Check introns with unique specificities

Recheck list of risdi/brana-specific introns
Update, 20230308

Last updated: 2023-03-08

Checks: 6 1

Knit directory: 20211209_JingxinRNAseq/analysis/

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library(tidyverse)

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Recheck list of risdi/brana-specific introns

I previously made a list of risdiplam/branaplam/C2C5-specific introns based on the dose response experiment. Because the different molecules have different genome-wide effective potencies (ie, 100nM C2C5 is different than 100nM risdiplam, despite them having generally similar specificity profiles), I tested for a difference in the EC50 of each intron for each traitment pair, relative to the genome-wide median. You can see that in a previous notebook I plotted the dose-response datapoints for a random sample of 20 of these significant molecule-specific effects, and they are generally believable effects from those.

GA.GT.Introns <- read_tsv("../output/EC50Estimtes.FromPSI.txt.gz")

ColorKey <- c("Branaplam-specific"="#005A32", "Risdiplam-specific"="#084594", "Non significant"="#969696")

P1.dat <- GA.GT.Introns %>%
  mutate(Color = case_when(
    EC.Ratio.Test.Estimate.FDR_Branaplam.Risdiplam > 0.05 ~ "Non significant",
    ECRatio.ComparedToGenomewideMedian_Branaplam.Risdiplam > 1 ~ "Risdiplam-specific",
    ECRatio.ComparedToGenomewideMedian_Branaplam.Risdiplam < 1 ~ "Branaplam-specific"
  ))

ggplot(P1.dat, aes(x=ED50_Branaplam, y=ED50_Risdiplam, color=Color)) +
  geom_point() +
  scale_x_continuous(trans='log10', limits = c(1, 1E7)) +
  scale_y_continuous(trans='log10', limits = c(1, 1E7)) +
  scale_color_manual(values=ColorKey) +
  labs(x= "Branaplam\nED50 (nanomolar)", y= "Risdiplam\nED50 (nanomolar)", color=NULL) +
  theme(legend.position='bottom') +
  theme_bw()

Version	Author	Date
ea36e65	Benjmain Fair	2023-03-07

P1.dat %>%
  count(Color)

# A tibble: 4 × 2
  Color                  n
  <chr>              <int>
1 Branaplam-specific   240
2 Non significant      200
3 Risdiplam-specific   161
4 <NA>                2878

Ok, so each point is a branaplam-specific or risdiplam-specific GA-GT intron. There are 200 non-significant points, 161 risdiplam-specific points, and 240 branaplam-specific points. I think it will be useful for Jingxin to be able to easily visualize these before validating them… Some introns that change PSI from 1% to 3% might be very significant, but not the best for validation. Furthermore, not all of these events might be involved in poison exon inclusion. Some of them might just be alt 5’ss or something. And these details might inform which are the best candidates for validation by flanking PCR primers. Also, when looking at the data, some of the ‘risdiplam-specific’ introns I called are just not believable effects. Like the dose-response data points might just be too noisy. I did a reasonable job of filtering these out, and trying to make the FDR estimate reasonably calibrated… Or like there are some examples where it appears ‘risdiplam-specific’ but it is because the cryptic event is only just barely visible at the highest dose of risdiplam, and not visible in any of the branaplam doses (so it just requires a really really high dose to see the effect). So for all these reasons, it will be best to check the raw coverage data first… So I’ll write the out this list as a bedfile for easy viewing in IGV, a save a session that has the bedfile loaded, along with bigwigs for the dose response experiment so hopefully it will be easy to view.

