析方法评估 - 宏基因组学分析软件的标准

Critical Assessment of Metagenome Interpretation—a benchmark of metagenomics software(Nature Methods)

Abstract

Methods for assembly, taxonomic profiling and binning are key to interpreting metagenome data, but a lack of consensus about benchmarking complicates performance assessment. The Critical Assessment of Metagenome Interpretation (CAMI) challenge has engaged the global developer community to benchmark their programs on highly complex and realistic data sets, generated from ~700 newly sequenced microorganisms and ~600 novel viruses and plasmids and representing common experimental setups. Assembly and genome binning programs performed well for species represented by individual genomes but were substantially affected by the presence of related strains. Taxonomic profiling and binning programs were proficient at high taxonomic ranks, with a notable performance decrease below family level. Parameter settings markedly affected performance, underscoring their importance for program reproducibility. The CAMI results highlight current challenges but also provide a roadmap for software selection to answer specific research questions.

3. 人类微生物项目中的不断扩展的菌株，功能

Strains, functions and dynamics in the expanded Human Microbiome Project（Nature）

Abstract

The characterization of baseline microbial and functional diversity in the human microbiome has enabled studies of microbiome-related disease, diversity, biogeography, and molecular function. The National Institutes of Health Human Microbiome Project has provided one of the broadest such characterizations so far. Here we introduce a second wave of data from the study, comprising 1,631 new metagenomes (2,355 total) targeting diverse body sites with multiple time points in 265 individuals. We applied updated profiling and assembly methods to provide new characterizations of microbiome personalization. Strain identification revealed subspecies clades specific to body sites; it also quantified species with phylogenetic diversity under-represented in isolate genomes. Body-wide functional profiling classified pathways into universal, human-enriched, and body site-enriched subsets. Finally, temporal analysis decomposed microbial variation into rapidly variable, moderately variable, and stable subsets. This study furthers our knowledge of baseline human microbial diversity and enables an understanding of personalized microbiome function and dynamics.

4. 无需比对的序列比较：优点，应用和工具

Alignment-free sequence comparison: benefits, applications, and tools（Genome Biology）

Abstract

Alignment-free sequence analyses have been applied to problems ranging from whole-genome phylogeny to the classification of protein families, identification of horizontally transferred genes, and detection of recombined sequences. The strength of these methods makes them particularly useful for next-generation sequencing data processing and analysis. However, many researchers are unclear about how these methods work, how they compare to alignment-based methods, and what their potential is for use for their research. We address these questions and provide a guide to the currently available alignment-free sequence analysis tools.

5.MetaGen：不借助于参考基因组使用多个宏基因组样本进行训练的分析工具

MetaGen: reference-free learning with multiple metagenomic samples（Genome Biology）

Abstract

A major goal of metagenomics is to identify and study the entire collection of microbial species in a set of targeted samples. We describe a statistical metagenomic algorithm that simultaneously identifies microbial species and estimates their abundances without using reference genomes. As a trade-off, we require multiple metagenomic samples, usually ≥10 samples, to get highly accurate binning results. Compared to reference-free methods based primarily on k-mer distributions or coverage information, the proposed approach achieves a higher species binning accuracy and is particularly powerful when sequencing coverage is low. We demonstrated the performance of this new method through both simulation and real metagenomic studies. 

.

6. DEIsoM：使用生物学重复识别存在差异表达的可变剪接转录本的一个层次贝叶斯模型

DEIsoM: a hierarchical Bayesian model for identifying differentially expressed isoforms using biological replicates (Bioinformatics)

Abstract

Motivation

High-throughput mRNA sequencing (RNA-Seq) is a powerful tool for quantifying gene expression. Identification of transcript isoforms that are differentially expressed in different conditions, such as in patients and healthy subjects, can provide insights into the molecular basis of diseases. Current transcript quantification approaches, however, do not take advantage of the shared information in the biological replicates, potentially decreasing sensitivity and accuracy.

