Improvements and impacts of GRCh38 human reference on high throughput sequencing data analysis
Open accessAbstract
Analyses of high throughput sequencing data starts with alignment against a reference genome, which is the foundation for all re-sequencing data analyses. Each new release of the human reference genome has been augmented with improved accuracy and completeness. It is presumed that the latest release of human reference genome, GRCh38 will contribute more to high throughput sequencing data analysis by providing more accuracy. But the amount of improvement has not yet been quantified. We conducted a study to compare the genomic analysis results between the GRCh38 reference and its predecessor GRCh37. Through analyses of alignment, single nucleotide polymorphisms, small insertion/deletions, copy number and structural variants, we show that GRCh38 offers overall more accurate analysis of human sequencing data. More importantly, GRCh38 produced fewer false positive structural variants. In conclusion, GRCh38 is an improvement over GRCh37 not only from the genome assembly aspect, but also yields more reliable genomic analysis results.
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“Gene density can be represented as the exome percentage per chromosome calculated as sum of all exon length within a chromosome divided by the chromosome length (Guo et al., 2017).”
Self-citationPálinkás, H. L., Békési, A., Róna, G., Pongor, L. S., Papp, G., Tihanyi, G., Holub, E., Póti, Á., Gemma, C., Ali, S., et al. (2020) · eLife · doi:10.7554/elife.60498 · Cited by 23 · see citing works
Barbitoff, Y. A., Ushakov, M. O., Lazareva, T. E., Nasykhova, Y. A., Glotov, A. S., & Predeus, A. V. (2023) · Briefings in Bioinformatics · doi:10.1093/bib/bbad508 · Cited by 26 · see citing works
“In general, switching to the hg38 reference genome assembly introduced several notable improvements, in particular, in light of variant calling [86, 87].”
BackgroundRivera‐Mulia, J. C., Kim, S., Gabr, H., Chakraborty, A., Ay, F., Kahveci, T., & Gilbert, D. M. (2019) · Genome Research · doi:10.1101/gr.247049.118 · Cited by 22 · see citing works
“Realigning our data to hg38 (GRCh38) would not significantly affect our conclusions as the major improvements of hg38 assembly are in the annotation of centromeric and other repetitive genomic regions (Guo et al. 2017), which are not included in our analysis.”
MethodPalafox, M. F., Desai, H. S., Arboleda, V. A., & Backus, K. M. (2021) · Molecular Systems Biology · doi:10.15252/msb.20209840 · Cited by 19 · see citing works
“One key application of these tools is in the improved prediction of variant pathogenicity (Guo et al , 2017).”
Colin, E., Duffourd, Y., Tisserant, É., Relator, R., Bruel, A., Mau‐Them, F. T., Denommé‐Pichon, A., Safraou, H., Delanne, J., Jean‐Marçais, N., et al. (2022) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2022.1021785 · Cited by 21 · see citing works
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“DUX4 overexpression activates genes associated with RNA metabolism processes, stem cell and germ-line development, and MERVL/HERVL retrotransposons (Geng et al. 2012; Young et al. 2013; Rickard et al. 2015; Hendrickson et al. 2017), 5These authors contributed equally to this work.”
BackgroundZeng, Z., Yi, Z., & Xu, B. (2025) · Cancer Letters · doi:10.1016/j.canlet.2025.217574 · Cited by 20 · see citing works
Li, G., Zhou, Z.-H., Yao, L., Xu, Y., Wang, L., & Fan, X. (2019) · Transfusion · doi:10.1111/trf.15476 · Cited by 18 · see citing works
Page, M. L., Vance, E. L., Cloward, M. E., Ringger, E., Dayton, L., Ebbert, M., Initiative, T. A. D. N., Investigator, P., Weiner, M. W., Aisen, P. S. S., et al. (2022) · Communications Biology · doi:10.1038/s42003-022-03795-x · Cited by 19 · see citing works
Genomic Tackling of Human Satellite DNA: Breaking Barriers through Time
Lopes, M., Louzada, S., Gama‐Carvalho, M., & Chaves, R. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22094707 · Cited by 18 · see citing works
Chromatin Hubs: A biological and computational outlook
Mora, A., Huang, X., Jauhari, S., Jiang, Q. L., & Li, X. (2022) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2022.07.002 · Cited by 17 · see citing works
“For example, many of the computational methods here reviewed still use hg19 data (see JEME’s and SEPT’s articles), a reference genome version that does not include centromere and other interesting heterochromatic data [168].”
MethodSheng, X., Xia, L. Y., Cahoon, J. L., Conti, D. V., Haiman, C. A., Kachuri, L., & Chiang, C. W. K. (2022) · Human Genetics and Genomics Advances · doi:10.1016/j.xhgg.2022.100159 · Cited by 16 · see citing works
“5 As such, there is a constant need to update the coordinate systems of these legacy datasets to ensure compatibility with data produced by the latest genotyping or sequencing platforms.”
Lees, W., Saha, S., Yaari, G., & Watson, C. T. (2024) · Bioinformatics · doi:10.1093/bioinformatics/btae144 · Cited by 16 · see citing works
“We compared Digger’s annotations to five IMGT-curated loci from the human reference assembly GRCh38.p12 (Guo et al. 2017) and the three IG loci from the rhesus macaque reference assembly rheMac10 (Warren et al. 2020, Nguefack Ngoune et al. 2022).”
Method‘There and Back Again’—Forward Genetics and Reverse Phenotyping in Pulmonary Arterial Hypertension
Swietlik, E. M., Prapa, M., Martin, J. M., Pandya, D., Auckland, K., Morrell, N. W., & Gräf, S. (2020) · Genes · doi:10.3390/genes11121408 · Cited by 15 · see citing works
A comprehensive survey of genome language models in bioinformatics
Shu, L., Tang, J., Guan, X., & Zhang, D. (2025) · Briefings in Bioinformatics · doi:10.1093/bib/bbaf724 · Cited by 16 · see citing works
“The latest assembly GRCh38 [68], along with its predecessor GRCh37/hg19 [81], provides a 3.2 billion base human genomic backbone covering well-annotated coding and non-coding regions.”
InfluentialPrins, B. P., Leitsalu, L., Pärna, K., Fischer, K., Metspalu, A., Haller, T., & Snieder, H. (2021) · Journal of Personalized Medicine · doi:10.3390/jpm11050358 · Cited by 15 · see citing works
“Multiple private sequence efforts are also underway, one of the most ambitious being the effort of the AstraZeneca to sequence 2 million human genomes [30], complemented by projects that will establish deeper and more accurate reference maps of the human genome [31].”
BackgroundMontemayor, C., Brunker, P. A. R., & Keller, M. (2019) · Current Opinion in Hematology · doi:10.1097/moh.0000000000000536 · Cited by 15 · see citing works
“Only a few published studies in transfusion [4 && ,21 & ] have transitioned to the most recent GRCh38 reference build [32], but this recent release still has discrepancies with the blood group alleles considered historically as references by immunohematologists.”
BackgroundLarge language models transform biological research: from architecture to utilization
Wang, T., & Luo, Z. (2025) · Science China Information Sciences · doi:10.1007/s11432-024-4466-3 · Cited by 14 · see citing works
“Table 1 [28,33,70, 73,78–94] delineates commonly employed datasets for pretraining or fine-tuning LLMs in the domains of genomics and transcriptomics, highlighting the datasets’ attributes and application scenarios.”
Estimating sequencing error rates using families
Paskov, K. M., Jung, J.-Y., Chrisman, B., Stockham, N., Washington, P. Y., Varma, M., Sun, M., & Wall, D. P. (2021) · BioData Mining · doi:10.1186/s13040-021-00259-6 · Cited by 14 · see citing works
“This result supports other work showing that GRCh38 improves read mapping and results in fewer false positive variant calls [18].”
