A comprehensive evaluation of normalization methods for Illumina high-throughput RNA sequencing data analysis
During the last 3 years, a number of approaches for the normalization of RNA sequencing data have emerged in the literature, differing both in the type of bias adjustment and in the statistical strategy adopted. However, as data continue to accumulate, there has been no clear consensus on the approp...
Saved in:
| Published in | Briefings in bioinformatics Vol. 14; no. 6; pp. 671 - 683 |
|---|---|
| Main Authors | , , , , , , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
England
Oxford Publishing Limited (England)
01.11.2013
Oxford University Press (OUP) |
| Subjects | |
| Online Access | Get full text |
Cover
Loading…
| Abstract | During the last 3 years, a number of approaches for the normalization of RNA sequencing data have emerged in the literature, differing both in the type of bias adjustment and in the statistical strategy adopted. However, as data continue to accumulate, there has been no clear consensus on the appropriate normalization method to be used or the impact of a chosen method on the downstream analysis. In this work, we focus on a comprehensive comparison of seven recently proposed normalization methods for the differential analysis of RNA-seq data, with an emphasis on the use of varied real and simulated datasets involving different species and experimental designs to represent data characteristics commonly observed in practice. Based on this comparison study, we propose practical recommendations on the appropriate normalization method to be used and its impact on the differential analysis of RNA-seq data. |
|---|---|
| AbstractList | During the last 3 years, a number of approaches for the normalization of RNA sequencing data have emerged in the literature, differing both in the type of bias adjustment and in the statistical strategy adopted. However, as data continue to accumulate, there has been no clear consensus on the appropriate normalization method to be used or the impact of a chosen method on the downstream analysis. In this work, we focus on a comprehensive comparison of seven recently proposed normalization methods for the differential analysis of RNA-seq data, with an emphasis on the use of varied real and simulated datasets involving different species and experimental designs to represent data characteristics commonly observed in practice. Based on this comparison study, we propose practical recommendations on the appropriate normalization method to be used and its impact on the differential analysis of RNA-seq data.During the last 3 years, a number of approaches for the normalization of RNA sequencing data have emerged in the literature, differing both in the type of bias adjustment and in the statistical strategy adopted. However, as data continue to accumulate, there has been no clear consensus on the appropriate normalization method to be used or the impact of a chosen method on the downstream analysis. In this work, we focus on a comprehensive comparison of seven recently proposed normalization methods for the differential analysis of RNA-seq data, with an emphasis on the use of varied real and simulated datasets involving different species and experimental designs to represent data characteristics commonly observed in practice. Based on this comparison study, we propose practical recommendations on the appropriate normalization method to be used and its impact on the differential analysis of RNA-seq data. During the last 3 years, a number of approaches for the normalization of RNA sequencing data have emerged in the literature, differing both in the type of bias adjustment and in the statistical strategy adopted. However, as data continue to accumulate, there has been no clear consensus on the appropriate normalization method to be used or the impact of a chosen method on the downstream analysis. In this work, we focus on a comprehensive comparison of seven recently proposed normalization methods for the differential analysis of RNA-seq data, with an emphasis on the use of varied real and simulated datasets involving different species and experimental designs to represent data characteristics commonly observed in practice. Based on this comparison study, we propose practical recommendations on the appropriate normalization method to be used and its impact on the differential analysis of RNA-seq data. During the last 3 years, a number of approaches for the normalization of RNA sequencing data have emerged in the literature, differing both in the type of bias adjustment and in the statistical strategy adopted. However, as data continue to accumulate, there has been no clear consensus on the appropriate normalization method to be used or the impact of a chosen method on the downstream analysis. In this work, we focus on a comprehensive comparison of seven recently proposed normalization methods for the differential analysis of RNA-seq data, with an emphasis on the use of varied real and simulated datasets involving different species and experimental designs to represent data characteristics commonly observed in practice. Based on this comparison study, we propose practical recommendations on the appropriate normalization method to be used and its impact on the differential analysis of RNA-seq data. [PUBLICATION ABSTRACT] |
| Author | Le Crom, S. Castel, D. Aubert, J. Jaffrezic, F. Dillies, M.-A. Hennequet-Antier, C. Servant, N. Rau, A. Jouneau, L. Le Gall, C. Marot, G. Keime, C. Estelle, J. Jagla, B. Jeanmougin, M. Laloe, D. Guedj, M. Schaeffer, B. Guernec, G. |
| Author_xml | – sequence: 1 givenname: M.-A. surname: Dillies fullname: Dillies, M.-A. – sequence: 2 givenname: A. surname: Rau fullname: Rau, A. – sequence: 3 givenname: J. surname: Aubert fullname: Aubert, J. – sequence: 4 givenname: C. surname: Hennequet-Antier fullname: Hennequet-Antier, C. – sequence: 5 givenname: M. surname: Jeanmougin fullname: Jeanmougin, M. – sequence: 6 givenname: N. surname: Servant fullname: Servant, N. – sequence: 7 givenname: C. surname: Keime fullname: Keime, C. – sequence: 8 givenname: G. surname: Marot fullname: Marot, G. – sequence: 9 givenname: D. surname: Castel fullname: Castel, D. – sequence: 10 givenname: J. surname: Estelle fullname: Estelle, J. – sequence: 11 givenname: G. surname: Guernec fullname: Guernec, G. – sequence: 12 givenname: B. surname: Jagla fullname: Jagla, B. – sequence: 13 givenname: L. surname: Jouneau fullname: Jouneau, L. – sequence: 14 givenname: D. surname: Laloe fullname: Laloe, D. – sequence: 15 givenname: C. surname: Le Gall fullname: Le Gall, C. – sequence: 16 givenname: B. surname: Schaeffer fullname: Schaeffer, B. – sequence: 17 givenname: S. surname: Le Crom fullname: Le Crom, S. – sequence: 18 givenname: M. surname: Guedj fullname: Guedj, M. – sequence: 19 givenname: F. surname: Jaffrezic fullname: Jaffrezic, F. |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/22988256$$D View this record in MEDLINE/PubMed https://inria.hal.science/hal-00782486$$DView record in HAL |
| BookMark | eNqN0U1r3DAQBmBRUpqvXvoDiqCXtuBGkvXl4xLSJrC0UNKzGWultYIsbSV7If318cZpDqGHniSGZ4Zh3lN0FFO0CL2j5AslTX3R-e6i6wrh8hU6oVypihPBjw5_qSrBZX2MTku5I4QRpekbdMxYozUT8gQNK2zSsMu2t7H4vcV2D2GC0aeIk8Mx5QGC_7MUBjv2aVOwSxnfhDANPgLu_bavxj6nadvvphH__L7Cxf6ebDQ-bvEGRsAQIdwXX87Raweh2LdP7xn69fXq9vK6Wv_4dnO5WleGaz5W1GnpFBdNp5QwpBGaytp1VirFLHEcwNXANbFE2E7UVAPIjmkHnBqjjK7P0Kdlbg-h3WU_QL5vE_j2erVuDzUyH4JxLfd0th8Xu8tp3rqM7eCLsSFAtGkqLeUNk5QKqf-DCkJ1zerD1A8v6F2a8nyGR9Uwqhkjs3r_pKZusJvnVf_mM4PPCzA5lZKteyaUtIfw2zn8dgl_xuQFNn58TG7M4MO_Wh4Am3-yVg |
| CitedBy_id | crossref_primary_10_3390_life10090185 crossref_primary_10_7717_peerj_3859 crossref_primary_10_1093_bioinformatics_btu003 crossref_primary_10_1016_j_biotechadv_2016_03_001 crossref_primary_10_1071_ZO18005 crossref_primary_10_1080_15384101_2022_2123187 crossref_primary_10_1007_s11738_020_3013_8 crossref_primary_10_1097_TP_0000000000003992 crossref_primary_10_1093_nar_gky129 crossref_primary_10_1371_journal_pone_0294308 crossref_primary_10_1016_j_gdata_2015_05_022 crossref_primary_10_3389_fcimb_2017_00076 crossref_primary_10_1126_sciadv_ade3399 crossref_primary_10_3233_BLC_170144 crossref_primary_10_1186_s12864_016_2584_7 crossref_primary_10_1186_s12864_016_3022_6 crossref_primary_10_1167_iovs_19_26767 crossref_primary_10_1093_bib_bbaa156 crossref_primary_10_1016_j_csbj_2015_08_004 crossref_primary_10_1186_s12859_016_1195_2 crossref_primary_10_1186_s13059_014_0527_7 crossref_primary_10_4137_CIN_S21631 crossref_primary_10_1007_s12275_016_6233_2 crossref_primary_10_1186_s13059_016_0927_y crossref_primary_10_1093_chemse_bjw003 crossref_primary_10_3389_fgene_2022_838679 crossref_primary_10_3389_fmicb_2016_00794 crossref_primary_10_1186_s12864_025_11357_8 crossref_primary_10_1186_s12863_021_01015_9 crossref_primary_10_1186_s12864_024_10714_3 crossref_primary_10_3390_microorganisms13010051 crossref_primary_10_3389_fcell_2020_602493 crossref_primary_10_4049_jimmunol_2000908 crossref_primary_10_1096_fj_202402497R crossref_primary_10_3390_v8040111 crossref_primary_10_1186_s12920_023_01601_z crossref_primary_10_1093_bioinformatics_btx768 crossref_primary_10_1038_s41396_018_0230_x crossref_primary_10_1111_mec_13945 crossref_primary_10_1371_journal_pone_0191452 crossref_primary_10_1093_bioinformatics_btaa1063 crossref_primary_10_3389_fendo_2023_1021640 crossref_primary_10_1261_rna_053959_115 crossref_primary_10_1093_bib_bbab257 crossref_primary_10_1186_s12575_018_0067_8 crossref_primary_10_1007_s12561_016_9182_8 crossref_primary_10_21508_1027_4065_2022_67_4_5_13 crossref_primary_10_1186_s12859_018_2382_0 crossref_primary_10_1016_j_mam_2019_10_002 crossref_primary_10_1093_bioinformatics_btv377 crossref_primary_10_1186_s13059_015_0604_6 crossref_primary_10_1080_19490976_2023_2244139 crossref_primary_10_1534_g3_116_027995 crossref_primary_10_1038_srep18399 crossref_primary_10_3389_fgene_2024_1417533 crossref_primary_10_1016_j_mineng_2022_107660 crossref_primary_10_1111_gtc_12372 crossref_primary_10_1186_s12864_018_4488_1 crossref_primary_10_3389_fbioe_2019_00358 crossref_primary_10_1093_nar_gku1273 crossref_primary_10_1038_s41598_018_24865_3 crossref_primary_10_1093_bioinformatics_btv124 crossref_primary_10_1161_CIRCRESAHA_121_319300 crossref_primary_10_1186_s12864_016_2442_7 crossref_primary_10_1016_j_compbiomed_2018_10_021 crossref_primary_10_1038_srep33398 crossref_primary_10_1093_bib_bbaa351 crossref_primary_10_3390_horticulturae9080896 crossref_primary_10_1093_nar_gku1042 crossref_primary_10_4014_jmb_2007_07036 crossref_primary_10_1038_s41598_023_41443_4 crossref_primary_10_3390_ijerph18157939 crossref_primary_10_1038_s41596_019_0264_1 crossref_primary_10_1093_molbev_msad078 crossref_primary_10_1016_j_trac_2015_09_011 crossref_primary_10_1016_j_freeradbiomed_2015_07_007 crossref_primary_10_1038_s41598_023_29224_5 crossref_primary_10_1094_PHYTO_01_19_0024_R crossref_primary_10_1038_s41598_022_10662_6 crossref_primary_10_1093_gbe_evy265 crossref_primary_10_1186_s12864_024_10364_5 crossref_primary_10_1016_j_cca_2023_117683 crossref_primary_10_1182_blood_2014_04_512756 crossref_primary_10_1038_s41467_018_03766_z crossref_primary_10_1016_j_mam_2024_101269 crossref_primary_10_1186_s13068_015_0407_8 crossref_primary_10_1093_bioinformatics_btw475 crossref_primary_10_1126_science_1253435 crossref_primary_10_1016_j_artmed_2023_102589 crossref_primary_10_1016_j_fsi_2022_03_024 crossref_primary_10_1186_s12859_019_2879_1 crossref_primary_10_1186_s12864_018_4941_1 crossref_primary_10_3389_fmicb_2024_1447485 crossref_primary_10_1016_j_micres_2022_127240 crossref_primary_10_1038_s42003_024_06325_z crossref_primary_10_1186_s12870_014_0335_y crossref_primary_10_1016_j_bbagen_2016_04_008 crossref_primary_10_1155_2022_5600190 crossref_primary_10_1111_mec_17265 crossref_primary_10_1186_s13040_017_0150_8 crossref_primary_10_1177_0962280218764187 crossref_primary_10_1016_j_neuroscience_2024_07_002 crossref_primary_10_1093_bioinformatics_btab327 crossref_primary_10_3390_app12125895 crossref_primary_10_1136_jitc_2021_004440 crossref_primary_10_3233_JAD_220120 crossref_primary_10_1038_nmeth_3208 crossref_primary_10_1111_1755_0998_13128 crossref_primary_10_1186_s12859_024_05870_y crossref_primary_10_1186_1471_2105_15_293 crossref_primary_10_1016_j_tig_2013_05_010 crossref_primary_10_1093_bib_bbaa314 crossref_primary_10_18632_aging_205429 crossref_primary_10_1371_journal_pntd_0005398 crossref_primary_10_3389_fcimb_2022_904606 crossref_primary_10_1093_bioinformatics_btv165 crossref_primary_10_1016_j_neuron_2016_09_026 crossref_primary_10_1007_s00436_021_07251_3 crossref_primary_10_3389_fgene_2016_00164 crossref_primary_10_3390_ijms18081652 crossref_primary_10_1186_s13059_018_1466_5 crossref_primary_10_3389_fpls_2022_815443 crossref_primary_10_1186_s12915_019_0643_7 crossref_primary_10_1038_srep42460 crossref_primary_10_1101_gr_217984_116 crossref_primary_10_1002_evl3_22 crossref_primary_10_1186_s12859_020_03666_4 crossref_primary_10_1016_j_autrev_2023_103314 crossref_primary_10_3390_ijms222111334 crossref_primary_10_1038_s41598_017_03083_3 crossref_primary_10_52547_jsdp_18_2_97 crossref_primary_10_1155_2014_969768 crossref_primary_10_1371_journal_pone_0072918 crossref_primary_10_1080_01621459_2017_1328358 crossref_primary_10_1007_s11103_017_0627_3 crossref_primary_10_3390_ijms23094875 crossref_primary_10_1016_j_dci_2018_02_018 crossref_primary_10_1038_s41598_017_02404_w crossref_primary_10_1039_C9MO00174C crossref_primary_10_3389_fpls_2018_00108 crossref_primary_10_1016_j_csbj_2024_11_003 crossref_primary_10_1186_s12864_021_07742_8 crossref_primary_10_1016_j_envexpbot_2021_104555 crossref_primary_10_3389_fmicb_2017_00553 crossref_primary_10_2139_ssrn_3071522 crossref_primary_10_1002_lno_11370 crossref_primary_10_1093_nargab_lqab087 crossref_primary_10_1038_s41522_020_00160_w