Results

We present a novel hierarchical Bayesian model called Differentially Expressed Isoform detection from Multiple biological replicates (DEIsoM) for identifying differentially expressed (DE) isoforms from multiple biological replicates representing two conditions, e.g. multiple samples from healthy and diseased subjects. DEIsoM first estimates isoform expression within each condition by (1) capturing common patterns from sample replicates while allowing individual differences, and (2) modeling the uncertainty introduced by ambiguous read mapping in each replicate. Specifically, we introduce a Dirichlet prior distribution to capture the common expression pattern of replicates from the same condition, and treat the isoform expression of individual replicates as samples from this distribution. Ambiguous read mapping is modeled as a multinomial distribution, and ambiguous reads are assigned to the most probable isoform in each replicate. Additionally, DEIsoM couples an efficient variational inference and a post-analysis method to improve the accuracy and speed of identification of DE isoforms over alternative methods. Application of DEIsoM to an hepatocellular carcinoma (HCC) dataset identifies biologically relevant DE isoforms. The relevance of these genes/isoforms to HCC are supported by principal component analysis (PCA), read coverage visualization, and the biological literature.

7. MotifHyades：最大可能的从配对的序列进行从头DNA的motif的识别

MotifHyades: expectation maximization for de novo DNA motif pair discovery on paired sequences  (Bioinformatics)

Abstract

Motivation

In higher eukaryotes, protein–DNA binding interactions are the central activities in gene regulation. In particular, DNA motifs such as transcription factor binding sites are the key components in gene transcription. Harnessing the recently available chromatin interaction data, computational methods are desired for identifying the coupling DNA motif pairs enriched on long-range chromatin-interacting sequence pairs (e.g. promoter–enhancer pairs) systematically.

Results

To fill the void, a novel probabilistic model (namely, MotifHyades) is proposed and developed for de novo DNA motif pair discovery on paired sequences. In particular, two expectation maximization algorithms are derived for efficient model training with linear computational complexity. Under diverse scenarios, MotifHyades is demonstrated faster and more accurate than the existing ad hoc computational pipeline. In addition, MotifHyades is applied to discover thousands of DNA motif pairs with higher gold standard motif matching ratio, higher DNase accessibility and higher evolutionary conservation than the previous ones in the human K562 cell line. Lastly, it has been run on five other human cell lines (i.e. GM12878, HeLa-S3, HUVEC, IMR90, and NHEK), revealing another thousands of novel DNA motif pairs which are characterized across a broad spectrum of genomic features on long-range promoter–enhancer pairs.

8. karyoploteR：用于在基因组上绘制显示任意数据的R 包

karyoploteR: an R/Bioconductor package to plot customizable genomes displaying arbitrary data（Bioinformatics）

Abstract

Motivation

Data visualization is a crucial tool for data exploration, analysis and interpretation. For the visualization of genomic data there lacks a tool to create customizable non-circular plots of whole genomes from any species.

Results

We have developed karyoploteR, an R/Bioconductor package to create linear chromosomal representations of any genome with genomic annotations and experimental data plotted along them. Plot creation process is inspired in R base graphics, with a main function creating karyoplots with no data and multiple additional functions, including custom functions written by the end-user, adding data and other graphical elements. This approach allows the creation of highly customizable plots from arbitrary data with complete freedom on data positioning and representation.

9.runBNG：使用光学图谱对基因组进行分析的命令行工具包

runBNG: a software package for BioNano genomic analysis on the command line（Bioinformatics）

Abstract

Summary

We developed runBNG, an open-source software package which wraps BioNano genomic analysis tools into a single script that can be run on the command line. runBNG can complete analyses, including quality control of single molecule maps, optical map de novo assembly, comparisons between different optical maps, super-scaffolding and structural variation detection. Compared to existing software BioNano IrysView and the KSU scripts, the major advantages of runBNG are that the whole pipeline runs on one single platform and it has a high customizability.

欢迎关注生信人