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Table 1 The 29 genes (with two isoforms) used to compare the performance of RPiso and Ribomap

From: A tool for analyzing and visualizing ribo-seq data at the isoform level

Gene name isoform A versus isoform B Ribo-seq reads uniquely mapped to the unique exon of each isoform (by Bowtie): A versus B TL(A) versus TL(B) calculated by RPiso TL(A) versus TL(B) calculated by by Ribomap
ALG3 NM_005787 versus NM_001006941 91 versus 2 (A > B) 0.9 versus 0.01 (A > B) 110 versus 274 (A < B)
CNRIP1 NM_015463 versus NM_001111101 1 versus 0 (A > B) 0.01 versus 0 (A > B) 1 versus 2 (A < B)
COL5A1 NM_000093 versus NM_001278074 11 versus 0 (A > B) 0.69 versus 0 (A > B) 92 versus 1104 (A < B)
COQ6 NM_182476 versus NM_182480 9 versus 4 (A > B) 0.3 versus 0.11 (A > B) 12 versus 162 (A < B)
CRY2 NM_021117 versus NM_001127457 4 versus 0 (A > B) 0.06 versus 0 (A > B) 4 versus 30 (A < B)
EEF1E1 NM_001135650 versus NM_004280 124 versus 0 (A > B) 1.76 versus 0.6 (A > B) 135 versus 232 (A < B)
EGLN3 NM_022073 versus NM_001308103 30 versus 0 (A > B) 0.55 versus 0.02 (A > B) 22 versus 98 (A < B)
GALNT2 NM_004481 versus NM_001291866 181 versus 0 (A > B) 4.21 versus 0 (A > B) 234 versus 1926 (A < B)
KLF10 NM_005655 versus NM_001032282 53 versus 0 (A > B) 1.7 versus 0 (A > B) 89 versus 681 (A < B)
LCORL NM_001166139 versus NM_153686 22 versus 13 (A > B) 0.17 versus 0.15 (A > B) 31 versus 98 (A < B)
LIG3 NM_013975 versus NM_002311 57 versus 0 (A > B) 0.4 versus 0.01 (A > B) 65 versus 300 (A < B)
LRIG3 NM_153377 versus NM_001136051 9 versus 0 (A > B) 0.09 versus 0.04 (A > B) 17 versus 128 (A < B)
LRP5 NM_002335 versus NM_001291902 3 versus 0 (A > B) 0.46 versus 0 (A > B) 321 versus 338 (A < B)
LYSMD1 NM_001136543 versus NM_212551 7 versus 0 (A > B) 0.18 versus 0 (A > B) 7 versus 28 (A < B)
MAP1S NM_018174 versus NM_001308363 5 versus 0 (A > B) 0.15 versus 0 (A > B) 10 versus 135 (A < B)
MAT2B NM_013283 versus NM_182796 23 versus 0 (A > B) 3.61 versus 0 (A > B) 58 versus 1068 (A < B)
NAF1 NM_138386 versus NM_001128931 127 versus 0 (A > B) 1.2 versus 0 (A > B) 133 versus 406 (A < B)
NDUFA11 NM_175614 versus NM_001193375 28 versus 0 (A > B) 1.92 versus 0 (A > B) 29 versus 355 (A < B)
NSMAF NM_001144772 versus NM_003580 17 versus 13 (A > B) 0.11 versus 0.09 (A > B) 25 versus 167 (A < B)
NT5DC2 NM_001134231 versus NM_022908 62 versus 0 (A > B) 0.67 versus 0 (A > B) 62 versus 296 (A < B)
PPIL3 NM_130906 versus NM_032472 18 versus 0 (A > B) 0.59 versus 0 (A > B) 61 versus 75 (A < B)
PRKG1 NM_006258 versus NM_001098512 42 versus 0 (A > B) 0.2 versus 0 (A > B) 44 versus 77 (A < B)
RASA1 NM_002890 versus NM_022650 176 versus 0 (A > B) 0.45 versus 0 (A > B) 192 versus 321 (A < B)
RFC3 NM_002915 versus NM_181558 240 versus 0 (A > B) 2.01 versus 1.43 (A > B) 279 versus 808 (A < B)
RPS15 NM_001018 versus NM_001308226 22 versus 0 (A > B) 18.06 versus 0 (A > B) 24 versus 2482 (A < B)
CPD NM_001304 versus NM_001199775 9 versus 0 (A > B) 0.11 versus 0.52 (A < B) 640 versus 33 (A > B)
PPP2R2A NM_002717 versus NM_001177591 12 versus 0 (A > B) 0.44 versus 1.77 (A < B) 859 versus 39 (A > B)
RPL14 NM_001034996 versus NM_003973 3 versus 0 (A > B) 0.2 versus 65.57 (A < B) 12,815 versus 83 (A > B)
SUCLG2 NM_003848 versus NM_001177599 54 versus 0 (A > B) 0.41 versus 1.98 (A < B) 911 versus 16 (A > B)
  1. Take the gene ALG3 as an example. ALG3 has two isoforms (NM_005787 and NM_001006941). Each isoform has its unique exon. The unique exon of NM_005787 has much more Ribo-seq footprints (91 vs. 2 uniquely mapped reads) than the unique exon of NM_001006941 has. Therefore, the translational level (TL) of NM_005787 should be higher than that of NM_001006941. Our RPiso supports this assertion (0.9 vs. 0.01) while Ribomap contradicts this assertion (110 vs. 274). Therefore, our RPiso outperformed Ribomap in this case. In total, our RPiso outperformed Ribomap in 86% (25/29) of the cases (bold-faced names), suggesting that our RPiso estimates isoform abundance more accurately than Ribomap does