Rnaseq.uoregon.edu
United States
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| 1 | Rna-seqlopedia |
| No | Text |
| 1 | Rna-seqlopedia |
| 2 | 0. rna-seq workflow copy this link to clipboard |
| 3 | 1. experimental design copy this link to clipboard |
| 4 | 2. rna preparation copy this link to clipboard |
| 5 | 3. library preparation copy this link to clipboard |
| 6 | 4. sequencing copy this link to clipboard |
| 7 | 5. analysis copy this link to clipboard |
| 8 | 6. references copy this link to clipboard |
| No | Text |
| 1 | Writing |
| 2 | Editing |
| 3 | ımplementation |
| 4 | ınquiries |
| 5 | 1.1 overview copy this link to clipboard |
| 6 | 1.2 ıdentify the primary experimental objective. copy this link to clipboard |
| 7 | 1.3 annotation copy this link to clipboard |
| 8 | 1.4 differential gene expression (dge) copy this link to clipboard |
| 9 | 1.5 no subst**ute for "pilot" data copy this link to clipboard |
| 10 | 2.1 overview copy this link to clipboard |
| 11 | 2.2 working with rna copy this link to clipboard |
| 12 | 2.3 stabilize rna copy this link to clipboard |
| 13 | 2.4 ısolate and purify rna copy this link to clipboard |
| 14 | 2.5 target enrichment copy this link to clipboard |
| 15 | 2.6 rna fragmentation copy this link to clipboard |
| 16 | 3.1 overview copy this link to clipboard |
| 17 | 3.2 first-strand synthesis copy this link to clipboard |
| 18 | 3.3 second-strand synthesis copy this link to clipboard |
| 19 | 3.4 optional: fragmentation of cdna copy this link to clipboard |
| 20 | 3.5 sequencing adapters copy this link to clipboard |
| 21 | 3.6 addition of adapters copy this link to clipboard |
| 22 | 3.7 preparation of stranded libraries copy this link to clipboard |
| 23 | 3.8 validation and quantification copy this link to clipboard |
| 24 | 4.1 overview copy this link to clipboard |
| 25 | 4.2 choosing a sequencing platform copy this link to clipboard |
| 26 | 4.3 sample preparation and submission copy this link to clipboard |
| 27 | 5.1 overview copy this link to clipboard |
| 28 | 5.2 ınitial processing of sequencing reads copy this link to clipboard |
| 29 | 5.3 de novo transcriptome a***embly copy this link to clipboard |
| 30 | 5.4 aligning rna-seq reads to a reference copy this link to clipboard |
| 31 | 5.5 annotation of transcripts copy this link to clipboard |
| 32 | 5.6 differential gene/isoform expression copy this link to clipboard |
| 33 | 6.1 experimental design copy this link to clipboard |
| 34 | 6.2 rna preparation copy this link to clipboard |
| 35 | 6.3 library preparation copy this link to clipboard |
| 36 | 6.4 sequencing copy this link to clipboard |
| 37 | 6.5 analysis copy this link to clipboard |
| No | Text |
| 1 | Figure 0.1 rna-seq workflow |
| 2 | Table 1.1 recommendations for rna-seq options based upon experimental objectives. |
| 3 | 1.4.1 replication and dge copy this link to clipboard |
| 4 | 1.4.2 technical vs. biological replication copy this link to clipboard |
| 5 | 1.4.3 how many replicates should be sequenced? copy this link to clipboard |
| 6 | 1.4.4 depth of sequencing copy this link to clipboard |
| 7 | Figure 1.1 |
| 8 | 1.4.5 experimental complexity copy this link to clipboard |
| 9 | Figure 1.2 |
| 10 | 1.4.6 target transcript properties copy this link to clipboard |
