On the use of QDE-SVM for gene feature selection and cell type classification from scRNA-seq data.

Cell type identification is one of the fundamental tasks in single-cell RNA sequencing (scRNA-seq) studies. It is a key step to facilitate downstream interpretations such as differential expression, trajectory inference, etc. scRNA-seq data contains technical variations that could affect the interpretation of the cell types. Therefore, gene selection, also known as feature selection in data science, plays an important role in selecting informative genes for scRNA-seq cell type identification. Generally speaking, feature selection methods are categorized into filter-, wrapper-, and embedded-based approaches. From the existing literature, methods from filter- and embedded-based approaches are widely applied in scRNA-seq gene selection tasks. The wrapper-based method that gives promising results in other fields has yet been extensively utilized for selecting gene features from scRNA-seq data; in addition, most of the existing wrapper methods used in this field are clustering instead of classification-based. With a large number of annotated data available today, this study applied a classification-based approach as an alternative to the clustering-based wrapper method. In our work, a quantum-inspired differential evolution (QDE) wrapped with a classification method was introduced to select a subset of genes from twelve well-known scRNA-seq transcriptomic datasets to identify cell types. In particular, the QDE was combined with different machine-learning (ML) classifiers namely logistic regression, decision tree, support vector machine (SVM) with linear and radial basis function kernels, as well as extreme learning machine. The linear SVM wrapped with QDE, namely QDE-SVM, was chosen by referring to the feature selection results from the experiment. QDE-SVM showed a superior cell type classification performance among QDE wrapping with other ML classifiers as well as the recent wrapper methods (i.e., FSCAM, SSD-LAHC, MA-HS, and BSF). QDE-SVM achieved an average accuracy of 0.9559, while the other wrapper methods achieved average accuracies in the range of 0.8292 to 0.8872.

RNA-seq data of Ganoderma boninense at axenic culture condition and under in planta pathogen-oil palm (Elaeis guineensis Jacq.) interaction.

OBJECTIVE: Basal stem rot disease causes severe economic losses to oil palm production in South-east Asia and little is known on the pathogenicity of the pathogen, the basidiomyceteous Ganoderma boninense. Our data presented here aims to identify both the house-keeping and pathogenicity genes of G. boninense using Illumina sequencing reads. DESCRIPTION: The hemibiotroph G. boninense establishes via root contact during early stage of colonization and subsequently kills the host tissue as the disease progresses. Information on the pathogenicity factors/genes that causes BSR remain poorly understood. In addition, the molecular expressions corresponding to G. boninense growth and pathogenicity are not reported. Here, six transcriptome datasets of G. boninense from two contrasting conditions (three biological replicates per condition) are presented. The first datasets, collected from a 7-day-old axenic condition provide an insight onto genes responsible for sustenance, growth and development of G. boninense while datasets of the infecting G. boninense collected from oil palm-G. boninense pathosystem (in planta condition) at 1 month post-inoculation offer a comprehensive avenue to understand G. boninense pathogenesis and infection especially in regard to molecular mechanisms and pathways. Raw sequences deposited in Sequence Read Archive (SRA) are available at NCBI SRA portal with PRJNA514399, bioproject ID.

Draft Genome Sequence of Mycobacterium massiliense Strain M159, Showing Phenotypic Resistance to ß-Lactam and Tetracycline Antibiotics.

Mycobacterium massiliense is a nontuberculous mycobacterium associated with human infections. We report here the draft genome sequence of M. massiliense strain M159, isolated from the bronchial aspirate of a patient who had a pulmonary infection. This strain showed genotypic and in vitro resistance to a number of tetracyclines and beta-lactam antibiotics.

Whole-Genome Shotgun Sequencing of Mycobacterium abscessus M156, an Emerging Clinical Pathogen in Malaysia.

Mycobacterium abscessus is an emerging clinical pathogen commonly associated with non-tuberculous mycobacterial infections. We report herein the draft genome of M. abscessus strain M156.

