scholarly journals MetaQUBIC: a computational pipeline for gene-level functional profiling of metagenome and metatranscriptome

2019 ◽  
Vol 35 (24) ◽  
pp. 5397-5397 ◽  
Author(s):  
Anjun Ma ◽  
Minxuan Sun ◽  
Adam McDermaid ◽  
Bingqiang Liu ◽  
Qin Ma
Keyword(s):  
Computational Pipeline ◽  
Gene Level ◽  
Functional Profiling

scholarly journals MetaQUBIC: a computational pipeline for gene-level functional profiling of metagenome and metatranscriptome

2019 ◽  
Vol 35 (21) ◽  
pp. 4474-4477 ◽  
Author(s):  
Anjun Ma ◽  
Minxuan Sun ◽  
Adam McDermaid ◽  
Bingqiang Liu ◽  
Qin Ma
Keyword(s):  
Supplementary Information ◽  
Computational Pipeline ◽  
Data Types ◽  
Human Gut ◽  
Dna And Rna ◽  
Gene Expression Matrix ◽  
Environmental Interactions ◽  
Gene Level ◽  
Functional Profiling ◽  
Expression Matrix

Abstract Motivation Metagenomic and metatranscriptomic analyses can provide an abundance of information related to microbial communities. However, straightforward analysis of this data does not provide optimal results, with a required integration of data types being needed to thoroughly investigate these microbiomes and their environmental interactions. Results Here, we present MetaQUBIC, an integrated biclustering-based computational pipeline for gene module detection that integrates both metagenomic and metatranscriptomic data. Additionally, we used this pipeline to investigate 735 paired DNA and RNA human gut microbiome samples, resulting in a comprehensive hybrid gene expression matrix of 2.3 million cross-species genes in the 735 human fecal samples and 155 functional enriched gene modules. We believe both the MetaQUBIC pipeline and the generated comprehensive human gut hybrid expression matrix will facilitate further investigations into multiple levels of microbiome studies. Availability and implementation The package is freely available at https://github.com/OSU-BMBL/metaqubic. Supplementary information Supplementary data are available at Bioinformatics online.

Fragmentation and matching of human microRNA sequences in 3’utr

MicroRNA ◽  
2020 ◽  
Vol 09 ◽  
Author(s):  
M.S. Parker ◽  
A. Balasubramaniam ◽  
F.R. Sallee ◽  
S.L. Parker
Keyword(s):  
Time Scale ◽  
Point Mutations ◽  
Physical Separation ◽  
Gene Level ◽  
Mature Micrornas

: Matches of mature microRNAs (m-miRs) in human 3’utr can be traced to mutations producing fragments of original m-miR sequences without physical separation. (The by far fewer m-miR matches in 5’utr and cds follow similar patterns.) The sense and antisense m-miR fragments in 3’utr occur at quite similar levels. The fragmentation occurs at gene level by mutation within one of the paired m-miRs, which upon transcription results in increased interactive capability for both former pre-micro (pre-mir) RNA stem partners. The non-mutated stem partner can persist in 3’utr sequences, as is apparent from significant presence of miR-619-5p and miR-5096 and some conservation of 20 other simian-specific m-miR sequences. However, most of m-mir sequences in 3’utr are extensively fragmented, with low preservation of long matches. In flanks of individual m-miR embeds the mutated pre-mir positions are to a degree defined specifically. The m-mir matches of various sizes in 3’utr apparently reflect accumulation, on a phylogenetic time scale, of in-sequence point mutations. Across human 3’utr this fragmentation is significantly less for evolutionarily recent human m-miRs that originate in simians compared to human m-miRs first appearing in lower primates, and especially to human m-miRs introduced in non-primates.

scholarly journals Sequential filtering for clinically relevant variants as a method for clinical interpretation of whole exome sequencing findings in glioma

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Ege Ülgen ◽  
Özge Can ◽  
Kaya Bilguvar ◽  
Cemaliye Akyerli Boylu ◽  
Şirin Kılıçturgay Yüksel ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Clinical Analysis ◽  
Clinical Interpretation ◽  
Germline Variants ◽  
Whole Exome ◽  
Gene Level ◽  
Analysis Workflow ◽  
Tumor Mutational Burden ◽  
Diffuse Gliomas

Abstract Background In the clinical setting, workflows for analyzing individual genomics data should be both comprehensive and convenient for clinical interpretation. In an effort for comprehensiveness and practicality, we attempted to create a clinical individual whole exome sequencing (WES) analysis workflow, allowing identification of genomic alterations and presentation of neurooncologically-relevant findings. Methods The analysis workflow detects germline and somatic variants and presents: (1) germline variants, (2) somatic short variants, (3) tumor mutational burden (TMB), (4) microsatellite instability (MSI), (5) somatic copy number alterations (SCNA), (6) SCNA burden, (7) loss of heterozygosity, (8) genes with double-hit, (9) mutational signatures, and (10) pathway enrichment analyses. Using the workflow, 58 WES analyses from matched blood and tumor samples of 52 patients were analyzed: 47 primary and 11 recurrent diffuse gliomas. Results The median mean read depths were 199.88 for tumor and 110.955 for normal samples. For germline variants, a median of 22 (14–33) variants per patient was reported. There was a median of 6 (0–590) reported somatic short variants per tumor. A median of 19 (0–94) broad SCNAs and a median of 6 (0–12) gene-level SCNAs were reported per tumor. The gene with the most frequent somatic short variants was TP53 (41.38%). The most frequent chromosome-/arm-level SCNA events were chr7 amplification, chr22q loss, and chr10 loss. TMB in primary gliomas were significantly lower than in recurrent tumors (p = 0.002). MSI incidence was low (6.9%). Conclusions We demonstrate that WES can be practically and efficiently utilized for clinical analysis of individual brain tumors. The results display that NOTATES produces clinically relevant results in a concise but exhaustive manner.

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