The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
CHESS 3: an improved, comprehensive catalog of human genes and transcripts based on large-scale expression data, phylogenetic analysis, and protein structure
Open accessPreprint — published as 10.1186/s13059-023-03088-4 · Paper page
Abstract
The original CHESS database of human genes was assembled from nearly 10,000 RNA sequencing experiments in 53 human body sites produced by the Genotype-Tissue Expression (GTEx) project, and then augmented with genes from other databases to yield a comprehensive collection of protein-coding and noncoding transcripts. The construction of the new CHESS 3 database employed improved transcript assembly algorithms, a new machine learning classifier, and protein structure predictions to identify genes and transcripts likely to be functional and to eliminate those that appeared more likely to represent noise. The new catalog contains 41,356 genes on the GRCh38 reference human genome, of which 19,839 are protein-coding, and a total of 158,377 transcripts. These include 14,863 novel protein-coding transcripts. The total number of transcripts is substantially smaller than earlier versions due to improved transcriptome assembly methods and to a stricter protocol for filtering out noisy transcripts. Notably, CHESS 3 contains all of the transcripts in the MANE database, and at least one transcript corresponding to the vast majority of protein-coding genes in the RefSeq and GENCODE databases. CHESS 3 has also been mapped onto the complete CHM13 human genome, which gives a more-complete gene count of 43,773 genes and 19,968 protein-coding genes. The CHESS database is available at http://ccb.jhu.edu/chess .
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Highly accurate protein structure prediction with AlphaFold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764
Self-citation
Flagged first, then by citations
Research works printed but not linked: 35
- 10.1126/science.abj6987 · DOI · Paper page
- Frankish, A. , S. Carbonell-Sala , M. Diekhans , et al. GENCODE: reference annotation for the human and mouse genomes in 2023. Nucleic Acids Res, 2022. · DOI
- 2020, Liftoff: accurate mapping of gene annotations, Bioinformatics, 37, 1639
- 10.1093/nar/gkv1189 · DOI · Paper page
- 10.1186/s13059-018-1590-2 · DOI · Paper page
- 10.1038/nature21374 · DOI · Paper page
- 2022, APPRIS: selecting functionally important isoforms, Nucleic Acids Res, 50, D54, 10.1093/nar/gkab1058 · DOI
- 10.1126/science.1262110 · DOI · Paper page
- 10.1038/s41586-022-04558-8 · DOI · Paper page
- 10.1016/j.tibs.2016.08.008 · DOI
- Varabyou, A. , S.L. Salzberg , and M. Pertea . Effects of transcriptional noise on estimates of gene and transcript expression in RNA sequencing experiments. Genome Res, 2020. · DOI
- 2017, Novex-3, the tiny titin of muscle, Biophys Rev, 9, 201, 10.1007/s12551-017-0261-y · DOI
- 10.1096/fj.11-187971 · DOI
- 2022, ColabFold: making protein folding accessible to all, Nat Methods, 19, 679, 10.1038/s41592-022-01488-1 · DOI · Paper page
- 2021, Highly accurate protein structure prediction for the human proteome, Nature, 596, 590, 10.1038/s41586-021-03828-1 · DOI · Paper page
- 10.1093/nar/gkaa1046 · DOI
- 10.1093/nar/gky1031 · DOI · Paper page
- 2020, lncRNAKB, a knowledgebase of tissue-specific functional annotation and trait association of long noncoding RNA, Sci Data, 7, 326, 10.1038/s41597-020-00659-z · DOI
- RNAcentral Consortium, 2021, RNAcentral 2021: secondary structure integration, improved sequence search and new member databases, Nucleic Acids Res, 49, D212, 10.1093/nar/gkaa921 · DOI · Paper page