crossref_primary_10_3389_fpls_2017_00468 crossref_primary_10_1038_nrg3788 crossref_primary_10_1093_gbe_evu254 crossref_primary_10_1371_journal_pone_0192391 crossref_primary_10_3389_fgene_2020_00594 crossref_primary_10_1111_jfb_13798 crossref_primary_10_1073_pnas_1700231114 crossref_primary_10_1186_s12864_017_3819_y crossref_primary_10_1111_mec_12680 crossref_primary_10_1093_nar_gkv736 crossref_primary_10_1371_journal_pone_0084920 crossref_primary_10_1016_j_chemosphere_2020_127156 crossref_primary_10_1016_j_celrep_2016_08_060 crossref_primary_10_1371_journal_pone_0197840 crossref_primary_10_15252_msb_202110240 crossref_primary_10_1016_j_tig_2016_02_002 crossref_primary_10_1109_TCBB_2017_2665495 crossref_primary_10_1111_nph_14835 crossref_primary_10_1007_s00299_018_2255_z crossref_primary_10_1111_mec_13520 crossref_primary_10_1038_s41467_020_17445_5 crossref_primary_10_1371_journal_pone_0114159 crossref_primary_10_1186_s12859_024_05717_6 crossref_primary_10_1098_rsta_2015_0069 crossref_primary_10_1371_journal_pone_0089158 crossref_primary_10_1186_s40748_021_00131_9 crossref_primary_10_1021_pr401249b crossref_primary_10_3389_fpls_2015_01246 crossref_primary_10_3390_biology13070482 crossref_primary_10_1016_j_cmet_2018_10_007 crossref_primary_10_1186_s12859_017_1498_y crossref_primary_10_1186_s12862_016_0767_0 crossref_primary_10_1093_nar_gkv711 crossref_primary_10_1002_btpr_2137 crossref_primary_10_1186_s13059_021_02568_9 crossref_primary_10_1093_biostatistics_kxx028 crossref_primary_10_1186_s13007_020_00611_7 crossref_primary_10_1007_s10142_018_0636_6 crossref_primary_10_1371_journal_pcbi_1011447 crossref_primary_10_1186_s12903_024_05201_w crossref_primary_10_1016_j_celrep_2020_108506 crossref_primary_10_1002_wics_1586 crossref_primary_10_1038_s41598_022_24237_y crossref_primary_10_1093_nar_gkad429 crossref_primary_10_3389_fphys_2022_937899 crossref_primary_10_3389_fpls_2024_1309762 crossref_primary_10_1016_j_jhazmat_2020_122661 crossref_primary_10_3389_fimmu_2017_00118 crossref_primary_10_1097_MEG_0000000000002349 crossref_primary_10_1101_gr_278822_123 crossref_primary_10_1371_journal_pcbi_1010342 crossref_primary_10_3390_w15010063 crossref_primary_10_5691_jjb_36_63 crossref_primary_10_1111_ahg_12441 crossref_primary_10_1186_s12859_020_03866_y crossref_primary_10_3390_biology11071019 crossref_primary_10_1186_s12864_021_07775_z crossref_primary_10_3389_fgene_2023_1143382 crossref_primary_10_3390_f15091621 crossref_primary_10_3390_ani9010004 crossref_primary_10_1186_s12859_015_0847_y crossref_primary_10_1093_bioinformatics_btx073 crossref_primary_10_3390_biom11101445 crossref_primary_10_1186_s12864_020_6502_7 crossref_primary_10_1186_s12864_016_2546_0 crossref_primary_10_1049_iet_syb_2015_0026 crossref_primary_10_1016_j_parint_2016_10_011 crossref_primary_10_1093_ismejo_wrae234 crossref_primary_10_1016_j_gene_2022_146435 crossref_primary_10_1016_j_ibmb_2016_07_002 crossref_primary_10_3390_ijms23052611 crossref_primary_10_1016_j_envexpbot_2019_03_026 crossref_primary_10_1016_j_intimp_2020_106882 crossref_primary_10_1080_10412905_2025_2470788 crossref_primary_10_1016_j_canlet_2024_216919 crossref_primary_10_1186_s12864_017_3809_0 crossref_primary_10_1186_s12864_019_5753_7 crossref_primary_10_1002_0471142905_hg1113s83 crossref_primary_10_1016_j_gene_2016_08_027 crossref_primary_10_1016_j_jhazmat_2024_133688 crossref_primary_10_1038_s41598_019_42173_2 crossref_primary_10_3389_fgene_2021_823431 crossref_primary_10_1016_j_mocell_2024_100139 crossref_primary_10_3389_fimmu_2022_1039956 crossref_primary_10_1186_s12864_022_08992_w crossref_primary_10_1002_wcms_1658 crossref_primary_10_14336_AD_2024_0125_1 crossref_primary_10_1016_j_taap_2015_02_013 crossref_primary_10_1016_j_cbd_2016_06_002 crossref_primary_10_3390_cells11223527 crossref_primary_10_1093_bib_bbx104 crossref_primary_10_3390_stats7030059 crossref_primary_10_1186_s13059_024_03303_w crossref_primary_10_1016_j_fsi_2020_03_005 crossref_primary_10_1371_journal_pone_0206312 crossref_primary_10_1007_s12035_019_01681_y crossref_primary_10_1016_j_csbj_2024_01_013 crossref_primary_10_1016_j_jff_2023_105591 crossref_primary_10_1038_s41598_021_83345_3 crossref_primary_10_1186_s12859_018_2246_7 crossref_primary_10_1186_s12859_016_1254_8 crossref_primary_10_1093_bioinformatics_bty175 crossref_primary_10_1186_s12859_021_04438_4 crossref_primary_10_1093_nar_gkw734 crossref_primary_10_1111_pbi_12926 crossref_primary_10_1016_j_stem_2024_09_014 crossref_primary_10_1158_1078_0432_CCR_20_2107 crossref_primary_10_1002_widm_1383 crossref_primary_10_1038_s41598_022_23172_2 crossref_primary_10_1038_srep14476 crossref_primary_10_1016_j_scienta_2019_109140 crossref_primary_10_1021_acs_est_8b01066 crossref_primary_10_1111_mec_14591 crossref_primary_10_1007_s00421_023_05167_7 crossref_primary_10_1016_j_isci_2022_105166 crossref_primary_10_1177_1759091415593066 crossref_primary_10_1038_s41419_024_06694_7 crossref_primary_10_1038_srep32975 crossref_primary_10_1093_jac_dkx199 crossref_primary_10_1093_bioinformatics_btz052 crossref_primary_10_1371_journal_pone_0137782 crossref_primary_10_1093_nar_gkw545 crossref_primary_10_1615_CritRevEukaryotGeneExpr_2023046030 crossref_primary_10_1093_bioinformatics_btab091 crossref_primary_10_3390_ijms18061281 crossref_primary_10_1038_s41597_019_0043_4 crossref_primary_10_1093_bioinformatics_btu845 crossref_primary_10_1038_nmeth_4292 crossref_primary_10_1534_g3_115_021022 crossref_primary_10_1094_MPMI_10_18_0275_R crossref_primary_10_1186_1471_2105_15_S9_S6 crossref_primary_10_3389_fimmu_2019_00261 crossref_primary_10_1007_s00299_018_2318_1 crossref_primary_10_3390_insects15010030 crossref_primary_10_1016_j_ygeno_2015_07_006 crossref_primary_10_1093_ecco_jcc_jjaa236 crossref_primary_10_1371_journal_pcbi_1008890 crossref_primary_10_1080_20013078_2019_1684425 crossref_primary_10_1016_j_jconrel_2023_07_045 crossref_primary_10_1214_17_BA1055 crossref_primary_10_1194_jlr_M090555 crossref_primary_10_1515_sagmb_2014_0018 crossref_primary_10_1186_s12864_015_1406_7 crossref_primary_10_1186_s12967_021_02936_w crossref_primary_10_1371_journal_pone_0263344 crossref_primary_10_3389_fmicb_2020_00649 crossref_primary_10_1186_s12864_016_2646_x crossref_primary_10_1016_j_cbd_2020_100716 crossref_primary_10_1038_s41477_023_01545_3 crossref_primary_10_3389_fgene_2021_650795 crossref_primary_10_4137_BBI_S29470 crossref_primary_10_1186_s12864_019_5851_6 crossref_primary_10_1371_journal_pone_0071462 crossref_primary_10_1161_CIRCGENETICS_113_000129 crossref_primary_10_3390_biomedinformatics1020004 crossref_primary_10_1007_s00425_023_04236_7 crossref_primary_10_1111_tpj_17125 crossref_primary_10_1007_s12192_021_01217_1 crossref_primary_10_1186_s12859_019_3070_4 crossref_primary_10_1080_15592294_2020_1789270 crossref_primary_10_1371_journal_pbio_3001909 crossref_primary_10_1109_RBME_2012_2228311 crossref_primary_10_3389_fmicb_2018_00299 crossref_primary_10_1093_bib_bbae241 crossref_primary_10_1177_2211068214561788 crossref_primary_10_1007_s13253_015_0232_3 crossref_primary_10_1038_s41598_017_01299_x crossref_primary_10_1016_j_genrep_2016_12_011 crossref_primary_10_1093_nar_gkv014 crossref_primary_10_1093_nar_gku166 crossref_primary_10_3390_jof8060637 crossref_primary_10_1016_j_compbiomed_2015_07_029 crossref_primary_10_1007_s00500_022_07515_9 crossref_primary_10_1186_s42523_022_00186_9 crossref_primary_10_1172_jci_insight_98240 crossref_primary_10_4137_BBI_S38193 crossref_primary_10_1038_s41467_018_05627_1 crossref_primary_10_1093_bioinformatics_btz089 crossref_primary_10_1016_j_isci_2022_105102 crossref_primary_10_1155_2014_248090 crossref_primary_10_1093_nar_gkx680 crossref_primary_10_1038_srep46264 crossref_primary_10_4109_jslab_32_123 crossref_primary_10_1007_s10260_019_00496_4 crossref_primary_10_3390_w14213391 crossref_primary_10_1242_dev_098657 crossref_primary_10_1016_j_tplants_2015_06_013 crossref_primary_10_3892_ol_2021_13136 crossref_primary_10_3390_ijerph18157975 crossref_primary_10_1155_2015_621690 crossref_primary_10_1186_1471_2164_15_1008 crossref_primary_10_1007_s12064_016_0224_z crossref_primary_10_1002_biot_201500107 crossref_primary_10_1016_j_tplants_2013_02_001 crossref_primary_10_1016_j_compbiolchem_2017_10_010 crossref_primary_10_3402_jev_v4_29454 crossref_primary_10_7717_peerj_6710 crossref_primary_10_1016_j_vaccine_2015_04_054 crossref_primary_10_3389_fmicb_2023_1225781 crossref_primary_10_1038_s41559_023_02224_4 crossref_primary_10_3389_fgene_2019_00097 crossref_primary_10_3390_cancers13143470 crossref_primary_10_1186_s12920_020_00767_0 crossref_primary_10_4137_CIN_S13876 crossref_primary_10_1016_j_compbiomed_2021_104603 crossref_primary_10_1111_vco_12863 crossref_primary_10_1093_database_bav019 crossref_primary_10_1093_molbev_msab249 crossref_primary_10_1371_journal_pgen_1005592 crossref_primary_10_1016_j_csda_2016_01_011 crossref_primary_10_2147_IJGM_S439845 crossref_primary_10_1007_s10750_018_3682_0 crossref_primary_10_1186_s40880_015_0040_8 crossref_primary_10_1016_j_scitotenv_2022_153778 crossref_primary_10_1186_1471_2229_13_213 crossref_primary_10_1371_journal_pone_0273766 crossref_primary_10_3168_jds_2019_16397 crossref_primary_10_1038_s41576_019_0150_2 crossref_primary_10_1111_1462_2920_12668 crossref_primary_10_1126_science_aao3526 crossref_primary_10_1186_s13058_016_0710_8 crossref_primary_10_1007_s13592_019_00702_y crossref_primary_10_1016_j_jprot_2016_05_032 crossref_primary_10_1093_nar_gkaa850 crossref_primary_10_1371_journal_pone_0158899 crossref_primary_10_1186_s12864_019_6261_5 crossref_primary_10_1093_jas_skab346 crossref_primary_10_3389_fgene_2019_00911 crossref_primary_10_1186_s12864_022_08465_0 crossref_primary_10_1080_10618600_2022_2090947 crossref_primary_10_3389_fgene_2021_700489 crossref_primary_10_3390_v13040593 crossref_primary_10_1093_bib_bbab193 crossref_primary_10_1038_s41598_022_15578_9 crossref_primary_10_1186_s13229_015_0040_1 crossref_primary_10_1016_j_jcmgh_2023_04_004 crossref_primary_10_1007_s40484_018_0144_7 crossref_primary_10_1093_bib_bbab194 crossref_primary_10_1007_s10123_024_00536_4 crossref_primary_10_4014_jmb_2201_01034 crossref_primary_10_1038_s41598_020_74567_y crossref_primary_10_3389_fmars_2021_695236 crossref_primary_10_1038_s41590_017_0005_y crossref_primary_10_1016_j_toxlet_2016_06_2101 crossref_primary_10_1177_1471082X17706135 crossref_primary_10_1016_j_copbio_2014_06_011 crossref_primary_10_1111_1755_0998_12500 crossref_primary_10_1007_s00280_023_04616_6 crossref_primary_10_1186_s12859_015_0778_7 crossref_primary_10_32707_ercivet_1142293 crossref_primary_10_1038_s41598_017_14084_7 crossref_primary_10_1186_s12920_015_0116_y crossref_primary_10_1038_s41598_019_42157_2 crossref_primary_10_1089_omi_2013_0010 crossref_primary_10_3389_fgene_2023_1235927 crossref_primary_10_1261_rna_059360_116 crossref_primary_10_1038_s41598_019_42485_3 crossref_primary_10_1186_s12859_015_0763_1 crossref_primary_10_1007_s11427_021_2060_x crossref_primary_10_1038_s41536_021_00129_z crossref_primary_10_1080_20013078_2018_1446660 crossref_primary_10_1186_2049_2618_2_15 crossref_primary_10_1160_TH15_05_0411 crossref_primary_10_1093_bioinformatics_btz801 crossref_primary_10_1371_journal_pone_0077885 crossref_primary_10_1186_s12864_016_2508_6 crossref_primary_10_1534_genetics_114_169268 crossref_primary_10_1038_ncomms9878 crossref_primary_10_1093_nar_gky258 crossref_primary_10_1038_s41437_018_0136_4 crossref_primary_10_1016_j_psyneuen_2019_104468 crossref_primary_10_1186_s12864_016_3417_4 crossref_primary_10_3390_ijms17122125 crossref_primary_10_1038_s43586_022_00188_6 crossref_primary_10_1038_s41598_018_23069_z crossref_primary_10_1128_AEM_00185_16 crossref_primary_10_1016_j_freeradbiomed_2019_08_010 crossref_primary_10_1016_j_csbj_2020_05_018 crossref_primary_10_1186_s12859_024_05801_x crossref_primary_10_7717_peerj_576 crossref_primary_10_1016_j_csbj_2020_05_010 crossref_primary_10_1016_j_jprot_2018_03_032 crossref_primary_10_1186_1471_2105_16_S9_S2 crossref_primary_10_3389_fmicb_2023_1217750 crossref_primary_10_1038_srep46318 crossref_primary_10_3389_fnmol_2017_00045 crossref_primary_10_1186_s12859_018_2261_8 crossref_primary_10_1111_biom_12516 crossref_primary_10_1111_tpj_15666 crossref_primary_10_1111_tpj_16513 crossref_primary_10_1186_1754_6834_6_179 crossref_primary_10_1186_1471_2105_15_79 crossref_primary_10_1007_s11676_018_0773_8 crossref_primary_10_1038_s41598_024_75864_6 crossref_primary_10_1186_s12920_019_0538_z crossref_primary_10_1002_1878_0261_12669 crossref_primary_10_1111_2041_210X_13582 crossref_primary_10_1038_s41598_017_02325_8 crossref_primary_10_1038_s41598_017_02073_9 crossref_primary_10_1093_bioinformatics_btab645 crossref_primary_10_1002_vms3_859 crossref_primary_10_3390_ijms21010167 crossref_primary_10_3390_v13122409 crossref_primary_10_3389_fpls_2016_00348 crossref_primary_10_1182_bloodadvances_2017006668 crossref_primary_10_1214_17_AOAS1123 crossref_primary_10_1016_j_plgene_2020_100257 crossref_primary_10_1093_bib_bbab573 crossref_primary_10_1093_bioinformatics_btab641 crossref_primary_10_1093_bioinformatics_btv253 crossref_primary_10_1038_s41392_022_00990_4 crossref_primary_10_1111_2041_210X_13115 crossref_primary_10_1186_s12864_015_2353_z crossref_primary_10_7554_eLife_15657 crossref_primary_10_1534_g3_118_200174 crossref_primary_10_1016_j_cbd_2019_100601 crossref_primary_10_1093_jxb_eraa221 crossref_primary_10_1111_acel_12283 crossref_primary_10_3389_fpls_2014_00213 crossref_primary_10_4137_BBI_S12467 crossref_primary_10_1109_TCBB_2015_2485223 crossref_primary_10_1186_s13059_025_03525_6 crossref_primary_10_1016_j_livsci_2014_04_028 crossref_primary_10_1371_journal_pbio_3000481 crossref_primary_10_1155_2016_4305252 crossref_primary_10_1371_journal_ppat_1006033 crossref_primary_10_1186_s12864_021_07563_9 crossref_primary_10_1111_gbb_12007 crossref_primary_10_1016_j_exer_2018_01_009 crossref_primary_10_1093_bioinformatics_btx210 crossref_primary_10_1093_bioinformatics_bty783 crossref_primary_10_1186_s12864_018_4487_2 crossref_primary_10_1016_j_mib_2014_11_011 crossref_primary_10_1093_bib_bbab345 crossref_primary_10_1093_dnares_dsy011 crossref_primary_10_1016_j_plantsci_2019_110383 crossref_primary_10_1038_s41598_024_57670_2 crossref_primary_10_48130_forres_0024_0017 crossref_primary_10_1016_j_jphotobiol_2022_112550 crossref_primary_10_3389_ffunb_2021_768648 crossref_primary_10_3389_fpls_2016_01403 crossref_primary_10_1093_bib_bbab343 crossref_primary_10_1186_s12859_020_3450_9 crossref_primary_10_1002_wrna_1274 crossref_primary_10_3389_fmolb_2024_1499220 crossref_primary_10_1371_journal_pntd_0005209 crossref_primary_10_3390_genes10121042 crossref_primary_10_1016_j_csbj_2023_11_012 crossref_primary_10_1021_acs_jproteome_7b00646 crossref_primary_10_1111_pedi_13207 crossref_primary_10_1371_journal_pone_0116008 crossref_primary_10_1371_journal_pone_0242382 crossref_primary_10_1186_s13007_019_0440_x crossref_primary_10_1038_s41467_019_14184_0 crossref_primary_10_1186_2049_1891_5_32 crossref_primary_10_1186_s12864_017_3916_y crossref_primary_10_1016_j_ncrna_2025_03_003 crossref_primary_10_1093_bfgp_elu035 crossref_primary_10_3389_fgene_2018_00588 crossref_primary_10_1038_s41598_021_96046_8 crossref_primary_10_1136_jitc_2021_004335 crossref_primary_10_3389_fmicb_2020_570903 crossref_primary_10_1016_j_bbalip_2018_02_001 crossref_primary_10_1093_nar_gku976 crossref_primary_10_1186_1471_2164_16_S6_S2 crossref_primary_10_1128_AEM_02312_19 crossref_primary_10_21769_BioProtoc_4161 crossref_primary_10_1038_nbt_2931 crossref_primary_10_1186_s12859_015_0794_7 crossref_primary_10_1093_bib_bby045 crossref_primary_10_3389_fgene_2021_644091 crossref_primary_10_1007_s12094_022_02944_2 crossref_primary_10_1093_bioinformatics_btx017 crossref_primary_10_1016_j_semcdb_2017_07_030 crossref_primary_10_1186_s12864_018_4637_6 crossref_primary_10_1371_journal_pone_0182694 crossref_primary_10_1002_ece3_7083 crossref_primary_10_1186_s12859_016_1208_1 crossref_primary_10_1371_journal_pone_0201813 crossref_primary_10_18632_oncotarget_7364 crossref_primary_10_3168_jds_2018_15516 crossref_primary_10_1111_mec_14522 crossref_primary_10_18632_oncotarget_28690 crossref_primary_10_3390_ijms21051720 crossref_primary_10_18632_aging_203588 crossref_primary_10_1038_srep16946 crossref_primary_10_1016_j_plgene_2016_11_006 crossref_primary_10_1021_acs_jafc_9b02295 crossref_primary_10_1038_s41598_018_21587_4 crossref_primary_10_1093_nar_gkv806 crossref_primary_10_1016_j_plantsci_2017_01_005 crossref_primary_10_1016_j_heliyon_2019_e03079 crossref_primary_10_1016_j_margen_2018_05_005 crossref_primary_10_1038_nbt_2957 crossref_primary_10_1021_pr401106h crossref_primary_10_1186_s12859_023_05147_w crossref_primary_10_1186_s12864_015_1503_7 crossref_primary_10_1007_s00253_021_11563_w crossref_primary_10_18632_oncotarget_1822 crossref_primary_10_1109_TCBB_2017_2770120 crossref_primary_10_1186_1471_2105_15_188 crossref_primary_10_1097_HCO_0000000000000275 crossref_primary_10_1101_gr_184168_114 crossref_primary_10_1093_bioinformatics_btaa153 crossref_primary_10_1002_bit_26847 crossref_primary_10_1016_j_freeradbiomed_2015_01_004 crossref_primary_10_3389_fpls_2018_00004 crossref_primary_10_1534_genetics_115_182311 crossref_primary_10_1186_s40537_024_00902_z crossref_primary_10_1142_S0219720015500109 crossref_primary_10_1093_molbev_msw096 crossref_primary_10_1109_TCBB_2018_2790918 crossref_primary_10_1186_s12864_021_07369_9 crossref_primary_10_1371_journal_pntd_0005067 crossref_primary_10_1371_journal_pntd_0006152 crossref_primary_10_2119_molmed_2016_00078 crossref_primary_10_1093_nar_gkw953 crossref_primary_10_1016_j_gene_2017_04_023 crossref_primary_10_3389_fgene_2019_01207 crossref_primary_10_1038_s42003_018_0059_x crossref_primary_10_3389_fmicb_2016_00459 crossref_primary_10_1111_php_14003 crossref_primary_10_1093_bib_bbx153 crossref_primary_10_1002_ajhb_23784 crossref_primary_10_1016_j_gene_2015_01_002 crossref_primary_10_3390_plants12162894 crossref_primary_10_7554_eLife_78216 crossref_primary_10_3389_fgene_2022_833989 crossref_primary_10_1016_j_yrtph_2015_04_010 crossref_primary_10_3390_cells13171502 crossref_primary_10_1186_s12859_017_1912_5 crossref_primary_10_1038_s41598_018_37669_2 crossref_primary_10_1093_gbe_evx218 crossref_primary_10_3390_fishes7040152 crossref_primary_10_1093_nargab_lqaa093 crossref_primary_10_1186_s12864_015_1767_y crossref_primary_10_3389_fgene_2020_00041 crossref_primary_10_1016_j_bbagrm_2024_195058 crossref_primary_10_3389_fpls_2023_1210046 crossref_primary_10_1016_j_tiv_2016_09_013 crossref_primary_10_3390_ijms24108671 crossref_primary_10_1177_2515841419835460 crossref_primary_10_1186_s12870_021_02993_9 crossref_primary_10_3389_fonc_2021_779042 crossref_primary_10_1200_CCI_19_00118 crossref_primary_10_7554_eLife_02510 crossref_primary_10_1186_s12864_017_4251_z crossref_primary_10_1371_journal_pone_0094839 crossref_primary_10_4142_jvs_2018_19_1_99 crossref_primary_10_1038_srep45674 crossref_primary_10_1128_mBio_02302_20 crossref_primary_10_3390_insects15080612 crossref_primary_10_1186_s12859_014_0397_8 crossref_primary_10_1016_j_phytochem_2022_113419 crossref_primary_10_1261_rna_074922_120 crossref_primary_10_1038_jhg_2015_123 crossref_primary_10_1038_s41598_020_76881_x crossref_primary_10_1093_bib_bbx008 crossref_primary_10_3389_fmicb_2022_963218 crossref_primary_10_1016_j_scitotenv_2019_02_281 crossref_primary_10_1186_s12859_019_3247_x crossref_primary_10_1016_j_jhazmat_2024_135759 crossref_primary_10_3389_fgene_2021_722981 crossref_primary_10_1016_j_mbs_2021_108713 crossref_primary_10_1038_s44220_023_00148_3 crossref_primary_10_1128_mBio_01442_14 crossref_primary_10_3389_fimmu_2019_02367 crossref_primary_10_3934_mbe_2023476 crossref_primary_10_3390_a17080342 crossref_primary_10_1101_gr_177725_114 crossref_primary_10_3389_fgene_2022_890672 crossref_primary_10_1038_s41598_019_52770_w crossref_primary_10_1186_s12864_014_1194_5 crossref_primary_10_1038_s41598_018_28168_5 crossref_primary_10_1093_bib_bbw139 crossref_primary_10_1093_function_zqaa009 crossref_primary_10_1186_s12957_018_1380_z crossref_primary_10_1530_REP_16_0034 crossref_primary_10_3389_fgene_2024_1369628 crossref_primary_10_1371_journal_pone_0165919 crossref_primary_10_1111_mec_14003 crossref_primary_10_1016_j_gdata_2014_07_003 crossref_primary_10_1038_s41467_022_32906_9 crossref_primary_10_1186_s12859_015_0704_z crossref_primary_10_1016_j_mce_2014_10_005 crossref_primary_10_1038_s41587_022_01440_w crossref_primary_10_1186_s13059_015_0679_0 crossref_primary_10_3390_v8080239 crossref_primary_10_1093_bib_bbw128 crossref_primary_10_1002_ddr_21215 crossref_primary_10_1186_s40168_022_01423_8 crossref_primary_10_1128_msystems_00053_18 crossref_primary_10_1002_wrna_1631 crossref_primary_10_1016_j_xpro_2021_100397 crossref_primary_10_18632_oncotarget_28161 crossref_primary_10_1186_s12864_018_4852_1 crossref_primary_10_15252_msb_20188746 crossref_primary_10_1080_10495398_2020_1784185 crossref_primary_10_1038_s42003_019_0284_y crossref_primary_10_1186_s40064_015_0873_2 crossref_primary_10_13070_mm_en_3_203 crossref_primary_10_1016_j_csbj_2019_04_012 crossref_primary_10_1038_srep42659 crossref_primary_10_1126_scitranslmed_aan1217 crossref_primary_10_2174_1574893615666200203104214 crossref_primary_10_1093_bib_bbt086 crossref_primary_10_1186_s12934_020_01489_9 crossref_primary_10_1093_bib_bbv019 crossref_primary_10_3390_cimb44030074 crossref_primary_10_1016_j_cbd_2022_101014 crossref_primary_10_1016_j_celrep_2018_07_025 crossref_primary_10_1534_g3_117_040683 crossref_primary_10_1186_s13068_015_0213_3 crossref_primary_10_1089_scd_2015_0321 crossref_primary_10_1016_j_trsl_2016_07_012 crossref_primary_10_1016_j_cell_2021_04_024 crossref_primary_10_3390_jcm12206683 crossref_primary_10_1038_ismej_2013_229 crossref_primary_10_1371_journal_pone_0151975 crossref_primary_10_3390_cancers17060996 crossref_primary_10_3389_fpls_2019_00983 crossref_primary_10_1089_cmb_2020_0558 crossref_primary_10_1094_PDIS_04_16_0492_RE crossref_primary_10_1007_s12539_017_0276_x crossref_primary_10_1016_j_jgr_2018_05_007 crossref_primary_10_1038_s42003_019_0721_y crossref_primary_10_1186_s13062_018_0204_y crossref_primary_10_1261_rna_037895_112 crossref_primary_10_1038_s41467_025_55845_7 crossref_primary_10_1371_journal_pone_0125224 crossref_primary_10_1007_s12035_018_0988_x crossref_primary_10_1371_journal_pone_0169249 crossref_primary_10_1016_j_pmpp_2020_101480 crossref_primary_10_1371_journal_pone_0157022 crossref_primary_10_1186_s12864_024_10414_y crossref_primary_10_1111_mec_13344 crossref_primary_10_1007_s00122_018_3070_1 crossref_primary_10_1093_nar_gkac1056 crossref_primary_10_1186_1471_2105_14_357 crossref_primary_10_1093_nar_gkw655 crossref_primary_10_1186_s12870_023_04263_2 crossref_primary_10_3389_fpls_2017_01876 crossref_primary_10_1016_j_csbj_2017_10_001 crossref_primary_10_1640_0002_8444_109_3_224 crossref_primary_10_1016_j_abb_2021_108986 crossref_primary_10_3389_fmicb_2021_588025 crossref_primary_10_1093_nar_gkac064 crossref_primary_10_1093_gbe_evz176 crossref_primary_10_1186_s12859_014_0401_3 crossref_primary_10_1186_s13059_019_1738_8 crossref_primary_10_3389_fgene_2021_642227 crossref_primary_10_1111_acer_12457 crossref_primary_10_3389_fgene_2021_724527 crossref_primary_10_1186_s40168_017_0237_y crossref_primary_10_3389_fimmu_2021_635131 crossref_primary_10_18632_oncotarget_26808 crossref_primary_10_1080_07352689_2022_2084227 crossref_primary_10_1186_s12859_017_1872_9 crossref_primary_10_7717_peerj_12233 crossref_primary_10_1186_s12864_015_1709_8 crossref_primary_10_1049_nbt2_12115 crossref_primary_10_3389_fnins_2022_915907 crossref_primary_10_12688_f1000research_6536_1 crossref_primary_10_7554_eLife_55862 crossref_primary_10_1038_s41467_021_23558_2 crossref_primary_10_1038_s41467_020_19829_z crossref_primary_10_1016_j_cej_2025_160952 crossref_primary_10_1371_journal_pcbi_1006794 crossref_primary_10_3390_genes13122265 crossref_primary_10_1038_srep06347 crossref_primary_10_1186_s13072_025_00571_z crossref_primary_10_1261_rna_070227_118 crossref_primary_10_1186_s12859_017_1994_0 crossref_primary_10_1016_j_actatropica_2016_12_021 crossref_primary_10_1186_s12859_021_04339_6 crossref_primary_10_1007_s12892_023_00197_1 crossref_primary_10_1038_ismej_2014_78 crossref_primary_10_1093_icb_icw003 crossref_primary_10_1016_j_heliyon_2024_e35121 crossref_primary_10_1002_jcp_27486 crossref_primary_10_1038_nature23278 crossref_primary_10_1126_science_aaa9420 crossref_primary_10_1371_journal_pone_0147426 crossref_primary_10_1371_journal_pone_0227760 crossref_primary_10_1038_s41467_024_50420_y crossref_primary_10_1038_s41576_021_00326_y crossref_primary_10_1186_s12870_019_2195_y crossref_primary_10_3389_fmicb_2018_02397 crossref_primary_10_1093_pcp_pcv117 crossref_primary_10_1016_j_eti_2023_103377 crossref_primary_10_1111_ppa_13865 crossref_primary_10_1007_s00497_014_0253_z crossref_primary_10_1093_nar_gkw267 crossref_primary_10_1371_journal_pone_0147873 crossref_primary_10_1371_journal_pgen_1008328 crossref_primary_10_7717_peerj_1360 crossref_primary_10_1007_s10725_019_00507_0 crossref_primary_10_1038_s41467_020_19015_1 crossref_primary_10_2298_ABS240301014P crossref_primary_10_1073_pnas_2106682118 crossref_primary_10_3390_ani9100753 crossref_primary_10_1186_s12864_018_5386_2 crossref_primary_10_1111_1755_0998_13730 crossref_primary_10_1371_journal_pone_0176185 crossref_primary_10_3389_fgene_2023_1094099 crossref_primary_10_1086_710763 crossref_primary_10_1186_s12864_021_07790_0 crossref_primary_10_1038_s41564_018_0285_5 crossref_primary_10_1016_j_ejphar_2021_174094 crossref_primary_10_3892_ijmm_2022_5217 crossref_primary_10_1089_omi_2013_0110 crossref_primary_10_1186_s13059_015_0853_4 crossref_primary_10_1093_bioinformatics_btw521 crossref_primary_10_3389_fphys_2019_00008 crossref_primary_10_15446_abc_v19n2_41010 crossref_primary_10_1093_molbev_msac269 crossref_primary_10_1016_j_cbd_2024_101243 crossref_primary_10_1186_s12864_019_5870_3 crossref_primary_10_1002_ece3_6235 crossref_primary_10_1371_journal_pone_0192610 crossref_primary_10_1038_nprot_2013_084 crossref_primary_10_1371_journal_pone_0268072 crossref_primary_10_1371_journal_pntd_0004406 crossref_primary_10_1186_s13059_019_1682_7 crossref_primary_10_29130_dubited_803846 crossref_primary_10_1038_hdy_2017_50 crossref_primary_10_1093_bioinformatics_btv425 crossref_primary_10_1093_bib_bbac158 crossref_primary_10_1111_1758_2229_70026 crossref_primary_10_1111_imb_12260 crossref_primary_10_1371_journal_pone_0199021 crossref_primary_10_3389_fgene_2021_667936 crossref_primary_10_1016_j_aquaculture_2023_740200 crossref_primary_10_1016_j_csbj_2020_02_010 crossref_primary_10_1515_biolog_2015_0127 crossref_primary_10_1093_bioinformatics_btx606 crossref_primary_10_1016_j_gene_2018_03_073 crossref_primary_10_7717_peerj_4600 |
| Cites_doi | 10.1038/415530a 10.1017/S0016672307008646 10.1038/nature07509 10.1038/ng.259 10.1038/nbt.1883 10.1007/978-1-60761-842-3_3 10.1186/gb-2002-3-7-reports0033 10.1093/bioinformatics/19.2.185 10.1093/biostatistics/kxr054 10.1186/1471-2105-12-480 10.1093/nar/gkn430 10.1038/onc.2010.612 10.1073/pnas.0932692100 10.1093/nar/gkq817 10.1038/nmeth.1226 10.1093/bioinformatics/bts094 10.1111/j.2517-6161.1995.tb02031.x 10.1038/nrg2484 10.1038/ng1032 10.1186/1748-7188-7-5 10.1038/nbt.1621 10.1186/1471-2105-12-323 10.1038/nbt.1633 10.1371/journal.pone.0012336 10.1038/nature08872 |
| ContentType | Journal Article |
| Copyright | Copyright Oxford Publishing Limited(England) Nov 2013 Distributed under a Creative Commons Attribution 4.0 International License |
| Copyright_xml | – notice: Copyright Oxford Publishing Limited(England) Nov 2013 – notice: Distributed under a Creative Commons Attribution 4.0 International License |
| CorporateAuthor | on behalf of The French StatOmique Consortium French StatOmique Consortium |
| CorporateAuthor_xml | – name: on behalf of The French StatOmique Consortium – name: French StatOmique Consortium |
| DBID | AAYXX CITATION CGR CUY CVF ECM EIF NPM 7QO 7SC 8FD FR3 JQ2 K9. L7M L~C L~D P64 RC3 7X8 7TM 1XC |
| DOI | 10.1093/bib/bbs046 |
| DatabaseName | CrossRef Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed Biotechnology Research Abstracts Computer and Information Systems Abstracts Technology Research Database Engineering Research Database ProQuest Computer Science Collection ProQuest Health & Medical Complete (Alumni) Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional Biotechnology and BioEngineering Abstracts Genetics Abstracts MEDLINE - Academic Nucleic Acids Abstracts Hyper Article en Ligne (HAL) |
| DatabaseTitle | CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) Genetics Abstracts Biotechnology Research Abstracts Technology Research Database Computer and Information Systems Abstracts – Academic ProQuest Computer Science Collection Computer and Information Systems Abstracts ProQuest Health & Medical Complete (Alumni) Engineering Research Database Advanced Technologies Database with Aerospace Biotechnology and BioEngineering Abstracts Computer and Information Systems Abstracts Professional MEDLINE - Academic Nucleic Acids Abstracts |
| DatabaseTitleList | MEDLINE - Academic Engineering Research Database Genetics Abstracts MEDLINE |
| Database_xml | – sequence: 1 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: EIF name: MEDLINE url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search sourceTypes: Index Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Biology Statistics |
| EISSN | 1477-4054 |
| EndPage | 683 |
| ExternalDocumentID | oai_HAL_hal_00782486v1 3129297121 22988256 10_1093_bib_bbs046 |
| Genre | Research Support, Non-U.S. Gov't Journal Article Feature |
| GroupedDBID | --- -E4 .2P .I3 0R~ 1TH 23N 2WC 36B 4.4 48X 53G 5GY 5VS 6J9 70D 8VB AAHBH AAIJN AAIMJ AAJKP AAJQQ AAMDB AAMVS AAOGV AAPQZ AAPXW AARHZ AAVAP AAVLN AAYXX ABDBF ABEJV ABEUO ABGNP ABIXL ABNKS ABPQP ABPTD ABQLI ABWST ABXVV ABXZS ABZBJ ACGFO ACGFS ACGOD ACIWK ACPRK ACUFI ACUHS ACUXJ ACYTK ADBBV ADEYI ADFTL ADGKP ADGZP ADHKW ADHZD ADOCK ADPDF ADQBN ADRDM ADRTK ADVEK ADYVW ADZTZ ADZXQ AECKG AEGPL AEGXH AEJOX AEKKA AEKSI AELWJ AEMDU AEMOZ AENEX AENZO AEPUE AETBJ AEWNT AFFZL AFGWE AFIYH AFOFC AFRAH AGINJ AGKEF AGQXC AGSYK AHMBA AHQJS AHXPO AIAGR AIJHB AJEEA AJEUX AKHUL AKVCP AKWXX ALMA_UNASSIGNED_HOLDINGS ALTZX ALUQC ALXQX AMNDL ANAKG APIBT APWMN ARIXL AXUDD AYOIW AZVOD BAWUL BAYMD BEYMZ BHONS BQDIO BQUQU BSWAC BTQHN C45 CDBKE CITATION CS3 CZ4 DAKXR DIK DILTD DU5 D~K E3Z EAD EAP EAS EBA EBC EBD EBR EBS EBU EE~ EJD EMB EMK EMOBN EST ESX F5P F9B FHSFR FLIZI FLUFQ FOEOM FQBLK GAUVT GJXCC GX1 H13 H5~ HAR HW0 HZ~ IOX J21 JXSIZ K1G KBUDW KOP KSI KSN M-Z MK~ ML0 N9A NGC NLBLG NMDNZ NOMLY O0~ O9- OAWHX ODMLO OJQWA OK1 OVD OVEED P2P PAFKI PEELM PQQKQ Q1. Q5Y QWB RD5 RPM RUSNO RW1 RXO SV3 TEORI TH9 TJP TLC TOX TR2 TUS W8F WOQ X7H YAYTL YKOAZ YXANX ZKX ZL0 ~91 AAGQS AAUQX ABQTQ C1A CAG CGR COF CUY CVF ECM EIF GROUPED_DOAJ M49 NPM NU- 7QO 7SC 8FD FR3 JQ2 K9. L7M L~C L~D P64 RC3 7X8 7TM 1XC AHGBF |
| ID | FETCH-LOGICAL-c484t-1f86f7459b775c0958163fbe6772e0f4aaf3a480e05eb5318aa6b28fa41cc7c83 |
| ISSN | 1467-5463 1477-4054 |
| IngestDate | Sat Aug 23 06:30:57 EDT 2025 Thu Jul 10 18:28:19 EDT 2025 Thu Jul 10 22:02:03 EDT 2025 Mon Jun 30 09:02:23 EDT 2025 Thu Apr 03 06:59:55 EDT 2025 Tue Jul 01 03:39:21 EDT 2025 Thu Apr 24 23:07:31 EDT 2025 |
| IsDoiOpenAccess | false |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 6 |
| Keywords | differential analysis RNA-seq normalization high-throughput sequencing |
| Language | English |
| License | Distributed under a Creative Commons Attribution 4.0 International License: http://creativecommons.org/licenses/by/4.0 |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c484t-1f86f7459b775c0958163fbe6772e0f4aaf3a480e05eb5318aa6b28fa41cc7c83 |
| Notes | SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 content type line 23 |
| ORCID | 0000-0001-9487-2624 0000-0002-6241-1732 0000-0001-7579-6419 0000-0002-5094-7302 0000-0001-5836-2803 0000-0001-7604-3814 0000-0003-1678-7410 0000-0001-5203-5748 0000-0002-7437-8239 0000-0001-6239-4357 0000-0001-8359-0760 0000-0001-6469-488X 0000-0002-0534-7797 |
| OpenAccessLink | https://academic.oup.com/bib/article-pdf/14/6/671/467651/bbs046.pdf |
| PMID | 22988256 |
| PQID | 1459218220 |
| PQPubID | 26846 |
| PageCount | 13 |
| ParticipantIDs | hal_primary_oai_HAL_hal_00782486v1 proquest_miscellaneous_1492611568 proquest_miscellaneous_1450183231 proquest_journals_1459218220 pubmed_primary_22988256 crossref_primary_10_1093_bib_bbs046 crossref_citationtrail_10_1093_bib_bbs046 |
| ProviderPackageCode | CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | 2013-11-01 |
| PublicationDateYYYYMMDD | 2013-11-01 |
| PublicationDate_xml | – month: 11 year: 2013 text: 2013-11-01 day: 01 |
| PublicationDecade | 2010 |
| PublicationPlace | England |
| PublicationPlace_xml | – name: England – name: Oxford |
| PublicationTitle | Briefings in bioinformatics |
| PublicationTitleAlternate | Brief Bioinform |
| PublicationYear | 2013 |
| Publisher | Oxford Publishing Limited (England) Oxford University Press (OUP) |
| Publisher_xml | – name: Oxford Publishing Limited (England) – name: Oxford University Press (OUP) |
| References | (11_43628715) 2010; 79 (18_28263016) 2002; 32 (42_43628721) 2010; 112 Mortazavi (19_31403652) 2008; 5 Jeanmougin (29_38125486) 2010; 5 Pan (4_32505995) 2008; 40 (28_31629782) 2008; 36 (10_43628714) 2009; 4587234 Li (45_40502883) 2011; 12 Grabherr (8_39941153) 2011; 29 Calza (43_38119305) 2010; 673 (2_19682808) 2003; 100 Risso (32_41800854) 2011; 12 Wang (3_32505959) 2008; 456 (12_43628716) 2010; 674 Bolstad (22_17474861) 2003; 19 (36_41492176) 2011; 10 (40_38158488) 2011; 39 van 't Veer (1_16897320) 2002; 415 Strub (30_39056446) 2011; 30 (34_43628718) 2003; 197 (35_43628719) 2004; 10116 (7_43628713) 2010; 11 Kadota (44_42343489) 2012; 7 Jaffrezic (27_28757437) 2007; 89 Wang (38_32672279) 2009; 10 (33_41589437) 2012; 13 (23_39128509) 2003; 40 (39_43628720) 2002; 3 Trapnell (5_37213217) 2010; 28 (9_41913738) 2012; 28 (37_31268577) 1995; 57 Guttman (6_37213215) 2010; 28 Pickrell (21_36792846) 2010; 464 (14_43628717) 2010; 11106 |
| References_xml | – volume: 415 start-page: 530 issn: 1476-4687 issue: 6871 year: 2002 ident: 1_16897320 publication-title: Nature; Physical Science (London) doi: 10.1038/415530a – volume: 89 start-page: 19 issn: 0016-6723 issue: 1 year: 2007 ident: 27_28757437 publication-title: Genetical research doi: 10.1017/S0016672307008646 – volume: 456 start-page: 470 issn: 1476-4687 issue: 7221 year: 2008 ident: 3_32505959 publication-title: Nature; Physical Science (London) doi: 10.1038/nature07509 – volume: 40 start-page: 1413 issn: 1061-4036 issue: 12 year: 2008 ident: 4_32505995 publication-title: Nature genetics doi: 10.1038/ng.259 – volume: 29 start-page: 644 issn: 1087-0156 issue: 7 year: 2011 ident: 8_39941153 publication-title: Nature biotechnology doi: 10.1038/nbt.1883 – volume: 10 start-page: 1 issn: 1544-6115 year: 2011 ident: 36_41492176 – volume: 79 start-page: 709 issn: 1548-7091 year: 2010 ident: 11_43628715 – volume: 673 start-page: 37 issn: 1064-3745 year: 2010 ident: 43_38119305 publication-title: Methods in molecular biology (Clifton, N.J.) doi: 10.1007/978-1-60761-842-3_3 – volume: 3 start-page: research0033 issn: 1465-6906 year: 2002 ident: 39_43628720 publication-title: Genome biology doi: 10.1186/gb-2002-3-7-reports0033 – volume: 19 start-page: 185 issn: 1367-4803 issue: 2 year: 2003 ident: 22_17474861 publication-title: Bioinformatics doi: 10.1093/bioinformatics/19.2.185 – volume: 197 start-page: 362 issn: 0168-9525 year: 2003 ident: 34_43628718 publication-title: Trends in genetics : TIG – volume: 13 start-page: 204 issn: 1465-4644 issue: 2 year: 2012 ident: 33_41589437 publication-title: Biostatistics doi: 10.1093/biostatistics/kxr054 – volume: 112 start-page: R14 issn: 1465-6906 year: 2010 ident: 42_43628721 publication-title: Genome biology – volume: 4587234 start-page: 97 issn: 1476-4687 year: 2009 ident: 10_43628714 publication-title: Nature; Physical Science (London) – volume: 12 start-page: 480 issn: 1471-2105 year: 2011 ident: 32_41800854 publication-title: BMC bioinformatics [electronic resource] doi: 10.1186/1471-2105-12-480 – volume: 36 start-page: e108 issn: 0305-1048 issue: 17 year: 2008 ident: 28_31629782 publication-title: Nucleic Acids Research doi: 10.1093/nar/gkn430 – volume: 30 start-page: 2319 issn: 0950-9232 issue: 20 year: 2011 ident: 30_39056446 publication-title: Oncogene doi: 10.1038/onc.2010.612 – volume: 100 start-page: 8418 issn: 0027-8424 issue: 14 year: 2003 ident: 2_19682808 publication-title: PNAS doi: 10.1073/pnas.0932692100 – volume: 39 start-page: 578 issn: 0305-1048 issue: 2 year: 2011 ident: 40_38158488 publication-title: Nucleic Acids Research doi: 10.1093/nar/gkq817 – volume: 674 start-page: 569 issn: 1420-682X year: 2010 ident: 12_43628716 publication-title: Cellular and molecular life sciences : CMLS – volume: 11 start-page: 909 issn: 1548-7091 year: 2010 ident: 7_43628713 – volume: 5 start-page: 621 issn: 1548-7091 issue: 7 year: 2008 ident: 19_31403652 doi: 10.1038/nmeth.1226 – volume: 11106 start-page: R106 issn: 1465-6906 year: 2010 ident: 14_43628717 publication-title: Genome biology – volume: 28 start-page: 1086 issn: 1367-4803 issue: 8 year: 2012 ident: 9_41913738 publication-title: Bioinformatics doi: 10.1093/bioinformatics/bts094 – volume: 57 start-page: 289 year: 1995 ident: 37_31268577 publication-title: J R STAT SOC B STAT METHODOL doi: 10.1111/j.2517-6161.1995.tb02031.x – volume: 10 start-page: 57 issn: 1471-0056 issue: 1 year: 2009 ident: 38_32672279 publication-title: Nature reviews. Genetics doi: 10.1038/nrg2484 – volume: 32 start-page: 496 issn: 1061-4036 year: 2002 ident: 18_28263016 publication-title: Nature genetics doi: 10.1038/ng1032 – volume: 7 start-page: 5 issn: 1748-7188 issue: 1 year: 2012 ident: 44_42343489 doi: 10.1186/1748-7188-7-5 – volume: 28 start-page: 511 issn: 1087-0156 issue: 5 year: 2010 ident: 5_37213217 publication-title: Nature biotechnology doi: 10.1038/nbt.1621 – volume: 12 start-page: 323 issn: 1471-2105 year: 2011 ident: 45_40502883 publication-title: BMC bioinformatics [electronic resource] doi: 10.1186/1471-2105-12-323 – volume: 28 start-page: 503 issn: 1087-0156 issue: 5 year: 2010 ident: 6_37213215 publication-title: Nature biotechnology doi: 10.1038/nbt.1633 – volume: 5 start-page: e12336 issn: 1932-6203 issue: 9 year: 2010 ident: 29_38125486 doi: 10.1371/journal.pone.0012336 – volume: 464 start-page: 768 issn: 1476-4687 issue: 7289 year: 2010 ident: 21_36792846 publication-title: Nature; Physical Science (London) doi: 10.1038/nature08872 – volume: 10116 start-page: 6062 issn: 0027-8424 year: 2004 ident: 35_43628719 publication-title: PNAS – volume: 40 start-page: 403 year: 2003 ident: 23_39128509 publication-title: SCIENCE AND STATISTICS A FESTSCHRIFT FOR TERRY SPEED |
| SSID | ssj0020781 |
| Score | 2.5940583 |
| Snippet | During the last 3 years, a number of approaches for the normalization of RNA sequencing data have emerged in the literature, differing both in the type of bias... |
| SourceID | hal proquest pubmed crossref |
| SourceType | Open Access Repository Aggregation Database Index Database Enrichment Source |
| StartPage | 671 |
| SubjectTerms | Applications Bias Biochemistry, Molecular Biology Bioinformatics Comparative analysis Genomics High-Throughput Nucleotide Sequencing - methods High-Throughput Nucleotide Sequencing - standards Life Sciences Methodology Ribonucleic acid RNA Sequence Analysis, RNA - methods Sequence Analysis, RNA - standards Simulation Statistics |
| Title | A comprehensive evaluation of normalization methods for Illumina high-throughput RNA sequencing data analysis |
| URI | https://www.ncbi.nlm.nih.gov/pubmed/22988256 https://www.proquest.com/docview/1459218220 https://www.proquest.com/docview/1450183231 https://www.proquest.com/docview/1492611568 https://inria.hal.science/hal-00782486 |
| Volume | 14 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3db9MwELe6ISReEN8UBjIfL6jKlg87cR4j2FRQ6V46qW-R7TlbpZFOW4oET_zp3NlO0kJBg5cocq3U8v18vrPvfkfIW5mFLNImCrg2ecCE1IGKkwze4lN2qqMqNjbaYpqOT9inOZ8PBj_WopZWjdrX37fmlfyPVKEN5IpZsv8g2e6j0ADvIF94goTheSMZFzYi_Mqc-yj0nrrbxmegOXrh8yx9qWjLvjD6iOWNF7UcIVlx4Ev1XGKA8rQY-eBqPELA8NGR9LQlG9e_4GBXtuDnoh6pxdLTrzZrofMf8CDH6aDP6I8HxVltb-VFH10vV11MZbc7FCvl04gwdbuHHW4IMLAmKOpm4bMXLTEC3jysn11EiU_i69UtywAWoaOR3jdb2lodzdawuK5wU1fA5beNwJFkqYXCp7oO2Ra-7elxeXQymZSzw_lsh9yKwdFATTk7nncuO1Ih2fw0P6aW4DZPDuDbB-7LGybNzjkG1P7JW7FWy-weuevdDVo47NwnA1M_ILddAdJvD8mXgm4giPYIosuKbiCIegRREDVtEUR_QRAFBNEeQRQRRFsEPSInR4ez9-PAF-AINBOsCaJKpFXGeK6yjGswxgVY75UyKcyUCSsmZZVIJkITcqNAmQspUxWLSsLy15kWyWOyWy9r85RQ2EU5F0nGjM6YqEyucq5gg5OxkDwxckjetXNYas9Oj0VSLkoXJZGUMN-lm-8hedP1vXScLFt7vQZRdB2QRn1cTEpss3YxE-nXaEj2WkmVfmFfgzfMcyxsEIdD8qr7GdQu3qXJ2ixXtk-Iu2ES_a1PHqfgcaViSJ44FHTDieMcfFuePrvBPzwnd_rFs0d2m6uVeQGmcKNeWrT-BERlu-w |
| linkProvider | Oxford University Press |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=A+comprehensive+evaluation+of+normalization+methods+for+Illumina+high-throughput+RNA+sequencing+data+analysis&rft.jtitle=Briefings+in+bioinformatics&rft.au=Dillies%2C+Marie-Agn%C3%A8s&rft.au=Rau%2C+Andrea&rft.au=Aubert%2C+Julie&rft.au=Hennequet-Antier%2C+Christelle&rft.date=2013-11-01&rft.issn=1477-4054&rft.eissn=1477-4054&rft.volume=14&rft.issue=6&rft.spage=671&rft_id=info:doi/10.1093%2Fbib%2Fbbs046&rft.externalDBID=NO_FULL_TEXT |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1467-5463&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1467-5463&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1467-5463&client=summon |