ResultThe Regulatory Mendelian Mutation score for GRCh38
Schubach, M., Nazaretyan, L., & Kircher, M. (2022) · GigaScience · doi:10.1093/gigascience/giad024 · Cited by 13 · see citing works
Challenges in clinical interpretation of next-generation sequencing data: Advantages and Pitfalls
Karakoyun, H. K., Sayar, C., & Yararbaş, K. (2023) · Results in Engineering · doi:10.1016/j.rineng.2023.101421 · Cited by 13 · see citing works
A second look at exome sequencing data: detecting mobile elements insertion in a rare disease cohort
Garret, P., Chevarin, M., Vitobello, A., Verdez, S., Fournier, C., Verloès, A., Tisserant, É., Vabres, P., Prevel, O., Philippe, C., et al. (2022) · European Journal of Human Genetics · doi:10.1038/s41431-022-01250-3 · Cited by 13 · see citing works
Park, K., Yoon, Y. A., & Park, J. (2023) · Genes · doi:10.3390/genes14101875 · Cited by 12 · see citing works
“Conversion Rate and Accuracy The conversion rate of CrossMap, NCBI Remap, and UCSC liftOver was 99.82% (1,567, The conversion rate of CrossMap, NCBI Remap, and UCSC liftOver was 99.82% (1,567,838/1,570,644), 99.70% (1,565,953/1,570,644), and 99.99% (1,570,550/1,570,644), respectively (Figures 1A…”
BackgroundMethodResultInfluentialImpact of genome build on RNA-seq interpretation and diagnostics
Ungar, R. A., Goddard, P. C., Jensen, T. D., Degalez, F., Smith, K. S., Jin, C. A., Undiagnosed Diseases Network, Bonner, D. E., Bernstein, J. A., Wheeler, M. T., et al. (2024) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2024.05.005 · Cited by 12 · see citing works
ERNIE-ac4C: A Novel Deep Learning Model for Effectively Predicting N4-acetylcytidine Sites
Lu, R., Qiao, J., Li, K., Zhao, Y., Jin, J., Cui, F., Zhang, Z., Manavalan, B., & Wei, L. (2025) · Journal of Molecular Biology · doi:10.1016/j.jmb.2025.168978 · Cited by 12 · see citing works
Identifying suitable tools for variant detection and differential gene expression using RNA-seq data
Dharshini, S. A. P., Taguchi, Y., & Gromiha, M. M. (2019) · Genomics · doi:10.1016/j.ygeno.2019.12.011 · Cited by 12 · see citing works
A naturally occurring variant of MBD4 causes maternal germline hypermutation in primatesPreprint
Stendahl, A. M., Sanghvi, R., Peterson, S. M., Ray, K., Lima, A. C., Rahbari, R., & Conrad, D. F. (2023) · Genome Research · doi:10.1101/gr.277977.123 · Cited by 12 · see citing works
“…GRCh38 assembly and subsequent releases; the otherassemblydifferences involve chang-es to heterochromatic DNA (which we do not analyze here), a small amount of new sequence in assembly gaps, and the addition of small, alternate haplotypes at 178 loci, also not considered here (Guo et al. 2017).”
BackgroundAdvancing FDSTools by integrating STRNaming 1.1
Hoogenboom, J., Weiler, N., Busscher, L., Struik, L., Sijen, T., & van der Gaag, K. J. (2022) · Forensic Science International Genetics · doi:10.1016/j.fsigen.2022.102768 · Cited by 11 · see citing works
Moore, C. M., & Seibold, M. A. (2022) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2022.08.016 · Cited by 10 · see citing works
Kang, J., Dai, Y., Li, J., Fan, H., & Zhao, Z. (2023) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2023.01.025 · Cited by 10 · see citing works
“Starting from the raw sequencing reads, all samples were preprocessed, quality-controlled and integrated using the standard CellRanger mapping against the GRCh38 reference genome (Version 1.1.0, 10x Genomics) [29,33], Seurat and Signac pipelines with default settings (SF 1, Step 2) [30].”
InfluentialSelf-citationWhole exome sequencing of FFPE samples—expanding the horizon of forensic molecular autopsies
Adolfsson, E., Kling, D., Gunnarsson, C., Jonasson, J., Gréen, H., & Gréen, A. (2022) · International Journal of Legal Medicine · doi:10.1007/s00414-022-02906-x · Cited by 9 · see citing works
Overcoming challenges associated with broad sharing of human genomic data
LoTempio, J. E., & Moreno, J. D. (2025) · Nature Genetics · doi:10.1038/s41588-024-02049-2 · Cited by 9 · see citing works
“The reference genome, currently in draft 38 (GRCh38), was created largely during the HGP 27 .”
Zhang, Z., Zhang, S., Li, X., Zhao, Z., Chen, C., Zhang, J., Li, M., Wei, Z., Jiang, W., Pan, B., et al. (2020) · Briefings in Bioinformatics · doi:10.1093/bib/bbaa081 · Cited by 9 · see citing works
Expression profiling dataset of competing endogenous RNA in pre-eclampsia
Hu, X., Li, X., Tian, G. G., Zhang, H., Cheng, W., & Wu, J. (2019) · Data in Brief · doi:10.1016/j.dib.2019.104795 · Cited by 9 · see citing works
Xu, H., Zhen, Q., Bai, M., Fang, L., Zhang, Y., Bao, L., Ge, H., Moon, S., Chen, W., Fu, W., et al. (2021) · Genome Research · doi:10.1101/gr.267963.120 · Cited by 9 · see citing works
“ThedifferencesbetweenGRCh38and GRCh37 are most significant for highly repetitive genomic regions (Guo et al. 2017).”
Yi-yun, X., Zhang, Q., Wang, Y., Zhou, R., Ji, X., Meng, L., Luo, C., Liu, A., Jiao, J., Chen, H., et al. (2024) · Diagnostics · doi:10.3390/diagnostics14020165 · Cited by 8 · see citing works
“T2T assembly may bring new opportunities for OGM in the near future.”
BackgroundDeepGene: An Efficient Foundation Model for Genomics Based on Pan-Genome Graph Transformer
Zhang, X., Yang, M., Yin, X., Qian, Y., & Sun, F. (2025) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbbio.2025.3614354 · Cited by 10 · see citing works
“DNABERT utilized the human reference genome GRCh38.p13 [18] for pre-training, adopting k-mer-based sequence tokenization.”
Deficiency of Smooth Muscle Adar1 Exacerbates Vascular Remodeling and Pulmonary Hypertension
Kim, Y., Maroli, G., Woodcock, C.-. C., Kim, H., Liu, Y., Klouda, T., Li, Y., Li, Q., Hao, Y. T., Schumacher, V., et al. (2025) · Circulation Research · doi:10.1161/circresaha.125.326235 · Cited by 8 · see citing works
Mendoza-Álvarez, A., Muñoz‐Barrera, A., Rubio‐Rodríguez, L. A., Marcelino-Rodríguez, I., Corrales, A., Íñigo-Campos, A., Callero, A., Perez-Rodriguez, E., García-Robaina, J. C., González‐Montelongo, R., et al. (2020) · Journal of Medical Internet Research · doi:10.2196/19040 · Cited by 8 · see citing works
“Similarly, HADA uses GRCh37/hg19 coordinates, which is still considered to be the gold standard in clinical settings [42].”
