Biology subjects

Kirtipal, N.

Publications and source records attributed to Kirtipal, N..

3 recordsLinked to original sources

bioRxiv2024

Normalization of Single-cell RNA-seq Data UsingPartial Least Squares with Adaptive Fuzzy Weight

Normalization of single-cell RNA-seq (scRNA-seq) is a crucial step in downstream analysis, where raw data are adjusted to correct unwanted factors that prevent the direct comparison of expression measures. scRNA-seq data exhibits a multivariate relationship between transcript-specific expression and sequencing depth that a single scale factor cannot address. A partial least squares (PLS) regression was performed to accommodate the variability of gene expression in each condition, and upper and lower quantiles with adaptive fuzzy weights were utilized to correct unwanted biases in scRNA-seq data. The present approach was compared using real and simulated datasets across various state-of-the-art performance measures.

bioinformatics↗

bioRxiv2024

Extensively acquired antimicrobial resistant bacteria restructure the individual microbial community in post-antibiotic conditions

In recent years, the overuse of antibiotics has led to the emergence of antimicrobial resistant (AMR) bacteria. To evaluate the spread of AMR bacteria, the reservoir of AMR genes (resistome) has traditionally been identified from environmental samples, hospital environments, and human populations; however, the functional role of AMR bacteria in the human gut microbiome and their persistency within individuals has not been fully investigated. Here, we performed a strain-resolved in-depth analysis of the resistome changes by reconstructing a large number of metagenome-assembled genomes (MAGs) of antibiotics- treated individuals gut microbiome. Interestingly, we identified two bacterial populations with different resistome profiles, extensively acquired antimicrobial resistant bacteria (EARB) and sporadically acquired antimicrobial resistant bacteria (SARB), and found that EARB showed broader drug resistance and a significant functional role in shaping individual microbiome composition after antibiotic treatment. Furthermore, longitudinal strain analysis revealed that EARB bacteria were inherently carried by individuals and can reemerge through strain switching in the human gut microbiome. Our data on the presence of AMR bacteria in the human gut microbiome provides a new avenue for controlling the spread of AMR bacteria in the human community.

genomics↗

bioRxiv2023

Normalization of RNA-Seq Data using Adaptive Trimmed Mean with Multi-reference

The normalization of RNA sequencing data is a primary step for downstream analysis. The most popular method used for the normalization is the trimmed mean of M values (TMM) and DESeq. The TMM tries to trim away extreme log fold changes of the data to normalize the raw read counts based on the remaining non-deferentially expressed genes. However, the major problem with the TMM is that the values of trimming factor M are heuristic. This paper tries to estimate the adaptive value of M in TMM based on Jaeckels Estimator, and each sample acts as a reference to find the scale factor of each sample. The presented approach is validated on SEQC, MAQC2, MAQC3, PICKRELL, and two simulated datasets with two groups and three groups conditions by varying the percentage of differential expression and the number of replicates. The performance of the present approach is compared, and it shows better in terms of area under the receiver operating characteristic curve (AUC) and differential expression. The implementation of the present approach is available on the GitHub platform: https://github.com/vikkyak/Normalization-of-Bulk-RNA-seq.

bioinformatics↗