Julio Gutiérrez1, Karel H M van Wely2, Carlos Martínez-A2. 1. Department of Immunology and Oncology, Centro Nacional de Biotecnología-CSIC, Darwin 3, 28049, Madrid, Spain. jgutierrez@cnb.csic.es. 2. Department of Immunology and Oncology, Centro Nacional de Biotecnología-CSIC, Darwin 3, 28049, Madrid, Spain.
Correction to: Cell & Bioscience (2022) 12:84 https://doi.org/10.1186/s13578-022-00804-8
After publication of the original article [1], we realized that two files in the Supplementary Information, Additional files 4 and 7, were incorrect. The correct Additional files 4 and 7 are available on Cell & Bioscience’s website from the date of publication of this note.In addition, a part of the Methods section was missing in the original article. Methods for Additional file 4 are as follows:Burrows-Wheeler aligner BWA-MEM 0.7.15 (RRID:SCR_010910) was used to align paired-end reads to the UCSC mouse genome build mm10 with standard settings. Alignments were converted to BAM format and de-duplicated with Picard tools 2.9.0 (RRID:SCR_006525). To quantify relative expression of transcripts, we ran StringTie 1.3.3 (RRID:SCR_016323) [2] and calculated the transcripts per million (TPM) reads. Sample scaling and statistical analyses were performed with the R package edgeR (RRID:SCR_012802) [3]. Transcripts with TPM > 0 in all samples were kept for downstream analysis. Differentially expressed genes with an absolute value of log2 fold change ≥ 1 and a false-discovery rate (FDR) < 0.05 were considered statistically significant.Additional file 4. List of genes over- or underexpressed in E16 vs. WT livers.Additional file 7. Analysis of compositional biases around splice sites in E16 vs. WT livers.
Authors: Mihaela Pertea; Geo M Pertea; Corina M Antonescu; Tsung-Cheng Chang; Joshua T Mendell; Steven L Salzberg Journal: Nat Biotechnol Date: 2015-02-18 Impact factor: 54.908