| 11 | 1.4.7 treatment effect size copy this link to clipboard |
| 12 | Precautions when working with rna |
| 13 | 2.4.1 solubilization copy this link to clipboard |
| 14 | 2.4.2 mechanical homogenization copy this link to clipboard |
| 15 | Tissue specific considerations |
| 16 | 2.4.3 recovery of rna from lysate copy this link to clipboard |
| 17 | Considerations when using phenol/chloroform part**ioning |
| 18 | Solid-phase extraction vs. organic extraction |
| 19 | Small rnas |
| 20 | Removing genomic dna contaminants |
| 21 | 2.4.4 quant**ation and quality a***essment copy this link to clipboard |
| 22 | Figure 2.1 ıntact vs. degraded rna. |
| 23 | Figure 2.2 |
| 24 | 2.5.1 selection of mrnas via hybridization to oligo-dt copy this link to clipboard |
| 25 | 2.5.2 removal of ribosomal sequences via hybridization copy this link to clipboard |
| 26 | 2.5.3 copy-number normalization via duplex-specific nuclease digestion (dsn) copy this link to clipboard |
| 27 | 2.5.4 target enrichment via size-selection copy this link to clipboard |
| 28 | Figure 2.3 |
| 29 | Figure 3.1 |
| 30 | 3.2.1 first-strand priming using oligo-dt copy this link to clipboard |
| 31 | Considerations before using oligo-dt for 1st strand priming |
| 32 | 3.2.2 first-strand priming using random oligos copy this link to clipboard |
| 33 | 3.2.3 first-strand priming using a pre-ligated oligo copy this link to clipboard |
| 34 | 3.3.1 second-strand synthesis by rna displacement copy this link to clipboard |
| 35 | 3.3.2 second-strand synthesis using an oligo ligated to the 5′-end of the rna template copy this link to clipboard |
| 36 | 3.3.3 second-strand priming using oligo-dg and template switching (smart) copy this link to clipboard |
| 37 | Figure 3.2 |
| 38 | Table 3.1 list of functional elements contained in sequencing adapters. |
| 39 | 3.5.1 multiplexing samples with barcodes/indicies copy this link to clipboard |
| 40 | 3.5.2 paired-end sequencing copy this link to clipboard |
| 41 | 3.6.1 addition of adapters via y-adapter pcr copy this link to clipboard |
| 42 | Figure 3.3 |
| 43 | 3.6.2 addition of adapters via rt/pcr copy this link to clipboard |
| 44 | 3.6.3 addition of adapters via ligation copy this link to clipboard |
| 45 | Figure 3.4 |
| 46 | Figure 3.5 |
| 47 | Stereotypical rna-seq analysis pipeline |
| 48 | Outline: |
| 49 | 5.2.1 demultiplexing by index copy this link to clipboard |
| 50 | 5.2.2 removing adapters copy this link to clipboard |
| 51 | 5.2.3 filtering/trimming reads by quality copy this link to clipboard |
| 52 | 5.2.4 filtering/normalizing reads by k-mer coverage copy this link to clipboard |
| 53 | Table 5.1 read processing software |
| 54 | 5.3.1 de bruijn graph-based a***embly copy this link to clipboard |
| 55 | 5.3.2 overlap-layout-consensus a***embly copy this link to clipboard |
| 56 | 5.4.1 aligning to a reference genome copy this link to clipboard |
| 57 | 5.4.2 aligning to a transcriptome copy this link to clipboard |
| 58 | 5.4.3 microrna aligners copy this link to clipboard |
| 59 | 5.4.4 output files from short read aligners copy this link to clipboard |
| 60 | 5.6.1 normalization of read counts copy this link to clipboard |
| 61 | 5.6.2 differential expression analysis: discrete distribution models copy this link to clipboard |
