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  • Erratum
  • Open Access

Erratum to: Statistically based splicing detection reveals neural enrichment and tissue-specific induction of circular RNA during human fetal development

  • 1,
  • 2,
  • 3,
  • 1,
  • 2,
  • 2,
  • 4,
  • 3,
  • 2Email author and
  • 1Email author
Genome Biology201617:263

https://doi.org/10.1186/s13059-016-1123-9

  • Received: 1 December 2016
  • Accepted: 1 December 2016
  • Published:

The original article was published in Genome Biology 2015 16:126

Erratum

In this version of this article that was originally published [1] the authors had analysed two HeLa samples, SRR1637089 and SRR1637090, in Fig. 3 of the original publication. The authors had respectively analysed the samples as RNaseR+ and Ribominus, due to their incorrect annotations in a public database, but they were both Ribominus samples. The authors have now analysed appropriate positive and negative controls using their method, KNIFE, and find_circ. The results are presented in an amended version of Fig. 3c, please see updated version below. Furthermore, the authors have now provided a list of accession codes for the ENCODE data they analysed, please see the Table 1 below. Please note this was not part of the original article.
Fig. 3
Fig. 3

Statistical algorithm improves the sensitivity of circular RNA detection. a, b Circular RNA detected by both algorithms are divided into false positives (FP; flagged as false positives due to low posterior probability) or true positives (TP; our posterior probability ≥ 0.9). a Number of circular RNAs detected by our GLM or CIRI in ENCODE BJ poly(A)+/− data and HeLa RNase-R+/− data generated by Gao et al. [23]. CIRI results are based on all default parameters except the -E flag set to exclude false positives resulting from identical colinear exons. b Number of circular RNAs detected by our GLM or find_circ in ENCODE BJ poly(A)+/− data and HeLa RNase-R- data generated by Gao et al. [23]. c Circular RNAs detected in HeLa RNase-R+ and Ribo- data generated by Gao et al. [23] and poly(A)+, and poly(A)- data generated by ENCODE. Number of circular RNAs detected by our GLM method (one or more reads, posterior probability ≥ 0.9) compared with CIRI (default parameters except -E). For GLM results, the first number is the total number of circles and the number of those which were detected by the de novo portion of the algorithm are listed in parentheses. d Venn diagram comparing the number of putative circular RNAs identified by our annotation-dependent algorithm in Rnase-R-treated H9 cells and the results published by Zhang et al. [22]. Green circles and red circles show circular RNA identified by our algorithm with high and low confidence, respectively; the blue circle shows those identified by Zhang et al. e Total junctional reads for circles comprised of a single exon (posterior probability ≥ 0.9, read count > 1) shown by size for same data as in panel (d). Median exon length is shown in red. The x-axis is truncated at 2000 excluding 31 long exons, all but one with total read counts < 50]

Table 1

ENCODE accession codes

Source

Type

ACCESSION

A549

cell line, polyA+

GSM758564

AGO4450

cell line, polyA+

GSM758561

BJ

cell line, polyA+

GSM758562

GM12878

cell line, polyA+

GSM758559

H1

cell line, polyA+

GSM758566

HMEC

cell line, polyA+

GSM758571

HeLa

cell line, polyA+

GSM765402

HepG2

cell line, polyA+

GSM758575

HSSM

cell line, polyA+

GSM758578

HUVEC

cell line, polyA+

GSM758563

IMR90

cell line, polyA+

GSM981249

K562

cell line, polyA+

GSM765405

MCF7

cell line, polyA+

GSM765388

NHEK

cell line, polyA+

GSM765401

NHLF

cell line, polyA+

GSM765394

SKNSHRA

cell line, polyA+

GSM765395

A549

cell line, polyA-

GSM767854

AGO4450

cell line, polyA-

GSM765396

BJ

cell line, polyA-

GSM767855

GM12878

cell line, polyA-

GSM758572

H1

cell line, polyA-

GSM758573

HMEC

cell line, polyA-

GSM765397

HeLa

cell line, polyA-

GSM767847

HepG2

cell line, polyA-

GSM758567

HSSM

cell line, polyA-

GSM765391

HUVEC

cell line, polyA-

GSM767856

K562

cell line, polyA-

GSM758577

MCF7

cell line, polyA-

GSM767851

NHEK

cell line, polyA-

GSM765398

NHLF

cell line, polyA-

GSM765389

SKNSHRA

cell line, polyA-

GSM767845

camera-type eye

tissue

ENCSR000AFO

cerebellum

tissue

ENCSR000AEW

diencephalon

tissue

ENCSR000AEX

frontal cortex

tissue

ENCSR000AEY

heart

tissue

ENCSR000AEZ

heart

tissue

ENCSR000AHH

liver

tissue

ENCSR000AEU

liver

tissue

ENCSR000AFB

lung

tissue

ENCSR000AFC

metanephros

tissue

ENCSR000AFA

mononuclear cell

tissue

ENCSR000CUT

occipital lobe

tissue

ENCSR000AFD

parietal lobe

tissue

ENCSR000AFE

skeletal muscle

tissue

ENCSR000AFF

skin of body

tissue

ENCSR000AFG

spinal cord

tissue

ENCSR000AFH

stomach

tissue

ENCSR000AFI

temporal lobe

tissue

ENCSR000AFJ

thyroid gland

tissue

ENCSR000AFK

tongue

tissue

ENCSR000AFL

umbilical cord

tissue

ENCSR000AFM

urinary bladder

tissue

ENCSR000AEV

uterus

tissue

ENCSR000AFN

Source (cell line name or tissue type), Type of sample (tissue, polyA+ cell line, or polyA- cell line), and Accession code for all ENCODE data analyzed.]

Notes

Declarations

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Stanford Department of Biochemistry and Stanford Cancer Institute, Stanford, CA, USA
(2)
UC San Diego Department of Reproductive Medicine, San Diego, CA, USA
(3)
Center for Cardiovascular Biology, Institute for Stem Cell and Regenerative Medicine, Departments of Pathology, Bioengineering and Medicine/Cardiology, University of Washington, Seattle, WA 98109, USA
(4)
UC San Diego Department of Pathology, San Diego, CA, USA

Reference

  1. Szabo L, Morey R, Palpant NJ, Wang PL, Afari N, Jiang C, et al. Statistically based splicing detection reveals neural enrichment and tissue-specific induction of circular RNA during human fetal development. Genome Biol. 2016;16:126.View ArticleGoogle Scholar

Copyright

© The Author(s). 2016

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