P1.dat %>%
  dplyr::select(chrom=`#Chrom`, start, end, junc, score=ECRatio.ComparedToGenomewideMedian_Branaplam.Risdiplam, strand=strand.y, Color) %>%
  filter(!is.na(score)) %>%
  mutate(thickStart = start, thickEnd=end, Color=recode(Color, !!!ColorKey)) %>%
  mutate(RgbCol = apply(col2rgb(Color), 2, paste, collapse=',')) %>%
  dplyr::select(chrom:strand, thickStart, thickEnd, RgbCol) %>%
  arrange(chrom, start, end) %>%
  write_tsv("../code/Branaplam_Risdiplam_specific_introns.bed", col_names = F)

bgzip ../code/Branaplam_Risdiplam_specific_introns.bed
tabix -p bed ../code/Branaplam_Risdiplam_specific_introns.bed.gz

So to view, you will need to use the globus link I shared with Jingxin to download the code directory, or at minimum download the code/bigwigs folder of bigwig files, the code/tracks.xml IGV session, and the code/Branaplam_Risdiplam_specific_introns.bed.gz and code/Branaplam_Risdiplam_specific_introns.bed.gz.tbi. Then, from IGV, go to File >> OpenSession and open the tracks.xml. The tracks.xml uses relative filepaths so you need to preserve the relative filepaths of the thing you downloaded (that is, they need to all be in the same folder, such as a folder named code).

Now you should be able to select the Branaplam_Risdiplam_specific_introns.bed track, and Ctl-F or Ctl-B to jump to the next GA-GT introns, colored according to significance. Browse around to find coordinates of potential splice events for validation. Note that each bigwig is already normalized signal relative to library depth. With autoscaling for the y-axis turned on (the default), it may be visually obvious to see the poison exons, but it might not be totally obvious to see if there are effects on gene expression. To better visualize effects on host gene expression, I recommend just selecting all bigwig tracks and right-click to “group autoscale”. Since coverage of each track is already normalized by library size, it should be easy to visually interpret if there is a change in gene expression.

Here are screenshots of a few examples…

BranaSpecific1

BranaSpecific2

RisdiSpecific1

In general, I’m noticing there a quite a few believable branaplam-specific examples but the risdlam-specific are for the most part very small specificity effect sizes. That is, there are very few obviously risdiplam-specific events, compared to branaplam-specific events.

Let’s list the top risdi-specific introns in the following table:

P1.dat %>%
  arrange(desc(ECRatio.ComparedToGenomewideMedian_Branaplam.Risdiplam)) %>%
  head() %>%
  knitr::kable()

