ISeqQC: a tool for expression-based quality control in RNA sequencing.

ABSTRACT:

Background

Quality Control in any high-throughput sequencing technology is a critical step, which if overlooked can compromise an experiment and the resulting conclusions. A number of methods exist to identify biases during sequencing or alignment, yet not many tools exist to interpret biases due to outliers.

Results

Hence, we developed iSeqQC, an expression-based QC tool that detects outliers either produced due to variable laboratory conditions or due to dissimilarity within a phenotypic group. iSeqQC implements various statistical approaches including unsupervised clustering, agglomerative hierarchical clustering and correlation coefficients to provide insight into outliers. It can be utilized through command-line (Github: https://github.com/gkumar09/iSeqQC) or web-interf

SUBMITTER: Kumar G 

PROVIDER: S-EPMC7020508 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature