Cited by 27,219Genomics and Phylogenetic StudiesGene expression and cancer classificationSingle-cell and spatial transcriptomics

The DOI matches its Crossref record; 46 of the 47 references it cites were found in a registry or an index.

featureCounts: an efficient general purpose program for assigning sequence reads to genomic features

Open access

Liao, Yang, Smyth, Gordon K., Shi, Wei·2014·Bioinformatics

DOI 10.1093/bioinformatics/btt656

Open this paper in CoChat — free account Open PDF

Abstract

MOTIVATION: Next-generation sequencing technologies generate millions of short sequence reads, which are usually aligned to a reference genome. In many applications, the key information required for downstream analysis is the number of reads mapping to each genomic feature, for example to each exon or each gene. The process of counting reads is called read summarization. Read summarization is required for a great variety of genomic analyses but has so far received relatively little attention in the literature. RESULTS: We present featureCounts, a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments. featureCounts implements highly efficient chromosome hashing and feature blocking techniques. It is considerably faster than existing methods (by an order of magnitude for gene-level summarization) and requires far less computer memory. It works with either single or paired-end reads and provides a wide range of options appropriate for different sequencing applications. AVAILABILITY AND IMPLEMENTATION: featureCounts is available under GNU General Public License as part of the Subread (http://subread.sourceforge.net) or Rsubread (http://www.bioconductor.org) software packages.

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

Crossref · 10.1093/bioinformatics/btt656

Cites

46 of 46 references verified0 citation errors · 0 not checkable

Statistics

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.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

The Sequence Alignment/Map format and SAMtools
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., & 1000 Genome Project Data Processing Subgroup (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp352 · Cited by 62,041
Fast and accurate short read alignment with Burrows-Wheeler transform
Li, H., & Durbin, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp324 · Cited by 58,607
<tt>edgeR</tt> : a Bioconductor package for differential expression analysis of digital gene expression data
Robinson, M. D., McCarthy, D. J., & Smyth, G. K. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btp616 · Cited by 41,364
Self-citation
BEDTools: a flexible suite of utilities for comparing genomic features
Quinlan, A. R., & Hall, I. M. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq033 · Cited by 27,437
RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome
Li, B., & Dewey, C. N. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-323 · Cited by 22,179
Ultrafast and memory-efficient alignment of short DNA sequences to the human genome.
Langmead, B., Trapnell, C., Pop, M., & Salzberg, S. L. (2009) · Genome Biology · doi:10.1186/gb-2009-10-3-r25 · Cited by 21,849
Model-based Analysis of ChIP-Seq (MACS)
Zhang, Y., Liu, T., Meyer, C. A., Eeckhoute, J., Johnson, D. S., Bernstein, B. E., Nusbaum, C., Myers, R. M., Brown, M., Li, W., et al. (2008) · Genome Biology · doi:10.1186/gb-2008-9-9-r137 · Cited by 18,386
Differential expression analysis for sequence count data
Anders, S., & Huber, W. (2010) · Genome Biology · doi:10.1186/gb-2010-11-10-r106 · Cited by 15,581
Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation
Trapnell, C., Williams, B. A., Pertea, G., Mortazavi, A., Kwan, G., van Baren, M. J., Salzberg, S. L., Wold, B. J., & Pachter, L. (2010) · Nature Biotechnology · doi:10.1038/nbt.1621 · Cited by 15,556
Bioconductor: open software development for computational biology and bioinformatics
Gentleman, R. C., Carey, V. J., Bates, D. M., Bolstad, B., Dettling, M., Dudoit, S., Ellis, B., Gautier, L., Ge, Y., Gentry, J., et al. (2004) · Genome biology · doi:10.1186/gb-2004-5-10-r80 · Cited by 12,082
Self-citation

Flagged first, then by citations

Show all 47 references

1 of the 47 references couldn’t be matched to a known paper.

Sorted by citations

Items 1,001–1,100 of 1,224

The Tudor SND1 protein is an m6A RNA reader essential for replication of Kaposi’s sarcoma-associated herpesvirus
Baquero-Pérez, B., Antanaviciute, A., Yonchev, I. D., Carr, I., Wilson, S. A., & Whitehouse, A. (2019) · eLife · doi:10.7554/elife.47261 · Cited by 136
The Sox2 transcription factor binds RNA
Holmes, Z. E., Hamilton, D. J., Hwang, T., Parsonnet, N. V., Rinn, J. L., Wuttke, D. S., & Batey, R. (2020) · Nature Communications · doi:10.1038/s41467-020-15571-8 · Cited by 136
GAF is essential for zygotic genome activation and chromatin accessibility in the early Drosophila embryo
Gaskill, M. M., Gibson, T. J., Larson, E. D., & Harrison, M. M. (2021) · eLife · doi:10.7554/elife.66668 · Cited by 136
Isoform prefiltering improves performance of count-based methods for analysis of differential transcript usage
Soneson, C., Matthes, K. L., Nowicka, M., Law, C. W., & Robinson, M. D. (2016) · Genome biology · doi:10.1186/s13059-015-0862-3 · Cited by 135
Genetically Defined Syngeneic Mouse Models of Ovarian Cancer as Tools for the Discovery of Combination Immunotherapy
Iyer, S., Zhang, S., Yucel, S., Horn, H., Smith, S. G., Reinhardt, F., Hoefsmit, E., Assatova, B., Casado, J., Meinsohn, M.-C., et al. (2021) · Cancer Discovery · doi:10.1158/2159-8290.cd-20-0818 · Cited by 136
An RNA-Seq atlas of gene expression in mouse and rat normal tissues
Söllner, J. F., Leparc, G., Hildebrandt, T., Klein, H., Thomas, L., Stupka, E., & Simon, E. (2017) · Scientific Data · doi:10.1038/sdata.2017.185 · Cited by 133
Multi-omic rejuvenation and lifespan extension on exposure to youthful circulation
Zhang, B., Lee, D. E., Trapp, A., Tyshkovskiy, A., Lu, A. T., Bareja, A., Kerepesi, C., McKay, L. K., Shindyapina, A. V., Dmitriev, S. E., et al. (2023) · Nature Aging · doi:10.1038/s43587-023-00451-9 · Cited by 134
Neuronal ambient RNA contamination causes misinterpreted and masked cell types in brain single-nuclei datasets
Caglayan, E., Liu, Y., & Konopka, G. (2022) · Neuron · doi:10.1016/j.neuron.2022.09.010 · Cited by 123
FOXA1 mutations reveal distinct chromatin profiles and influence therapeutic response in breast cancer
Arruabarrena-Aristorena, A., Maag, J. L. V., Kittane, S., Cai, Y., Karthaus, W. R., Ladewig, E., Park, J., Kannan, S., Ferrando, L., Cocco, E., et al. (2020) · Cancer Cell · doi:10.1016/j.ccell.2020.08.003 · Cited by 130
TBL1XR1 mutations drive extranodal lymphoma by inducing a pro-tumorigenic memory fate
Venturutti, L., Teater, M., Zhai, A., Chadburn, A., Babiker, L., Kim, D., Béguelin, W., Lee, T. C., Kim, Y., Chin, C. R., et al. (2020) · Cell · doi:10.1016/j.cell.2020.05.049 · Cited by 127
Human ESC-derived chimeric mouse models of Huntington's disease reveal cell-intrinsic defects in glial progenitor cell differentiation
Osipovitch, M., Asenjo Martinez, A., Mariani, J. N., Cornwell, A., Dhaliwal, S., Zou, L., Chandler-Militello, D., Wang, S., Li, X., Benraiss, S.-J., et al. (2019) · Cell Stem Cell · doi:10.1016/j.stem.2018.11.010 · Cited by 120
Skeletal muscle transcriptome in healthy aging
Tumasian, R. A., Harish, A., Kundu, G., Yang, J.-H., Ubaida-Mohien, C., Gonzalez-Freire, M., Kaileh, M., Zukley, L. M., Chia, C. W., Lyashkov, A., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-22168-2 · Cited by 126
A NPAS4–NuA4 complex couples synaptic activity to DNA repair
Pollina, E. A., Gilliam, D. T., Landau, A. T., Lin, C., Pajarillo, N., Davis, C. P., Harmin, D. A., Yap, E.-L., Vogel, I. R., Griffith, E. C., et al. (2023) · Nature · doi:10.1038/s41586-023-05711-7 · Cited by 125
Different effects of constitutive and induced microbiota modulation on microglia in a mouse model of Alzheimer’s disease
Mezö, C., Dokalis, N., Mossad, O., Staszewski, O., Neuber, J., Yilmaz, B., Schnepf, D., de Agüero, M. G., Ganal-Vonarburg, S. C., Macpherson, A. J., et al. (2020) · Acta Neuropathologica Communications · doi:10.1186/s40478-020-00988-5 · Cited by 120
Micro-environmental sensing by bone marrow stroma identifies IL-6 and TGFβ1 as regulators of hematopoietic ageing
Valletta, S., Thomas, A., Meng, Y., Ren, X., Drissen, R., Sengül, H., Di Genua, C., & Nerlov, C. (2020) · Nature Communications · doi:10.1038/s41467-020-17942-7 · Cited by 122
Habenular TCF7L2 links nicotine addiction to diabetes
Duncan, A., Heyer, M. P., Ishikawa, M., Caligiuri, S. P. B., Liu, X.-A., Chen, Z., Micioni Di Bonaventura, M. V., Elayouby, K. S., Ables, J. L., Howe, W. M., et al. (2019) · Nature · doi:10.1038/s41586-019-1653-x · Cited by 119
A mouse tissue atlas of small noncoding RNA
Isakova, A., Fehlmann, T., Keller, A., & Quake, S. R. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2002277117 · Cited by 119
Astrocytes and neurons share region-specific transcriptional signatures that confer regional identity to neuronal reprogramming
Herrero-Navarro, Á., Puche-Aroca, L., Moreno-Juan, V., Sempere-Ferràndez, A., Espinosa, A., Susín, R., Torres-Masjoan, L., Leyva-Díaz, E., Karow, M., Figueres-Oñate, M., et al. (2021) · Science Advances · doi:10.1126/sciadv.abe8978 · Cited by 117
Niche stiffening compromises hair follicle stem cell potential during ageing by reducing bivalent promoter accessibility
Koester, J., Miroshnikova, Y. A., Ghatak, S., Chacón-Martínez, C. A., Morgner, J., Li, X., Atanassov, I., Altmüller, J., Birk, D. E., Koch, M., et al. (2021) · Nature Cell Biology · doi:10.1038/s41556-021-00705-x · Cited by 117
Cross-species analysis of enhancer logic using deep learning
Minnoye, L., Taskiran, I. I., Mauduit, D., Fazio, M., Van Aerschot, L., Hulselmans, G., Christiaens, V., Makhzami, S., Seltenhammer, M., Karras, P., et al. (2020) · Genome Research · doi:10.1101/gr.260844.120 · Cited by 116
A spatial vascular transcriptomic, proteomic, and phosphoproteomic atlas unveils an angiocrine Tie-Wnt signaling axis in the liver
Inverso, D., Shi, J., Lee, K. H., Jakab, M., Ben-Moshe, S., Kulkarni, S. R., Schneider, M., Wang, G., Komeili, M., Vélez, P. A., et al. (2021) · Developmental Cell · doi:10.1016/j.devcel.2021.05.001 · Cited by 114
Arid1b haploinsufficient mice reveal neuropsychiatric phenotypes and reversible causes of growth impairment
Celen, C., Chuang, J.-C., Luo, X., Nijem, N., Walker, A. K., Chen, F., Zhang, S., Chung, A. S., Nguyen, L. H., Nassour, I., et al. (2017) · eLife · doi:10.7554/elife.25730 · Cited by 113
ELOF1 is a transcription-coupled DNA repair factor that directs RNA polymerase II ubiquitylation
van der Weegen, Y., de Lint, K., van den Heuvel, D., Nakazawa, Y., Mevissen, T. E. T., van Schie, J. J. M., San Martin Alonso, M., Boer, D. E. C., González-Prieto, R., Narayanan, I. V., et al. (2021) · Nature Cell Biology · doi:10.1038/s41556-021-00688-9 · Cited by 114
HIF inhibitor 32-134D eradicates murine hepatocellular carcinoma in combination with anti-PD1 therapy
Salman, S., Meyers, D. J., Wicks, E. E., Lee, S. N., Datan, E., Thomas, A. M., Anders, N. M., Hwang, Y., Lyu, Y., Yang, Y., et al. (2022) · Journal of Clinical Investigation · doi:10.1172/jci156774 · Cited by 111
“quantified with featureCounts (94), and differential gene expres-”
Method
A multicenter study benchmarking single-cell RNA sequencing technologies using reference samples
Chen, W., Zhao, Y., Chen, X., Yang, Z., Xu, X., Bi, Y., Chen, V., Li, J., Choi, H., Ernest, B., et al. (2021) · Nature Biotechnology · doi:10.1038/s41587-020-00748-9 · Cited by 114
Genome-Wide CRISPR Screens Identify Multiple Synthetic Lethal Targets That Enhance KRASG12C Inhibitor Efficacy
Mukhopadhyay, S., Huang, H.-Y., Lin, Z., Ranieri, M., Li, S., Sahu, S., Liu, Y., Ban, Y., Guidry, K., Hu, H., et al. (2023) · Cancer Research · doi:10.1158/0008-5472.can-23-2729 · Cited by 105
Absolute Quantification of Transcription Factors Reveals Principles of Gene Regulation in Erythropoiesis
Gillespie, M. A., Palii, C. G., Sanchez-Taltavull, D., Shannon, P., Longabaugh, W. J. R., Downes, D. J., Sivaraman, K., Espinoza, H. M., Hughes, J. R., Price, N. D., et al. (2020) · Molecular Cell · doi:10.1016/j.molcel.2020.03.031 · Cited by 110
Large-scale chromatin reorganization reactivates placenta-specific genes that drive cellular aging
Liu, Z., Ji, Q., Ren, J., Yan, P., Wu, Z., Wang, S., Sun, L., Wang, Z., Li, J., Sun, G., et al. (2022) · Developmental Cell · doi:10.1016/j.devcel.2022.05.004 · Cited by 109
Substantial somatic genomic variation and selection for BCOR mutations in human induced pluripotent stem cells
Rouhani, F. J., Zou, X., Danecek, P., Badja, C., Amarante, T. D., Koh, G., Wu, Q., Memari, Y., Durbin, R., Martincorena, I., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01147-3 · Cited by 105
Extensive remodeling of the extracellular matrix during aging contributes to age-dependent impairments of muscle stem cell functionality
Schüler, S. C., Kirkpatrick, J. M., Schmidt, M., Santinha, D., Koch, P., Di Sanzo, S., Cirri, E., Hemberg, M., Ori, A., & von Maltzahn, J. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.109223 · Cited by 106
An organoid-based screen for epigenetic inhibitors that stimulate antigen presentation and potentiate T-cell-mediated cytotoxicity
Zhou, Z., Van der Jeught, K., Fang, Y., Yu, T., Li, Y., Ao, Z., Liu, S., Zhang, L., Yang, Y., Eyvani, H., et al. (2021) · Nature Biomedical Engineering · doi:10.1038/s41551-021-00805-x · Cited by 107
IFN signaling and neutrophil degranulation transcriptional signatures are induced during SARS-CoV-2 infection
Rosa, B. A., Ahmed, M., Singh, D. K., Choreño-Parra, J. A., Cole, J., Jiménez-Álvarez, L. A., Rodríguez-Reyna, T. S., Singh, B., Gonzalez, O., Carrion, R., et al. (2021) · Communications Biology · doi:10.1038/s42003-021-01829-4 · Cited by 106
Interaction of bacterial genera associated with therapeutic response to immune checkpoint PD-1 blockade in a United States cohort
Newsome, R. C., Gharaibeh, R. Z., Pierce, C. M., da Silva, W. V., Paul, S., Hogue, S. R., Yu, Q., Antonia, S., Conejo-Garcia, J. R., Robinson, L. A., et al. (2022) · Genome Medicine · doi:10.1186/s13073-022-01037-7 · Cited by 104
Epigenomic map of human liver reveals principles of zonated morphogenic and metabolic control
Brosch, M., Kattler, K., Herrmann, A., von Schönfels, W., Nordström, K., Seehofer, D., Damm, G., Becker, T., Zeissig, S., Nehring, S., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-06611-5 · Cited by 98
Transcription Factor PU.1 Promotes Conventional Dendritic Cell Identity and Function via Induction of Transcriptional Regulator DC-SCRIPT
Chopin, M., Lun, A. T., Zhan, Y., Schreuder, J., Coughlan, H., D’Amico, A., Mielke, L. A., Almeida, F. F., Kueh, A. J., Dickins, R. A., et al. (2019) · Immunity · doi:10.1016/j.immuni.2018.11.010 · Cited by 104
Self-citation
Identification of potential blood biomarkers for early diagnosis of Alzheimer’s disease through RNA sequencing analysis
Shigemizu, D., Mori, T., Akiyama, S., Higaki, S., Watanabe, H., Sakurai, T., Niida, S., & Ozaki, K. (2020) · Alzheimer's Research & Therapy · doi:10.1186/s13195-020-00654-x · Cited by 103
Cell-specific proteome analyses of human bone marrow reveal molecular features of age-dependent functional decline
Hennrich, M. L., Romanov, N., Horn, P., Jaeger, S., Eckstein, V., Steeples, V., Ye, F., Ding, X., Poisa-Beiro, L., Lai, M. C., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-06353-4 · Cited by 101
A reanalysis of mouse ENCODE comparative gene expression data
Gilad, Y., & Mizrahi-Man, O. (2015) · F1000Research · doi:10.12688/f1000research.6536.1 · Cited by 100
Hsf1 promotes hematopoietic stem cell fitness and proteostasis in response to ex vivo culture stress and aging
Kruta, M., Sunshine, M. J., Chua, B. A., Fu, Y., Chawla, A., Dillingham, C. H., Hidalgo San Jose, L., De Jong, B., Zhou, F. J., & Signer, R. A. J. (2021) · Cell Stem Cell · doi:10.1016/j.stem.2021.07.009 · Cited by 100
COX2 regulates senescence secretome composition and senescence surveillance through PGE2
Gonçalves, S., Yin, K., Ito, Y., Chan, A., Olan, I., Gough, S., Cassidy, L., Serrao, E., Smith, S., Young, A., et al. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.108860 · Cited by 95
The 10q26 Risk Haplotype of Age-Related Macular Degeneration Aggravates Subretinal Inflammation by Impairing Monocyte Elimination
Beguier, F., Housset, M., Roubeix, C., Augustin, S., Zagar, Y., Nous, C., Mathis, T., Eandi, C., Benchaboune, M., Drame-Maigné, A., et al. (2020) · Immunity · doi:10.1016/j.immuni.2020.07.021 · Cited by 87
Detecting heterogeneity in single-cell RNA-Seq data by non-negative matrix factorization
Zhu, X., Ching, T., Pan, X., Weissman, S. M., & Garmire, L. (2017) · PeerJ · doi:10.7717/peerj.2888 · Cited by 86
Transcriptomics and proteomics reveal a cooperation between interferon and T-helper 17 cells in neuromyelitis optica
Agasing, A. M., Wu, Q., Khatri, B., Borisow, N., Ruprecht, K., Brandt, A. U., Gawde, S., Kumar, G., Quinn, J. L., Ko, R. M., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-16625-7 · Cited by 98
Engineering a haematopoietic stem cell niche by revitalizing mesenchymal stromal cells
Nakahara, F., Borger, D. K., Wei, Q., Pinho, S., Maryanovich, M., Zahalka, A. H., Suzuki, M., Cruz, C. D., Wang, Z., Xu, C., et al. (2019) · Nature Cell Biology · doi:10.1038/s41556-019-0308-3 · Cited by 99
Transcription-associated topoisomerase 2α (TOP2A) activity is a major effector of cytotoxicity induced by G-quadruplex ligands
Bossaert, M., Pipier, A., Riou, J.-F., Noirot, C., Nguyên, L.-T., Serre, R.-F., Bouchez, O., Defrancq, E., Calsou, P., Britton, S., et al. (2021) · eLife · doi:10.7554/elife.65184 · Cited by 97
“Expression levels were computed with featureCount (Liao et al., 2014) using Ensembl annotation.”
Method
Hierarchical and stage-specific regulation of murine cardiomyocyte maturation by serum response factor
Guo, Y., Jardin, B. D., Zhou, P., Sethi, I., Akerberg, B. N., Toepfer, C. N., Ai, Y., Li, Y., Ma, Q., Guatimosim, S., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-06347-2 · Cited by 96
HSV-1-induced disruption of transcription termination resembles a cellular stress response but selectively increases chromatin accessibility downstream of genes
Hennig, T., Michalski, M., Rutkowski, A. J., Djakovic, L., Whisnant, A. W., Friedl, M.-S., Jha, B. A., Baptista, M. A. P., L’Hernault, A., Erhard, F., et al. (2018) · PLOS Pathogens · doi:10.1371/journal.ppat.1006954 · Cited by 95
Analysis of whole genome-transcriptomic organization in brain to identify genes associated with alcoholism
Kapoor, M., Wang, J.-C., Farris, S. P., Liu, Y., McClintick, J., Gupta, I., Meyers, J. L., Bertelsen, S., Chao, M., Nurnberger, J., et al. (2019) · Translational Psychiatry · doi:10.1038/s41398-019-0384-y · Cited by 92
Disruption of SUV39H1 -Mediated H3K9 Methylation Sustains CAR T-cell Function
Jain, N., Zhao, Z., Koche, R. P., Antelope, C., Gozlan, Y., Montalbano, A., Brocks, D., Lopez, M., Dobrin, A., Shi, Y., et al. (2024) · Cancer Discovery · doi:10.1158/2159-8290.cd-22-1319 · Cited by 95
FOXC2 controls adult lymphatic endothelial specialization, function, and gut lymphatic barrier preventing multiorgan failure
González-Loyola, A., Bovay, E., Kim, J., Lozano, T. W., Sabine, A., Renevey, F., Arroz-Madeira, S., Rapin, A., Wypych, T. P., Rota, G., et al. (2021) · Science Advances · doi:10.1126/sciadv.abf4335 · Cited by 94
Histone H3K4me1 and H3K27ac play roles in nucleosome eviction and eRNA transcription, respectively, at enhancers
Kang, Y., Kim, Y. W., Kang, J., & Kim, A. (2021) · The FASEB Journal · doi:10.1096/fj.202100488r · Cited by 93
A transcriptomic atlas of mammalian olfactory mucosae reveals an evolutionary influence on food odor detection in humans
Saraiva, L. R., Riveros-McKay, F., Mezzavilla, M., Abou-Moussa, E. H., Arayata, C. J., Makhlouf, M., Trimmer, C., Ibarra-Soria, X., Khan, M., Van Gerven, L., et al. (2019) · Science Advances · doi:10.1126/sciadv.aax0396 · Cited by 92
Cell culture-based profiling across mammals reveals DNA repair and metabolism as determinants of species longevity
Ma, S., Upneja, A., Galecki, A., Tsai, Y.-M., Burant, C. F., Raskind, S., Zhang, Q., Zhang, Z. D., Seluanov, A., Gorbunova, V., et al. (2016) · eLife · doi:10.7554/elife.19130 · Cited by 89
Arrayed CRISPRi and quantitative imaging describe the morphotypic landscape of essential mycobacterial genes
de Wet, T. J., Winkler, K. R., Mhlanga, M., Mizrahi, V., & Warner, D. F. (2020) · eLife · doi:10.7554/elife.60083 · Cited by 79
Single-cell epigenome analysis reveals age-associated decay of heterochromatin domains in excitatory neurons in the mouse brain
Zhang, Y., Amaral, M. L., Zhu, C., Grieco, S. F., Hou, X., Lin, L., Buchanan, J., Tong, L., Preissl, S., Xu, X., et al. (2022) · Cell Research · doi:10.1038/s41422-022-00719-6 · Cited by 89
Immune correlates of tuberculosis disease and risk translate across species
Ahmed, M., Thirunavukkarasu, S., Rosa, B. A., Thomas, K. A., Das, S., Rangel-Moreno, J., Lu, L., Mehra, S., Mbandi, S. K., Thackray, L. B., et al. (2020) · Science Translational Medicine · doi:10.1126/scitranslmed.aay0233 · Cited by 89
Endothelial sensing of AHR ligands regulates intestinal homeostasis
Wiggins, B. G., Wang, Y.-F., Burke, A., Grunberg, N., Vlachaki Walker, J. M., Dore, M., Chahrour, C., Pennycook, B. R., Sanchez-Garrido, J., Vernia, S., et al. (2023) · Nature · doi:10.1038/s41586-023-06508-4 · Cited by 89
Impact of low dose oral exposure to bisphenol A (BPA) on the neonatal rat hypothalamic and hippocampal transcriptome: a clarity-BPA consortium study
Arambula, S. E., Belcher, S. M., Planchart, A., Turner, S. D., & Patisaul, H. B. (2016) · Endocrinology · doi:10.1210/en.2016-1339 · Cited by 87
Consensus molecular subtype classification of colorectal adenomas
Komor, M. A., Bosch, L. J., Bounova, G., Bolijn, A. S., Delis‐van Diemen, P. M., Rausch, C., Hoogstrate, Y., Stubbs, A. P., de Jong, M., Jenster, G., et al. (2018) · The Journal of Pathology · doi:10.1002/path.5129 · Cited by 86
Trisomy 21–induced dysregulation of microglial homeostasis in Alzheimer’s brains is mediated by USP25
Zheng, Q., Li, G., Wang, S., Zhou, Y., Liu, K., Gao, Y., Zhou, Y., Zheng, L., Zhu, L., Deng, Q., et al. (2021) · Science Advances · doi:10.1126/sciadv.abe1340 · Cited by 85
Activation of endogenous retroviruses during brain development causes an inflammatory response
Jönsson, M. E., Garza, R., Sharma, Y., Petri, R., Södersten, E., Johansson, J. G., Johansson, P. A., Atacho, D. A., Pircs, K., Madsen, S., et al. (2021) · The EMBO Journal · doi:10.15252/embj.2020106423 · Cited by 80
Deciphering the decline of metabolic elasticity in aging and obesity
Zhou, Q., Yu, L., Cook, J. R., Qiang, L., & Sun, L. (2023) · Cell Metabolism · doi:10.1016/j.cmet.2023.08.001 · Cited by 80
Functional multi-organelle units control inflammatory lipid metabolism of macrophages
Zimmermann, J. A., Lucht, K., Stecher, M., Badhan, C., Glaser, K. M., Epple, M. W., Koch, L. R., Deboutte, W., Manke, T., Ebnet, K., et al. (2024) · Nature Cell Biology · doi:10.1038/s41556-024-01457-0 · Cited by 79
Silencing SMOC2 ameliorates kidney fibrosis by inhibiting fibroblast to myofibroblast transformation
Gerarduzzi, C., Kumar, R. K., Trivedi, P., Ajay, A. K., Iyer, A., Boswell, S., Hutchinson, J. N., Waikar, S. S., & Vaidya, V. S. (2017) · JCI Insight · doi:10.1172/jci.insight.90299 · Cited by 79
Heritable Epigenomic Changes to the Maize Methylome Resulting from Tissue Culture
Han, Z., Crisp, P. A., Stelpflug, S., Kaeppler, S. M., Li, Q., & Springer, N. M. (2018) · Genetics · doi:10.1534/genetics.118.300987 · Cited by 78
Autoantigen-specific CD4+ T cells acquire an exhausted phenotype and persist in human antigen-specific autoimmune diseases
Saggau, C., Bacher, P., Esser, D., Rasa, M., Meise, S., Mohr, N., Kohlstedt, N., Hutloff, A., Schacht, S.-S., Dargvainiene, J., et al. (2024) · Immunity · doi:10.1016/j.immuni.2024.08.005 · Cited by 79
Interleukin 4 modulates microglia homeostasis and attenuates the early slowly progressive phase of amyotrophic lateral sclerosis
Rossi, C., Cusimano, M., Zambito, M., Finardi, A., Capotondo, A., Garcia-Manteiga, J. M., Comi, G., Furlan, R., Martino, G., & Muzio, L. (2018) · Cell Death & Disease · doi:10.1038/s41419-018-0288-4 · Cited by 77
DNA damage contributes to neurotoxic inflammation in Aicardi-Goutières syndrome astrocytes
Giordano, A. M. S., Luciani, M., Gatto, F., Abou Alezz, M., Beghè, C., Della Volpe, L., Migliara, A., Valsoni, S., Genua, M., Dzieciatkowska, M., et al. (2022) · Journal of Experimental Medicine · doi:10.1084/jem.20211121 · Cited by 76
Transcription-dependent cohesin repositioning rewires chromatin loops in cellular senescence
Olan, I., Parry, A. J., Schoenfelder, S., Narita, M., Ito, Y., Chan, A. S. L., Slater, G. S. C., Bihary, D., Bando, M., Shirahige, K., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-19878-4 · Cited by 76
An integrated flow cytometry-based platform for isolation and molecular characterization of circulating tumor single cells and clusters
Bhagwat, N., Dulmage, K., Pletcher, C. H., Wang, L., DeMuth, W., Sen, M., Balli, D., Yee, S. S., Sa, S., Tong, F., et al. (2018) · Scientific Reports · doi:10.1038/s41598-018-23217-5 · Cited by 75
Regulation of RNA polymerase II processivity by Spt5 is restricted to a narrow window during elongation
Fitz, J., Neumann, T., & Pavri, R. (2018) · The EMBO Journal · doi:10.15252/embj.201797965 · Cited by 74
Single-nucleus RNA-seq2 reveals functional crosstalk between liver zonation and ploidy
Richter, M. L., Deligiannis, I. K., Yin, K., Danese, A., Lleshi, E., Coupland, P., Vallejos, C. A., Matchett, K. P., Henderson, N. C., Colome-Tatche, M., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-24543-5 · Cited by 75
iPSC Modeling of RBM20-Deficient DCM Identifies Upregulation of RBM20 as a Therapeutic Strategy
Briganti, F., Sun, H., Wei, W., Wu, J., Zhu, C., Liss, M., Karakikes, I., Rego, S., Cipriano, A., Snyder, M., et al. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.108117 · Cited by 68
Combinatorial Expression of Grp and Neurod6 Defines Dopamine Neuron Populations with Distinct Projection Patterns and Disease Vulnerability
Kramer, D. J., Risso, D., Kosillo, P., Ngai, J., & Bateup, H. S. (2018) · eNeuro · doi:10.1523/eneuro.0152-18.2018 · Cited by 70
Discovery and characterization of variance QTLs in human induced pluripotent stem cells
Sarkar, A. K., Tung, P.-Y., Blischak, J. D., Burnett, J. E., Li, Y. I., Stephens, M., & Gilad, Y. (2019) · PLOS Genetics · doi:10.1371/journal.pgen.1008045 · Cited by 72
Positive selection of somatically mutated clones identifies adaptive pathways in metabolic liver disease
Wang, Z., Zhu, S., Jia, Y., Wang, Y., Kubota, N., Fujiwara, N., Gordillo, R., Lewis, C., Zhu, M., Sharma, T., et al. (2023) · Cell · doi:10.1016/j.cell.2023.03.014 · Cited by 72
Bacterially produced metabolites protect C. elegans neurons from degeneration
Urrutia, A., García-Angulo, V. A., Fuentes, A., Caneo, M., Legüe, M., Urquiza, S., Delgado, S. E., Ugalde, J., Burdisso, P., & Calixto, A. (2020) · PLOS Biology · doi:10.1371/journal.pbio.3000638 · Cited by 71
A systematically biosynthetic investigation of lactic acid bacteria reveals diverse antagonistic bacteriocins that potentially shape the human microbiome
Zhang, D., Zhang, J., Kalimuthu, S., Liu, J., Song, Z.-M., He, B.-B., Cai, P., Zhong, Z., Feng, C., Neelakantan, P., et al. (2023) · Microbiome · doi:10.1186/s40168-023-01540-y · Cited by 72
“0.3 [67] (with parameters of “-”
Influential
Increased autophagy in EphrinB2-deficient osteocytes is associated with elevated secondary mineralization and brittle bone
Vrahnas, C., Blank, M., Dite, T. A., Tatarczuch, L., Ansari, N., Crimeen-Irwin, B., Nguyen, H., Forwood, M. R., Hu, Y., Ikegame, M., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-11373-9 · Cited by 70
Self-citation
Microglia from offspring of dams with allergic asthma exhibit epigenomic alterations in genes dysregulated in autism
Vogel Ciernia, A., Careaga, M., LaSalle, J. M., & Ashwood, P. (2018) · Glia · doi:10.1002/glia.23261 · Cited by 69
Diversified transcriptional responses of myeloid and glial cells in spinal cord injury shaped by HDAC3 activity
Wahane, S., Zhou, X., Zhou, X., Guo, L., Friedl, M.-S., Kluge, M., Ramakrishnan, A., Shen, L., Friedel, C. C., Zhang, B., et al. (2021) · Science Advances · doi:10.1126/sciadv.abd8811 · Cited by 67
Deconstructing Stepwise Fate Conversion of Human Fibroblasts to Neurons by MicroRNAs
Cates, K., McCoy, M. J., Kwon, J.-S., Liu, Y., Abernathy, D. G., Zhang, B., Liu, S., Gontarz, P., Kim, W. K., Chen, S., et al. (2021) · Cell Stem Cell · doi:10.1016/j.stem.2020.08.015 · Cited by 67
Postmortem Cortical Transcriptomics of Lewy Body Dementia Reveal Mitochondrial Dysfunction and Lack of Neuroinflammation
Rajkumar, A. P., Bidkhori, G., Shoaie, S., Clarke, E., Morrin, H., Hye, A., Williams, G., Ballard, C., Francis, P., & Aarsland, D. (2020) · The American Journal of Geriatric Psychiatry · doi:10.1016/j.jagp.2019.06.007 · Cited by 65
Male autism spectrum disorder is linked to brain aromatase disruption by prenatal BPA in multimodal investigations and 10HDA ameliorates the related mouse phenotype
Symeonides, C., Vacy, K., Thomson, S., Tanner, S., Chua, H. K., Dixit, S., Mansell, T., O’Hely, M., Novakovic, B., Herbstman, J. B., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-48897-8 · Cited by 66
Foxp3+ Regulatory T Cells Inhibit CCl4-Induced Liver Inflammation and Fibrosis by Regulating Tissue Cellular Immunity
Ikeno, Y., Ohara, D., Takeuchi, Y., Watanabe, H., Kondoh, G., Taura, K., Uemoto, S., & Hirota, K. (2020) · Frontiers in Immunology · doi:10.3389/fimmu.2020.584048 · Cited by 62
Multi-omics analysis reveals contextual tumor suppressive and oncogenic gene modules within the acute hypoxic response
Andrysik, Z., Bender, H., Galbraith, M. D., & Espinosa, J. M. (2021) · Nature Communications · doi:10.1038/s41467-021-21687-2 · Cited by 63
Profiling DNA break sites and transcriptional changes in response to contextual fear learning
Stott, R. T., Kritsky, O., & Tsai, L.-H. (2021) · PLOS ONE · doi:10.1371/journal.pone.0249691 · Cited by 62
Transcription of the NKG2D ligand MICA is suppressed by the IRE1/XBP1 pathway of the unfolded protein response through the regulation of E2F1
Obiedat, A., Seidel, E., Mahameed, M., Bernani, O., Tsukerman, P., Voutetakis, K., Chatziioannou, A., Mcmahon, M., Avril, T., Chevet, E., et al. (2019) · The FASEB Journal · doi:10.1096/fj.201801350rr · Cited by 51
An integrated multi-omics analysis reveals osteokines involved in global regulation
Liang, W., Wei, T., Hu, L., Chen, M., Tong, L., Zhou, W., Duan, X., Zhao, X., Zhou, W., Jiang, Q., et al. (2024) · Cell Metabolism · doi:10.1016/j.cmet.2024.03.006 · Cited by 67
Cellular stress signaling activates type-I IFN response through FOXO3-regulated lamin posttranslational modification
Hwang, I., Uchida, H., Dai, Z., Li, F., Sanchez, T., Locasale, J. W., Cantley, L. C., Zheng, H., & Paik, J. (2021) · Nature Communications · doi:10.1038/s41467-020-20839-0 · Cited by 61
Co-targeting SOS1 enhances the antitumor effects of KRASG12C inhibitors by addressing intrinsic and acquired resistance
Thatikonda, V., Lyu, H., Jurado, S., Kostyrko, K., Bristow, C. A., Albrecht, C., Alpar, D., Arnhof, H., Bergner, O., Bosch, K., et al. (2024) · Nature Cancer · doi:10.1038/s43018-024-00800-6 · Cited by 76
ApoC-III ASO promotes tissue LPL activity in the absence of apoE-mediated TRL clearance
Ramms, B., Patel, S., Nora, C., Pessentheiner, A. R., Chang, M. W., Green, C. R., Golden, G. J., Secrest, P., Krauss, R. M., Metallo, C. M., et al. (2019) · Journal of Lipid Research · doi:10.1194/jlr.m093740 · Cited by 59
The 22q11.2 region regulates presynaptic gene-products linked to schizophrenia
Nehme, R., Pietiläinen, O., Artomov, M., Tegtmeyer, M., Valakh, V., Lehtonen, L., Bell, C., Singh, T., Trehan, A., Sherwood, J., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-31436-8 · Cited by 58
A microfluidic cancer-on-chip platform predicts drug response using organotypic tumor slice culture
Chakrabarty, S., Quiros-Solano, W. F., Kuijten, M. M. P., Haspels, B., Mallya, S., Lo, C. S. Y., Othman, A., Silvestri, C., van de Stolpe, A., Gaio, N., et al. (2022) · Cancer Research · doi:10.1158/0008-5472.can-21-0799 · Cited by 61
Altered network properties in C9ORF72 repeat expansion cortical neurons are due to synaptic dysfunction
Perkins, E. M., Burr, K., Banerjee, P., Mehta, A. R., Dando, O., Selvaraj, B. T., Suminaite, D., Nanda, J., Henstridge, C. M., Gillingwater, T. H., et al. (2021) · Molecular Neurodegeneration · doi:10.1186/s13024-021-00433-8 · Cited by 54
Potent Synergistic Interactions between Lopinavir and Azole Antifungal Drugs against Emerging Multidrug-Resistant Candida auris
Eldesouky, H. E., Salama, E. A., Lanman, N. A., Hazbun, T. R., & Seleem, M. N. (2020) · Antimicrobial Agents and Chemotherapy · doi:10.1128/aac.00684-20 · Cited by 56
Resident macrophages restrain pathological adipose tissue remodeling and protect vascular integrity in obese mice
Chen, Q., Lai, S. M., Xu, S., Tan, Y., Leong, K., Liu, D., Tan, J. C., Naik, R. R., Barron, A. M., Adav, S. S., et al. (2021) · The EMBO Reports · doi:10.15252/embr.202152835 · Cited by 56
Myocardial Milieu Favors Local Differentiation of Regulatory T Cells
Delgobo, M., Weiß, E., Ashour, D., Richter, L., Popiolkowski, L., Arampatzi, P., Stangl, V., Arias-Loza, P., Mariotti-Ferrandiz, E., Rainer, P. P., et al. (2023) · Circulation Research · doi:10.1161/circresaha.122.322183 · Cited by 57
Atypical plant homeodomain of UBR7 functions as an H2BK120Ub ligase and breast tumor suppressor
Adhikary, S., Chakravarti, D., Terranova, C., Sengupta, I., Maitituoheti, M., Dasgupta, A., Srivastava, D. K., Ma, J., Raman, A. T., Tarco, E., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-08986-5 · Cited by 57
Aducanumab anti-amyloid immunotherapy induces sustained microglial and immune alterations
Cadiz, M. P., Gibson, K. A., Todd, K. T., Nascari, D. G., Massa, N., Lilley, M. T., Olney, K. C., Al-Amin, M. M., Jiang, H., Holtzman, D. M., et al. (2024) · Journal of Experimental Medicine · doi:10.1084/jem.20231363 · Cited by 55