MethodValidation of a comprehensive long-read sequencing platform for broad clinical genetic diagnosis
Sen, S., Handler, H. P., Victorsen, A., Flaten, Z., Ellison, A., Knutson, T. P., Munro, S. A., Martinez, R. J., Billington, C. J., Laffin, J. J. S., et al. (2025) · Frontiers in Genetics · doi:10.3389/fgene.2025.1499456 · Cited by 7 · see citing works
Du, H., Diao, C., Zhao, P., Zhou, L., & Liu, J. (2020) · Briefings in Bioinformatics · doi:10.1093/bib/bbaa399 · Cited by 7 · see citing works
The Isolation and Deep Sequencing of Mitochondrial DNA
Bury, A. G., Robertson, F. M., Pyle, A., Payne, B. A. I., & Hudson, G. (2021) · Methods in molecular biology · doi:10.1007/978-1-0716-1270-5_27 · Cited by 7 · see citing works
Bhattacharjee, K., Sengupta, A., Kumar, R., & Ghosh, A. (2025) · Frontiers in Bioinformatics · doi:10.3389/fbinf.2025.1536783 · Cited by 6 · see citing works
Broche, J., Köhler, A., Kühnel, F., Osteresch, B., Chandrasekaran, T., Adam, S., Brockmeyer, J., & Jeltsch, A. (2023) · Communications Biology · doi:10.1038/s42003-023-04466-1 · Cited by 6 · see citing works
In-depth serum virome analysis in patients with acute liver failure with indeterminate etiology
Ren, Y., Xu, Y., Lee, W. M., Bisceglie, A. M. D., & Fan, X. (2019) · Archives of Virology · doi:10.1007/s00705-019-04466-9 · Cited by 6 · see citing works
Razzaghy‐Azar, M., Nourbakhsh, M., Vafadar, M., Nourbakhsh, M., Talebi, S., Sharifi‐Zarchi, A., Siavashani, E. S., & Garshasbi, M. (2021) · Clinical Biochemistry · doi:10.1016/j.clinbiochem.2021.01.007 · Cited by 6 · see citing works
Zheng, H., Zhao, X., Wang, H., Ding, Y., Lu, X., Zhang, G., Yang, J., Wang, L., Zhang, H., Bai, Y., et al. (2019) · Briefings in Bioinformatics · doi:10.1093/bib/bbz073 · Cited by 6 · see citing works
Starrett, G. J., Baikie, B. C., Stoff, B. K., Grossniklaus, H. E., Buren, I. V., Berry, E., Novoa, R. A., Rieger, K. E., Sarin, K. Y., Lynch, C. F., et al. (2024) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-24-1327 · Cited by 5 · see citing works
A Framework for Bioinformatic Reporting in Prenatal Sequencing: Insights From a Systematic Review
Pritchard, A. J., Lim, K. M. X., Smith, G., Scotchman, E., Gibbs, A., Lombard, P., & Chandler, N. J. (2026) · Prenatal Diagnosis · doi:10.1002/pd.70085 · Cited by 5 · see citing works
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CNV-Finder: streamlining copy number variation discovery
Kuznetsov, N., Daida, K., Makarious, M. B., Al-Mubarak, B. R., Brolin, K. A., Malik, L., Kouam, C., Baker, B., Real, R., Step, K., et al. (2026) · Bioinformatics Advances · doi:10.1093/bioadv/vbag205 · Cited by 5 · see citing works
“All graphical representations and positional references in this paper adhere to the Genome Reference Consortium Human Build 38 (hg38) (Guo et al .”
Yu, H., Zhao, S., Ness, S. A., Kang, H., Sheng, Q., Samuels, D. C., Oyebamiji, O., Zhao, Y., & Guo, Y. P. (2020) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1007968 · Cited by 5 · see citing works
“2% from GRCh37 to GRCh38 [17], the nucleotide volume occupied by MNRs, DNRs, and TNRs consistently increased in absolute number (S1 Table); in total, GRCh37 and GRCh38 harbor 141.”
BackgroundSelf-citationZhang, Q., Ke, W., Ye, J., Zhang, P., Yang, Q., Pan, F., Wang, K., & Zha, B. (2024) · Endocrine · doi:10.1007/s12020-024-03756-w · Cited by 5 · see citing works
“Considering the different versions of the reference genome, if not converted, it might lead to inconsistencies in coordinates or annotations, affecting the accuracy and comparability of the results [31].”