junc	#Chrom	start	end	gid	strand.y	seq	Donor.score	gene_names	gene_ids	SpliceDonor	UpstreamSpliceAcceptor	IntronType	Steepness	LowerLimit	UpperLimit	ED50_Branaplam	ED50_C2C5	ED50_Risdiplam	spearman.coef.Branaplam	spearman.coef.C2C5	spearman.coef.Risdiplam	EC.Ratio.Test.Estimate_Branaplam.C2C5	EC.Ratio.Test.Estimate_Branaplam.Risdiplam	EC.Ratio.Test.Estimate_C2C5.Risdiplam	ECRatio.ComparedToGenomewideMedian_Branaplam.C2C5	ECRatio.ComparedToGenomewideMedian_Branaplam.Risdiplam	ECRatio.ComparedToGenomewideMedian_C2C5.Risdiplam	EC.Ratio.Test.Estimate.P_Branaplam.C2C5	EC.Ratio.Test.Estimate.P_Branaplam.Risdiplam	EC.Ratio.Test.Estimate.P_C2C5.Risdiplam	EC.Ratio.Test.Estimate.FDR_Branaplam.C2C5	EC.Ratio.Test.Estimate.FDR_Branaplam.Risdiplam	EC.Ratio.Test.Estimate.FDR_C2C5.Risdiplam	Color
chr2:72179461:72182894:clu_4568_-	chr2	72179461	72182894	chr2_clu_4568_-	-	GAGAGTAAGTA	6.005894	EXOC6B	ENSG00000144036.16	chr2.72182894.-	chr2.72182903.-	Annotated	-2.7570544	3.1361062	31.384932	2.495499e+09	248.12468	785.0629479	0.2277339	0.5594024	0.9139077	1.005744e+07	3178724.1044	0.3160571	7.482724e+06	25547101.480	3.0610287	0.0000000	0.0000000	0.0000000	0.0000000	0.0000000	0.0000000	Risdiplam-specific
chr13:20404741:20405904:clu_25569_-	chr13	20404741	20405904	chr13_clu_25569_-	-	GAGAGTAAGTC	5.446634	CRYL1	ENSG00000165475.15	chr13.20405904.-	chr13.20405997.-	Alt 5’ss	-2.8191629	3.3431713	48.302244	1.641993e+09	1400.00395	4071.6117233	0.1740777	0.6024948	0.9128709	1.172849e+06	403278.4047	0.3438452	8.725985e+05	3241109.952	3.3301579	0.0000000	0.0000000	0.0000000	0.0000000	0.0000000	0.0000000	Risdiplam-specific
chr9:108931201:108933271:clu_18237_-	chr9	108931201	108933271	chr9_clu_18237_-	-	AAGAGTAAGCA	4.905988	ELP1	ENSG00000070061.15	chr9.108933271.-	chr9.108933405.-	Alt 5’ss	-9.6753286	0.5638888	7.339398	2.540583e+07	33.32162	895.8671341	0.1926687	0.9052038	0.7822166	7.624427e+05	28358.9229	0.0371948	5.672567e+05	227917.950	0.3602338	0.0000021	0.0000000	0.0000000	0.0000023	0.0000000	0.0000000	Risdiplam-specific
chr18:10773629:10774006:clu_33760_-	chr18	10773629	10774006	chr18_clu_33760_-	-	ATGAGTAAGTC	4.559120	PIEZO2	ENSG00000154864.12	chr18.10774006.-	chr18.10774036.-	Annotated	-2.2089456	0.0687500	51.453519	1.001587e+07	143.33677	1424.8728605	0.2738613	0.9128709	0.8416254	6.987650e+04	7029.3086	0.1005962	5.198805e+04	56493.880	0.9742791	0.0000000	0.0000000	0.4229854	0.0000000	0.0000000	0.6497405	Risdiplam-specific
chr19:10330526:10332870:clu_34319_-	chr19	10330526	10332870	chr19_clu_34319_-	-	GAGAGTACGCC	2.214523	RAVER1	ENSG00000161847.14	chr19.10332870.-	chr19.10332909.-	Alt 5’ss	-0.0000251	0.1685537	3.589164	1.413434e+03	22.81686	0.7759248	0.9831921	-0.2712254	-0.5135291	6.194690e+01	1821.6118	29.4060210	4.608844e+01	14640.120	284.7988165	0.9969948	0.9965823	0.9983501	0.4873920	0.4546814	1.0000000	Non significant
chr4:41014398:41032584:clu_10225_-	chr4	41014398	41032584	chr4_clu_10225_-	-	AGGAGTAGGTG	5.043083	APBB2	ENSG00000163697.17	chr4.41032584.-	chr4.41032626.-	Alt 5’ss	-3.0030040	0.0355949	1.682290	3.820296e+05	22.66113	452.1565311	0.3195048	0.8580987	0.9082951	1.685837e+04	844.9056	0.0501179	1.254261e+04	6790.426	0.4853942	0.0010952	0.0000000	0.0006567	0.0009786	0.0000000	0.0025582	Risdiplam-specific

After looking at some of the top risdiplam-specific hits from the list above, here is perhaps the most clear example:

RisdiSpecific2

Update, 20230308

Yang suggested I do some more exploring/filtering of the data a bit more to see if there are any introns and interesting host genes with reasonable differences in specificity between the risdiplam and branaplam treatments. So like HTT should show up here for example, but I wonder what other interesting genes may be on the list. I want to get a more useful/filtered list for Yang and Jingxin to browse

ColorKey <- c("Branaplam-specific"="#005A32", "Risdiplam-specific"="#084594", "Non significant"="#969696")


P.histogram <- P1.dat %>%
  mutate(Color = factor(Color, levels=names(ColorKey))) %>%
  ggplot(aes(x=log2(ECRatio.ComparedToGenomewideMedian_Branaplam.Risdiplam), fill=Color)) +
  geom_histogram() +
  scale_fill_manual(values=ColorKey) +
  theme(legend.position="bottom") +
  labs(x="Specificity\nlog2(BranaplamEC50/RisdiplamEC50)", caption="EC50s normalized to median before comparing ratios")

P.histogram

Version	Author	Date
a97c2eb	Benjmain Fair	2023-03-08

Let’s just consider stronger specificity effects, with abs(log2 ratio) > 2.

Note that I haven’t filtered these GA-GT intron affects for those with effects on the host gene. So like some of these hits may not effect host gene expression.

P.histogram +
  xlim(c(-10, 10)) +
  geom_vline(xintercept=c(-2,2))

Version	Author	Date
a97c2eb	Benjmain Fair	2023-03-08

SpecificEffects <- P1.dat %>%
  mutate(log2Ratio = log2(ECRatio.ComparedToGenomewideMedian_Branaplam.Risdiplam)) %>%
  filter(abs(log2Ratio)>2) %>%
  filter(!Color == "Non significant") %>%
  separate_rows(gene_names, gene_ids, sep=',') %>%
  dplyr::select(Color, log2Ratio, gene_names, gene_ids, junc) %>%
  # filter(gene_names == "HTT") %>%
  arrange(log2Ratio)

head(SpecificEffects)

# A tibble: 6 × 5
  Color              log2Ratio gene_names gene_ids           junc               
  <chr>                  <dbl> <chr>      <chr>              <chr>              
1 Branaplam-specific    -30.8  ASB3       ENSG00000115239.24 chr2:53765585:5378…
2 Branaplam-specific    -15.7  SETD5      ENSG00000168137.18 chr3:9468615:94704…
3 Branaplam-specific     -8.13 C8orf88    ENSG00000253250.3  chr8:90971594:9097…
4 Branaplam-specific     -7.52 NCF2       ENSG00000116701.15 chr1:183564030:183…
5 Branaplam-specific     -7.16 ANKRD10    ENSG00000088448.14 chr13:110905233:11…
6 Branaplam-specific     -6.67 DAPP1      ENSG00000070190.13 chr4:99841827:9985…

Let’s also merge this with some gene expression data. For convenience, I’m just going to merge it with the spearman of the dose:response effect on expression, and also gather the FoldChange at the mid-point dose, which I think is a reasonable place to start to see some effects (the high dose in this experiment might be a bit ridiculous from the pharmacology point of view).

gene_names <- read_tsv("../data/Genes.list.txt")

GeneExpressionData.tidy <- read_tsv("../code/DoseResponseData/LCL/TidyExpressionDoseData.txt.gz") %>%
  mutate(CPM = log2(CPM)) %>%
  mutate(ensembl_gene_id = str_replace(Geneid, "^(.+?)\\..*$", "\\1")) %>%
  left_join(gene_names)

As a data parsing side note… I can quickly get the doses for the midpoint doses by filtering on the color column. Let me remember how I coded the colors to get the appropriate doses

GeneExpressionData.tidy %>%
  distinct(color, .keep_all=T) %>%
  ggplot(aes(x=1, y=color, fill=color)) +
  geom_raster() +
  geom_label(aes(label=color)) +
  scale_fill_identity() +
  facet_wrap(~treatment)

Version	Author	Date
a97c2eb	Benjmain Fair	2023-03-08

Ok, so in other words, I want to filter for color = #969696 (DMSO), or #74C476 (middle branaplam dose), or #6BAED6 (middle risdiplam dose).

MoleculeSpecificEffects <- GeneExpressionData.tidy %>%
  filter(color %in% c("#74C476", "#6BAED6")) %>%
  filter(Geneid %in% SpecificEffects$gene_ids) %>%
  dplyr::select(Geneid, CPM, SampleName, treatment, spearman) %>%
  left_join(
    GeneExpressionData.tidy %>%
      filter(color %in% c("#969696")) %>%
      filter(Geneid %in% SpecificEffects$gene_ids) %>%
      dplyr::select(Geneid, CPM) %>%
      group_by(Geneid) %>%
      summarise(CPM_DMSO = mean(CPM))
  ) %>%
  mutate(Log2FoldChange = CPM - CPM_DMSO) %>%
  pivot_wider(names_from = c("treatment"), values_from=c("CPM", "spearman", "SampleName", "Log2FoldChange")) %>%
  inner_join(SpecificEffects, by=c("Geneid"="gene_ids")) %>%
  dplyr::rename(log2RatioOfSplicingED50= log2Ratio) %>%
  arrange(log2RatioOfSplicingED50)

MoleculeSpecificEffects %>%
  filter(gene_names == "HTT") %>%
  knitr::kable()

Geneid	CPM_DMSO	CPM_Branaplam	CPM_Risdiplam	spearman_Branaplam	spearman_Risdiplam	SampleName_Branaplam	SampleName_Risdiplam	Log2FoldChange_Branaplam	Log2FoldChange_Risdiplam	Color	log2RatioOfSplicingED50	gene_names	junc
ENSG00000197386.12	7.892803	4.910666	7.186162	-0.8333333	-0.8666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-2.982138	-0.7066416	Branaplam-specific	-3.346746	HTT	chr4:3213736:3213958:clu_9322_+

Ok that makes sense. Note that the CPM columns are actually log2CPM. We can see that HTT has a branaplam-specific effect.

Let’s print the full table…

So for this table I only considered ones where there is a significant difference in splicing ED50 between risdiplam and branaplam. Technically, I renormalized EC50 to the genomewide median ED50 for GA-GT introns since risdiplam and branaplam molar concentrations aren’t directly comparable even for STAT1. Then, I filtered for the stronger effects (with log2 ratio) magnitude greater than 2 (see histogram above with the 2 vertical lines). Then, in the table, I am also listing the effects on expression in branaplam and risdiplam… Because some of the GA-GT introns that get upregulated don’t actually effect host gene expression, like if they don’t create an NMD poison exon. Note that all the CPM values in the table are actually log2CPM.

Then, in the table there is also a column called “spearman_Branaplam” or “spearman_Risdiplam” which is the expression dose:response speraman correlation across the whole titration series… so in the example of HTT which is on the table (and also above), you can see that there is a similarly strong negative spearman correlation coefficient in the risdiplam and branaplam, but the log2RatioOfSplicingED50 column suggests it is quite branaplam specific, and if you look at the CPM_Branaplam (100nM branaplam) column compared to the CPM_DMSO and CPM_Risdiplam (316nM risdiplam) columns, you can see that there really is only a strong expression effect in branaplam at that midpoint dose… The midpoint dose is roughly comparable to some of the relatively low doses that Jingxin used in the recent experiment of 52 molecules

MoleculeSpecificEffects %>%
  knitr::kable()