| 62 | 5.6.3 differential expression analysis: continuous distribution models copy this link to clipboard |
| 63 | 5.6.4 differential expression analysis: nonparametric models copy this link to clipboard |
| 64 | 5.6.5 choice of analysis software copy this link to clipboard |
| 65 | Table 5.2 differential expression software |
| No | Text |
| 1 | 2.4.3.1 organic extraction copy this link to clipboard |
| 2 | 2.4.3.2 solid-phase extraction copy this link to clipboard |
| 3 | 2.4.4.1 a***essing rna quality copy this link to clipboard |
| 4 | 2.4.4.2 a***essing rna quant**y copy this link to clipboard |
| 5 | 2.5.1.1 fis***ng out mature mrna by the tail copy this link to clipboard |
| 6 | 2.5.1.2 supersage enrichment for 3′ mrna tags copy this link to clipboard |
| 7 | 5.3.1.1 commonly used graph-based a***embly software copy this link to clipboard |
| 8 | 5.3.2.1 commonly used olc a***embly software copy this link to clipboard |
| No | Text |
| 1 | Muscle and skin: |
| 2 | Tissues high in fat: |
| 3 | Enzymatic |
| 4 | Metal ion |
| 5 | Heat |
| 6 | Sonication |
| 7 | Barcodes: |
| 8 | Indices: |
| 9 | Velvet/Oases: |
| 10 | Trans-ABySS: |
| 11 | Trinity: |
| No | Text |
| 1 | qualitative |
| 2 | quant**ative |
| 3 | Qualitative |
| 4 | Quant**ative |
| 5 | Sampling variance: |
| 6 | Technical variance: |
| 7 | Biological variance: |
| 8 | counts |
| 9 | variances |
| 10 | Unless you are genuinely interested in comparing technical aspects of RNA-seq, or you expect technical variation to be especially great for a large majority of the target transcripts, we recommend greater resource allocation to biological replication. |
| 11 | differential expression studies using RNA-seq data need to be replicated in order to estimate within- and among-group variation |
| 12 | A |
| 13 | B |
| 14 | Amplification element |
| 15 | Primary sequencing priming site |
| 16 | Barcode/Index |
| 17 | Paired-end sequencing priming site |
| 18 | Index sequencing priming site |
| 19 | not |
| 20 | i |
| 21 | p |
| 22 | i = -10*log10(p) |
| 23 | i = -10*log10[p/(1-p)] |
| 24 | CAP3: |
| 25 | MIRA 3: |
| 26 | Roche GS De Novo a***ember ("Newbler"): |
| 27 | Anders, S, W Huber. (6) |
| 28 | Benjamini, Y, Y Hochberg. (2) |
| 29 | Bullard, JH, E Purdom, KD Hansen, S Dudoit. (4) |
| 30 | Busby, MA, C Stewart, C Miller, K Grzeda, G Marth. (2) |
| 31 | Levin JZ, M. Ya***our, X. Adiconis, et al. (2) |
| 32 | McIntyre, LM, KK Lopiano, AM Morse, V Amin, AL Oberg, LJ Young, SV Nuzhdin. (2) |
| 33 | Noble, WS. (2) |
| 34 | Sokal, R.R., and F.J. Rohlf. (2) |
| 35 | Storey, JD. (2) |
| 36 | Wang, Y, N Ghaffari, CD Johnson, UM Braga-Neto, H Wang, R Chen, H Zhou. (2) |
| 37 | Aranda R, Dineen SM, Craig RL, Guerrieri RA, Robertson JM. (2) |
| 38 | Chomczynski P, Sacchi N. (4) |
| 39 | Ekblom R., Slate J., Horsburgh, et al. (2) |
| 40 | Forconi M, Herschlag D. (2) |
| 41 | Kirby KS. (2) |
| 42 | Matsumura H., Molina C., Kruger D.H., Terauchi R., and Kahl G. (2) |
| 43 | Raz T, Kapranov P, Lipson D, Letovsky S, Milos PM, Thompson JF. (2) |
| 44 | Volkin E, Carter CE. (2) |
| 45 | Zhulidov PA, Bogdanova EA, Shcheglov AS, Vagner LL, Khaspekov GL, Kozhemyako VB, Matz MV, Meleshkevitch E, Moroz LL, Lukyanov SA, Shagin DA. |
| 46 | Zhulidov PA, Bogdanova EA, Shcheglov AS, Vagner LL, Khaspekov GL, Kozhemyako VB, Matz MV, Meleshkevitch E, Moroz LL, Lukyanov SA, Shagin DA. |