Authors: Liao, Y., Smyth, G. K., & Shi, W.
Affiliations: The University of Melbourne (AU)
Corresponding author: Shi, Wei
ORCID: Liao, Yang
Smyth, Gordon K.
Shi, Wei
Venue: Bioinformatics
Publisher: Oxford University Press (OUP)
Published: 2013-11-13
Volume: 30
Issue: 7
Pages: 923-930
ISSN: 1367-4803 (ISSN-L)
1367-4811
DOI: 10.1093/bioinformatics/btt656
OpenAlex: W2138207763
Cited by: 27,219
References: 47
Citations by year: 2026: 3661 · 2025: 4344 · 2024: 4323 · 2023: 3554 · 2022: 3316 · 2021: 2761 · 2020: 2083 · 2019: 1326 · 2018: 894 · 2017: 561 · 2016: 250 · 2015: 99 · 2014: 31 · 2013: 6
FWCI: 58.18
Type: journal article
Language: en
Open access: bronze
doi.org
Locations: Bioinformatics (publishedVersion)
PubMed (publishedVersion)
arXiv (Cornell University) (submittedVersion)
arXiv (Cornell University)
Funders: Australian Government
Medical Research Council
National Health and Medical Research Council (1023454)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
Keywords: featureCounts, read counting, genomic features, paired-end reads, RNA-seq
MeSH terms: Algorithms, Histones, Software, Genome, Sequence Analysis, RNA, Genomics, High-Throughput Nucleotide Sequencing

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

featureCounts: an efficient general purpose program for assigning sequence reads to genomic features

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Self-check

Citations

Cites

Cited by

Related

Metadata

Record

About these checks