Geneid	CPM_DMSO	CPM_Branaplam	CPM_Risdiplam	spearman_Branaplam	spearman_Risdiplam	SampleName_Branaplam	SampleName_Risdiplam	Log2FoldChange_Branaplam	Log2FoldChange_Risdiplam	Color	log2RatioOfSplicingED50	gene_names	junc
ENSG00000115239.24	4.3081982	4.1890728	4.3196633	-0.8166667	0.9000000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.1191255	0.0114651	Branaplam-specific	-30.837171	ASB3	chr2:53765585:53782217:clu_4400_-
ENSG00000168137.18	6.0661148	6.1276722	6.2102237	-0.0166667	0.6333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0615575	0.1441089	Branaplam-specific	-15.702685	SETD5	chr3:9468615:9470459:clu_6956_+
ENSG00000253250.3	2.5719371	2.9005508	2.5340035	0.8000000	0.5166667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.3286136	-0.0379337	Branaplam-specific	-8.128940	C8orf88	chr8:90971594:90978579:clu_16756_-
ENSG00000116701.15	5.4192338	5.5229186	5.5790500	-0.4000000	-0.1333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.1036848	0.1598162	Branaplam-specific	-7.515091	NCF2	chr1:183564030:183565154:clu_1624_-
ENSG00000088448.14	5.0353703	4.9280315	5.1069535	-0.2500000	0.8000000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.1073388	0.0715831	Branaplam-specific	-7.155299	ANKRD10	chr13:110905233:110906033:clu_25920_-
ENSG00000070190.13	5.7763049	4.3533232	3.9080913	-0.9666667	-0.9000000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-1.4229816	-1.8682135	Branaplam-specific	-6.669824	DAPP1	chr4:99841827:99853218:clu_9719_+
ENSG00000050748.17	5.2584252	5.3263748	5.3632371	-0.5333333	0.5500000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0679496	0.1048119	Branaplam-specific	-6.577305	MAPK9	chr5:180250701:180261684:clu_12460_-
ENSG00000196792.12	3.7273769	4.0174847	4.0453431	0.9500000	0.8833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.2901078	0.3179662	Branaplam-specific	-6.202894	STRN3	chr14:30919106:30929201:clu_26459_-
ENSG00000170476.16	8.4436025	8.1173012	8.3130122	-1.0000000	-0.9500000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.3263014	-0.1305903	Branaplam-specific	-5.524008	MZB1	chr5:139388131:139388461:clu_12222_-
ENSG00000064933.18	4.6810344	2.2646238	2.5518368	-0.9833333	-1.0000000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-2.4164106	-2.1291976	Branaplam-specific	-5.522988	PMS1	chr2:189818829:189843964:clu_6477_+
ENSG00000087460.25	10.2499857	10.0997995	10.1649180	-0.9333333	-0.9166667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.1501862	-0.0850677	Branaplam-specific	-4.958655	GNAS	chr20:58895684:58898941:clu_37372_+
ENSG00000180198.16	7.0524244	9.6440401	7.2642243	0.9833333	0.9166667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	2.5916157	0.2117999	Branaplam-specific	-4.819941	RCC1	chr1:28508901:28529858:clu_2419_+
ENSG00000242125.3	4.9287895	3.2413027	4.5095734	-0.9833333	-0.9666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-1.6874868	-0.4192161	Branaplam-specific	-4.819941	SNHG3	chr1:28508901:28529858:clu_2419_+
ENSG00000112739.17	6.2932301	6.3802628	6.2891568	-0.4333333	-0.2333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0870327	-0.0040733	Branaplam-specific	-4.813817	PRPF4B	chr6:4021466:4027691:clu_12493_+
ENSG00000205861.12	0.9774978	1.2937702	0.5553771	-0.1833333	-0.7500000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.3162724	-0.4221207	Branaplam-specific	-4.744962	PCOTH	chr13:23889553:23890000:clu_25976_+
ENSG00000131981.16	5.6559843	5.6235088	5.7031307	0.2333333	0.7666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0324755	0.0471464	Branaplam-specific	-4.693610	LGALS3	chr14:55129647:55137370:clu_27175_+
ENSG00000078747.15	6.1734625	5.7468173	6.1599485	-0.8666667	-0.6666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.4266451	-0.0135139	Branaplam-specific	-4.614054	ITCH	chr20:34392914:34393791:clu_37125_+
ENSG00000258724.1	-Inf	-6.1574410	-Inf	-0.1980295	0.2738613	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	Inf	NaN	Branaplam-specific	-4.608812	PINX1	chr8:10765916:10820210:clu_16442_-
ENSG00000254093.9	3.9415665	3.6255573	3.8983668	-0.9833333	-0.6666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.3160092	-0.0431996	Branaplam-specific	-4.608812	PINX1	chr8:10765916:10820210:clu_16442_-