| 47 | Zhulidov PA, Bogdanova EA, Shcheglov AS, Shagina IA, Wagner LL, Khazpekov GL, Kozhemyako | VV, Lukyanov SA, Shagin DA. |
| 48 | Zhulidov PA, Bogdanova EA, Shcheglov AS, Shagina IA, Wagner LL, Khazpekov GL, Kozhemyako | VV, Lukyanov SA, Shagin DA. |
| 49 | Borodina T, Adjaye J., and Sultan M. (2) |
| 50 | Hansen et al. (2) |
| 51 | Levesque-Sergerie J-P, Duquette M, Thibault C, Delbecchi L, Bissonnette N. (2) |
| 52 | Levin J.Z., Ya***our M. , Adiconis X., et al. (2) |
| 53 | Okello et al. (2) |
| 54 | Roberts et al. (2) |
| 55 | Ståhlberg A, Kubista M, Pfaffl M. (2) |
| 56 | Zhu YY, Machleder EM, Chenchik A, Li R, Siebert PD. (2) |
| 57 | Glenn T.C. (2) |
| 58 | Liu L., Li Y., Li S., et al. (2) |
| 59 | M.L. Metzker M.L. (2) |
| 60 | Altschul, SF, W Gish, W Miller, EW Myers, DJ Lipman. (2) |
| 61 | Auer, PL, RW Doerge. (2) |
| 62 | Blanca, JM, L Pascual, P Ziarsolo, F Nuez, J Canizares. (2) |
| 63 | Brautigam, A, T Mullick, S Schliesky, AP Weber. (2) |
| 64 | Brown, CT, A Howe, Q Zhang, AB Pyrkosz, TH Brom (2) |
| 65 | Busby, MA, C Stewart, C Miller, K Grzeda, G Marth (2) |
| 66 | Camacho, C, G Coulouris, V Avagyan, N Ma, J Papadopoulos, K Bealer, TL Madden. (2) |
| 67 | Catchen, JM, A Amores, P Hohenlohe, W Cresko, JH Postlethwait (2) |
| 68 | Chevreux, B, T Pfisterer, B Drescher, AJ Driesel, WE Muller, T Wetter, S Suhai (2) |
| 69 | Chung, LM, JP Ferguson, W Zheng, F Qian, V Bruno, RR Montgomery, H Zhao (2) |
| 70 | c****, PJ, CJ Fields, N Goto, ML Heuer, PM Rice (2) |
| 71 | Compeau, PE, PA Pevzner, G Tesler (2) |
| 72 | Conesa, A, S Gotz, JM Garcia-Gomez, J Terol, M Talon, M Robles (2) |
| 73 | Di, Y, DW Schafer, JS c***bie, JH Chang (2) |
| 74 | Dillies, MA, A Rau, J Aubert, et al (2) |
| 75 | Fonseca, NA, J Rung, A Brazma, JC Marioni (2) |
| 76 | Francis, WR, LM Christianson, R Kiko, ML Powers, NC Shaner, SH Haddock (2) |
| 77 | Gillis, J, M Mistry, P Pavlidis (2) |
| 78 | Grabherr, MG, BJ Haas, M Ya***our, et al (2) |
| 79 | Hardcastle, TJ, KA Kelly (2) |
| 80 | Huang da, W, BT Sherman, RA Lempicki (2) |
| 81 | Huang, X, A Madan (2) |
| 82 | Kvam, VM, P Liu, Y Si (2) |
| 83 | Leng, N, JA Dawson, JA Thomson, V Ruotti, AI Rissman, BMG Smits, JD Haag, MN Gould, RM Stewart, C Kendziorski (2) |
| 84 | Li, H, B Handsaker, A Wysoker, T Fennell, J Ruan, N Homer, G Marth, G Abecasis, R Durbin, S Genome Project Data Processing (2) |
| 85 | Li, J, R Tibs***rani (2) |
| 86 | Li, J, DM Witten, IM Johnstone, R Tibs***rani (2) |
| 87 | Li, Z, Y Chen, D Mu, et al (2) |
| 88 | Lohse, M, AM Bolger, A Nagel, AR Fernie, JE Lunn, M St**t, B Usadel (2) |
| 89 | Love, MI, Huber, W, S Anders (2) |
| 90 | Lund, SP, D Nettleton, DJ McCarthy, GK Smyth (2) |
| 91 | Martin, JA, Z Wang (2) |
| 92 | Miller, JR, S Koren, G Sutton (2) |
| 93 | Mortazavi, A, BA Williams, K Mccue, L Schaeffer, B Wold (2) |
| 94 | Oshlack, A, MD Robinson, MD Young (2) |
| 95 | Pevzner, PA, H Tang, MS Waterman (2) |
| 96 | Robertson, G, J Schein, R Chiu, et al (2) |
| 97 | Robinson, MD, DJ McCarthy, GK Smyth (2) |
| 98 | Robinson, MD, A Oshlack (2) |
| 99 | Schulz, MH, DR Zerbino, M Vingron, E Birney (2) |
| 100 | Simpson, JT, K Wong, SD Jackman, JE Schein, SJ Jones, I Birol (2) |
| 101 | Smyth, GK (2) |
| 102 | Soneson, C, M Delorenzi (2) |
| 103 | Tarazona, S, F Garcia-Alcalde, J Dopazo, A Ferrer, A Conesa (2) |