Genome sequence of Mycobacterium abscessus strain M152.

Mycobacterium abscessus is an environmental bacterium with increasing clinical relevance. Here, we report the annotated whole-genome sequence of M. abscessus strain M152.

Analysis of the genome of Mycobacterium abscessus strain M94 reveals an uncommon cluster of tRNAs.

Mycobacterium abscessus is a species of rapidly growing nontuberculous mycobacteria that is frequently associated with opportunistic infections in humans. Here, we report the annotated genome sequence of M. abscessus strain M94, which showed an unusual cluster of tRNAs.

Annotated genome sequence of Mycobacterium massiliense strain M154, belonging to the recently created taxon Mycobacterium abscessus subsp. bolletii comb. nov.

Mycobacterium massiliense has recently been proposed as a member of Mycobacterium abscessus subsp. bolletii comb. nov. Strain M154, a clinical isolate from the bronchoalveolar lavage fluid of a Malaysian patient presenting with lower respiratory tract infection, was subjected to shotgun DNA sequencing with the Illumina sequencing technology to obtain whole-genome sequence data for comparison with other genetically related strains within the M. abscessus species complex.

Genomic Analysis of Mycobacterium massiliense strain M115, an isolate from human sputum.

We report the draft genome sequence of a clinical isolate, strain M115, identified as Mycobacterium massiliense, a member of the newly created taxon of Mycobacterium abscessus subspecies bolletii comb. nov.

Genome analysis of Mycobacterium massiliense strain M172, which contains a putative mycobacteriophage.

The genome of Mycobacterium massiliense M172, isolated from a human sputum sample, was sequenced using Illumina GA IIX technology and found to contain 5,204,460 bp, including putative genes for virulence and antibiotic resistance as well as a 92-kb genomic region most likely to correspond to a mycobacteriophage.

Draft genome sequence of Mycobacterium bolletii strain M24, a rapidly growing mycobacterium of contentious taxonomic status.

The whole-genome sequence of Mycobacterium bolletii M24, isolated from the bronchoalveolar lavage fluid of a Malaysian patient, is reported here. The circular chromosome of 5,507,730 bp helped to clarify the taxonomic position of this organism within the M. abscessus complex and revealed the presence of proteins potentially important for pathogenicity in a human host.

Genome sequence of Mycobacterium massiliense M18, isolated from a lymph node biopsy specimen.

Mycobacterium massiliense is a rapidly growing mycobacterial species. The pathogenicity of this subspecies is not well known. We report here the annotated genome sequence of M. massiliense strain M18, which was isolated from a lymph node biopsy specimen from a Malaysian patient suspected of having tuberculous cervical lymphadenitis.

Genome sequence of the Mycobacterium abscessus strain M93.

Mycobacterium abscessus is a rapid-growing species of nontuberculous mycobacteria that is frequently associated with opportunistic infections in humans. We report herein the draft genome sequence of M. abscessus strain M93.

Evaluation of PCR-RFLP analysis targeting hsp65 and rpoB genes for the typing of mycobacterial isolates in Malaysia.

In this study, PCR-RFLP analysis (PRA) targeting hsp65 and rpoB gene regions was evaluated for the identification of mycobacterial species isolated from Malaysian patients. Overall, the hsp65 PRA identified 92.2 % of 90 isolates compared to 85.6 % by the rpoB PRA. With 47 rapidly growing species, the hsp65 PRA identified fewer (89.4 %) species than the rpoB PRA (95.7 %), but with 23 slow-growing species the reverse was true (91.3 % identification by the hsp65 PRA but only 52.5 % by the rpoB PRA). There were 16 isolates with discordant PRA results, which were resolved by 16S rRNA and hsp65 gene sequence analysis. The findings in this study suggest that the hsp65 PRA is more useful than the rpoB PRA for the identification of Mycobacterium species, particularly with the slow-growing members of the genus. In addition, this study reports 5 and 12 novel restriction patterns for inclusion in the hsp65 and rpoB PRA algorithms, respectively.