AirLift: A Fast and Comprehensive Technique for Remapping Alignments Between Reference Genomes
Kim, J. S., Fırtına, C., Cavlak, M. B., Cali, D. S., Hajinazar, N., Alser, M., Alkan, C., & Mutlu, O. (2024) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2024.3433378 · Cited by 5 · see citing works
“AirLift is the first tool that provides BAM-to-BAM remapping results of a read data set on which downstream analysis can be immediately performed.”
BackgroundMethodInfluentialOrigin Matters: Using a Local Reference Genome Improves Measures in Population GenomicsPreprint
Thorburn, D. J., Sagonas, Κ., Panchal, M., Chain, F. J. J., Feulner, P. G. D., Bornberg‐Bauer, E., Reusch, T. B. H., Samonte, I. E., Milinski, M., Lenz, T. L., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.01.10.523267 · Cited by 5 · see citing works
Prakash, A., Mahoney, K. E., & Orsburn, B. C. (2021) · Cancers · doi:10.3390/cancers13153754 · Cited by 4 · see citing works
“Human SwissProt; Canonical + isoforms 42,414 UniProt, September, 2019 Human UniProt Trembl 53,211 UniProt, September, 2019 Common contaminants 269 cRAP database [38]) Known somatic variants (missense + nonsense) 2,537,773 February, 2020 (Lazar Lab) [40] Known population variants (dbSNP) 1,042,598 dbSNP, July, 2020 Ann…”
Zhang, T., Dong, J., Jiang, H., Zhao, Z., Zhou, M., & Yuan, T. (2022) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2022.1000638 · Cited by 4 · see citing works
“All simulated data are generated based on chromosome 21 in the reference genome GRCH38/hg38 (Guo et al., 2017).”
MethodChu, C., Liu, D., Duofa, W., Hu, S., & Zhang, Y. (2023) · International Journal of Immunopathology and Pharmacology · doi:10.1177/03946320231211795 · Cited by 4 · see citing works
“All genes were annotated with fi le GRCh38 to distinguish mRNAs and lncRNAs, 19 and all data (lncRNA, mRNA, somatic mutation information, and clinical information) were matched for further analysis.”
MethodWen, B., Wei, S., Huang, D., Zhang, C., Wang, H., Liu, S., & Wu, X. (2025) · Archives of Gerontology and Geriatrics · doi:10.1016/j.archger.2025.105774 · Cited by 4 · see citing works
- Authors
- Guo, Y., Dai, Y., Yu, H., Zhao, S., Samuels, D. C., & Shyr, Y.
- Affiliations
- Vanderbilt University (US)
- Corresponding author
- Guo, Yan
- Shyr, Yu
- Venue
- Genomics
- Publisher
- Elsevier BV
- Published
- 2017-03
- Volume
- 109
- Issue
- 2
- Pages
- 83-90
- ISSN
- 0888-7543 (ISSN-L)
- OpenAlex
- W2580314844
- Cited by
- 172
- References
- 40
- Citations by year
- 2026: 16 · 2025: 26 · 2024: 18 · 2023: 17 · 2022: 17 · 2021: 31 · 2020: 14 · 2019: 27 · 2018: 5
- FWCI
- 5.14
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Genomics (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Cancer Institute (P30CA068485)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomic variations and chromosomal abnormalities
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
- Keywords
- GRCh38, GRCh37, human reference genome, high-throughput sequencing data analysis, sequence alignment, single nucleotide polymorphisms, small insertions and deletions, copy number variation, structural variants
- MeSH terms
- Data Accuracy, Humans, Polymorphism, Genetic, Genomic Library, Genome, Human, Sequence Analysis, DNA, Genomics, High-Throughput Nucleotide Sequencing
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