Springer Nature
Browse
12859_2020_3399_MOESM3_ESM.pdf (102.45 kB)

Additional file 3 of iSeqQC: a tool for expression-based quality control in RNA sequencing

Download (102.45 kB)
journal contribution
posted on 2020-02-14, 08:11 authored by Gaurav Kumar, Adam Ertel, George Feldman, Joan Kupper, Paolo Fortina
Additional file 3. Public Dataset Results. Quality control metrics produced by iSeqQC from other datasets. A) Counts distribution plot showing several low-expressed samples on Bottomly dataset; B) GC-bias plot showing no GC-content bias in any samples on Bottomly dataset; C) Unsupervised PCA clustering (un-normalized) showing variation in several samples in Risso dataset; D) Multifactor PCA showing library protocol method and different flow cell to be the major source of the variation; E) Unsupervised PCA clustering (un-normalized) showing samples clustered based on RNA extraction method in Tarazona dataset; F) Multifactor PCA showing RNA-extraction method to be the major source of variation.

Funding

National Cancer Institute

History