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A Simplest Bioinformatics Pipeline for Whole Transcriptome Sequencing: Overview of the Processing and Steps from Raw Data to Downstream Analysis.

Gupta, A.; Gupta, S.; Jatawa, S. K.; Mishra, A. K.; Suravajhala, P.

2019-11-09 bioinformatics
10.1101/836973 bioRxiv
Show abstract

Recent advances in next generation sequencing (NGS) technologies have heralded the genomic research. From the good-old inferring differentially expressed genes (DEG) using microarray to the current adage NGS-based whole transcriptome or RNA-Seq pipelines, there have been advances and improvements. With several bioinformatics pipelines for analysing RNA-Seq on rise, inferring the candidate DEGs prove to be a cumbersome approach as one may have to reach consensus among all the pipelines. To Check this, we have benchmarked the well known cufflinks-cuffdiff pipeline on a set of datasets and outline it in the form of a protocol where researchers interested in performing whole transcriptome shotgun sequencing and its downstream analysis can better disseminate the analysis using their datasets.

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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.