- Pertea, M. , A. Shumate , G. Pertea , et al. Thousands of large-scale RNA sequencing experiments yield a comprehensive new human gene list and reveal extensive transcriptional noise. bioRxiv, 2018. · DOI
- 2022, Genome-Wide Analysis of Human Long Noncoding RNAs: A Provocative Review, Annu Rev Genomics Hum Genet, 23, 153, 10.1146/annurev-genom-112921-123710 · DOI · Paper page
- 10.1101/gr.229102. Article published online before print in May 2002 · DOI · Paper page
- Shumate, A. and S.L. Salzberg . Liftoff: accurate mapping of gene annotations. Bioinformatics, 2020. · DOI
- 10.1038/ng.437 · DOI · Paper page
- 10.1038/ng.2653 · DOI · Paper page
- 10.1038/s41587-019-0201-4 · DOI · Paper page
- 2020, Reference genome and transcriptome informed by the sex chromosome complement of the sample increase ability to detect sex differences in gene expression from RNA-Seq data, Biol Sex Differ, 11, 42, 10.1186/s13293-020-00312-9 · DOI
- 10.1186/s13059-019-1910-1 · DOI
- 2021, TieBrush: an efficient method for aggregating and summarizing mapped reads across large datasets, Bioinformatics, 37, 3650, 10.1093/bioinformatics/btab342 · DOI
- Monzon, V. , D.H. Haft , and A. Bateman . Folding the unfoldable: using AlphaFold to explore spurious proteins. Bioinformatics Advances, 2022. 2(1). · DOI
- Sommer, M.J. , S. Cha , A. Varabyou , et al. Structure-guided isoform identification for the human transcriptome. Elife, 2022. 11. · DOI · Paper page
- 2022, A complete reference genome improves analysis of human genetic variation, Science, 376, eabl3533, 10.1126/science.abl3533 · DOI · Paper page
- 2022, Failure to Detect Mutations in U2AF1 due to Changes in the GRCh38 Reference Sequence, J Mol Diagn, 24, 219, 10.1016/j.jmoldx.2021.10.013 · DOI
- 10.1371/journal.pone.0207531 · DOI
- 10.1093/bioinformatics/btq033 · DOI · Paper page
Metadata
- Authors
- Varabyou, A., Sommer, M. J., Erdogdu, B., Shinder, I., Minkin, I., Chao, K.-H., Park, S., Heinz, J., Pockrandt, C., Shumate, A., Rincon, N., Puiu, D., Steinegger, M., Salzberg, S. L., & Pertea, M.
- Affiliations
- Johns Hopkins University (US)
- Seoul National University (KR)
- Corresponding author
- Varabyou, Ales
- Salzberg, Steven L.
- Pertea, Mihaela
- ORCID
- Venue
- Genome biology
- Publisher
- openRxiv
- Published
- 2022-12-22
- Volume
- 24
- Issue
- 1
- Pages
- 249-249
- ISSN
- 1465-6906 (ISSN-L)
- PMC
- PMC10614308
- OpenAlex
- W4388022000
- Cited by
- 54
- References
- 1
- Citations by year
- 2026: 14 · 2025: 23 · 2024: 13 · 2023: 4
- FWCI
- 4.80
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Genome biology (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Seoul National University Open Repository (Seoul National University) (submittedVersion, other-oa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Seoul National University Open Repository (Seoul National University) (submittedVersion)
- Funders
- National Science Foundation (1759518)
- National Research Foundation (2021-R1C1-C102065)
- Seoul National University
- National Research Foundation of Korea (2021-R1C1-C102065, 2021-M3A9-I4021220, 2020M3‐A9G7‐103933, 2019R1-A6A1-A10073437, 2020M3-A9G7-103933, 2021-R1C1-C102065, and 2021-M3A9-I4021220)
- National Institutes of Health
- Directorate for Biological Sciences (DBI-1759518)
- Samsung
- National Institute of Mental Health (R01MH123567)
- National Human Genome Research Institute (R01HG006677)
- National Institute of General Medical Sciences (R35GM130151)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- transcriptome, RNA-seq, genome annotation, protein-coding genes, transcriptome assembly, Manes, protein structure prediction, noise reduction, human body sites
- MeSH terms
- Algorithms, Humans, Phylogeny, Proteins, Software, Genome, Human, Molecular Sequence Annotation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review