| 104 | Trapnell, C, DG Hendrickson, M Sauvageau, L Goff, JL Rinn, L Pachter (2) |
| 105 | Van De Wiel, MA, GGR Leday, L Pardo, H Rue, AW Van Der Vaart, WN Van Wieringen (2) |
| 106 | Wang, LK, ZX Feng, X Wang, XW Wang, XG Zhang (2) |
| 107 | Yu, D, W Huber, O Vitek (2) |
| 108 | Zerbino, DR, E Birney (2) |
| 109 | Zhou, Y-H, K Xia, FA Wright (2) |
| No | Text |
| 1 | i.e. (6) |
| 2 | DGE experiments must be designed to accurately measure both the counts of each transcript and the variances that are a***ociated with those numbers. |
| 3 | Unless you are genuinely interested in comparing technical aspects of RNA-seq, or you expect technical variation to be especially great for a large majority of the target transcripts, we recommend greater resource allocation to biological replication. |
| 4 | differential expression studies using RNA-seq data need to be replicated in order to estimate within- and among-group variation |
| 5 | e.g. (13) |
| 6 | In practice many protocols actually combine both procedures. In this case, after adding appropriate amounts of alcohol to the aqueous phase from the phenol/chloroform extraction, it is further purified using a silica column. |
| 7 | However, this method alone will not accurately catch guanidinium and phenol contamination. |
| 8 | However, users that are working with non-model organisms should consult the manufacturer to verify that the capture oligos are compatible with the rRNA in their sample. |
| 9 | However, the manufacturer does not recommend this kit for RNA-seq. |
| 10 | E. coli (4) |
| 11 | de novo (17) |
| 12 | i |
| 13 | p |
| 14 | i = -10*log10(p) |
| 15 | i = -10*log10[p/(1-p)] |
| 16 | De novo |
| 17 | de Bruijn (8) |
| 18 | etc |
| 19 | etc. |
| 20 | Genome Biol (10) |
| 21 | Journal of the Royal Statistical Society Series B-Methodological (2) |
| 22 | BMC Bioinformatics (14) |
| 23 | Bioinformatics (22) |
| 24 | Nature methods. (4) |
| 25 | BMC Genomics (6) |
| 26 | Nat Biotech (4) |
| 27 | W.H. Freeman, New York. (2) |
| 28 | Journal of the Royal Statistical Society: Series B (Statistical Methodology) (2) |
| 29 | Anal Biochem (4) |
| 30 | Nat Protoc (4) |
| 31 | Comparative and functional genomics. (2) |
| 32 | Meth Enzymol (2) |
| 33 | Biochemical Journal (2) |
| 34 | Tag-based Next Generation Sequencing (2) |
| 35 | PLoS ONE (4) |
| 36 | J Am Chem Soc (2) |
| 37 | Nucleic Acids Res. (2) |
| 38 | Bioorg Khim. (2) |
| 39 | Methods in enzymology. (2) |
| 40 | Nucleic acids research. (2) |
| 41 | BMC Mol Biol (2) |
| 42 | Genome biology. (2) |
| 43 | Clin Chem (2) |
| 44 | BioTechniques (2) |
| 45 | Molecular ecology resources. (2) |
| 46 | Journal of biomedicine & biotechnology. (2) |
| 47 | Nature reviews Genetics. (2) |
| 48 | J Mol Biol (2) |
| 49 | J Exp Bot (2) |
| 50 | arXiv: (2) |
| 51 | G3: Genes, Genomes, Genetics (2) |
| 52 | Genome Res (10) |
| 53 | Nucleic Acids Res (4) |
| 54 | Nat Biotechnol (4) |
| 55 | Stat Appl Genet Mol Biol (6) |
| 56 | Brief Bioinform (2) |
| 57 | Nat. Protocols (2) |
| 58 | Am J Bot (2) |
| 59 | Stat Methods Med Res (2) |
| 60 | Biostatistics (4) |
| 61 | Brief Funct Genomics (2) |
| 62 | Genome Biology (2) |
| 63 | Nat Rev Genet 12:671-682 (2) |
| 64 | Genomics (2) |
| 65 | Nature Methods (2) |
| 66 | PNAS (2) |
| 67 | Nat Meth (2) |
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