ENSG00000143569.19	7.7077429	7.2917077	7.0205834	-0.8666667	-0.9500000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.4160352	-0.6871596	Branaplam-specific	-4.586487	UBAP2L	chr1:154262202:154263103:clu_3309_+
ENSG00000102921.8	6.1395411	6.0907831	6.1279102	0.3666667	0.0666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0487579	-0.0116309	Branaplam-specific	-4.428989	N4BP1	chr16:48562444:48570182:clu_30578_-
ENSG00000100368.14	3.9931320	3.6222784	3.9677602	-0.9000000	-0.3833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.3708536	-0.0253719	Branaplam-specific	-4.411832	CSF2RB	chr22:36934738:36935351:clu_38681_+
ENSG00000111237.19	5.9226823	5.1901804	5.8840081	-1.0000000	-0.6666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.7325019	-0.0386742	Branaplam-specific	-4.338322	VPS29	chr12:110498859:110499535:clu_24109_-
ENSG00000172175.15	6.6152367	6.9167005	6.7481051	-0.1333333	0.3833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.3014638	0.1328683	Branaplam-specific	-4.278250	MALT1	chr18:58747300:58747405:clu_33627_+
ENSG00000010270.13	5.7620132	5.9089846	5.7548570	0.9333333	0.8333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.1469714	-0.0071562	Branaplam-specific	-4.248940	STARD3NL	chr7:38184562:38207447:clu_15662_+
ENSG00000090372.15	6.0804844	4.2989135	5.9960428	-0.9333333	-0.9333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-1.7815710	-0.0844417	Branaplam-specific	-4.199628	STRN4	chr19:46733236:46733807:clu_34931_-
ENSG00000176531.10	3.2001713	3.5516429	3.4279162	0.9000000	0.8000000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.3514715	0.2277449	Branaplam-specific	-4.154132	PHLDB3	chr19:43487123:43497118:clu_34828_-
ENSG00000000938.13	5.4668031	4.9207099	5.3181011	-0.5000000	-0.5000000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.5460932	-0.1487020	Branaplam-specific	-3.990816	FGR	chr1:27619173:27621559:clu_435_-
ENSG00000147905.17	5.5084515	5.2834282	5.3798056	-0.9500000	-0.2333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.2250233	-0.1286460	Branaplam-specific	-3.951407	ZCCHC7	chr9:37331433:37349357:clu_18867_+
ENSG00000153914.16	5.3992150	3.2561870	5.0795539	-0.8833333	-0.7833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-2.1430280	-0.3196611	Branaplam-specific	-3.940037	SREK1	chr5:66158230:66158809:clu_11012_+
ENSG00000101639.18	4.9258571	5.0520124	4.8327785	-0.4333333	-0.8166667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.1261553	-0.0930786	Branaplam-specific	-3.934320	CEP192	chr18:13038579:13040830:clu_33475_+
ENSG00000163960.12	5.5158041	5.7377556	5.6465791	0.5666667	0.4500000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.2219515	0.1307750	Branaplam-specific	-3.872331	UBXN7	chr3:196393619:196407246:clu_9186_-
ENSG00000106268.15	4.9628095	5.2294993	5.0653461	0.4833333	-0.5833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.2666898	0.1025367	Branaplam-specific	-3.805406	NUDT1	chr7:2242975:2244563:clu_15466_+
ENSG00000102897.10	4.5736910	4.8807922	4.4613245	-0.1500000	-0.0500000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.3071011	-0.1123666	Branaplam-specific	-3.734031	LYRM1	chr16:20900889:20902486:clu_29410_+
ENSG00000110090.13	4.8495802	5.0761787	4.9416200	0.4666667	0.5333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.2265985	0.0920398	Branaplam-specific	-3.648140	CPT1A	chr11:68759661:68760256:clu_21705_-
ENSG00000134882.16	5.1507778	4.3414083	4.6378393	-0.9833333	-0.9833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.8093695	-0.5129385	Branaplam-specific	-3.622183	UBAC2	chr13:99237454:99238427:clu_26229_+
ENSG00000171530.14	6.4857089	5.8097853	6.3302933	-0.9666667	-0.3833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.6759236	-0.1554156	Branaplam-specific	-3.621325	TBCA	chr5:77708347:77774185:clu_11981_-
ENSG00000147439.13	5.1520551	5.0749800	5.0856878	-0.8833333	0.4833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0770752	-0.0663673	Branaplam-specific	-3.615688	BIN3	chr8:22636962:22643652:clu_16481_-
ENSG00000177565.18	5.4283368	5.4312737	5.6095957	-0.6666667	0.1000000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0029369	0.1812589	Branaplam-specific	-3.588868	TBL1XR1	chr3:177098541:177147522:clu_9068_-
ENSG00000064313.12	5.4381021	4.5840260	4.3196633	-0.8000000	-0.9000000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.8540761	-1.1184388	Branaplam-specific	-3.576764	TAF2	chr8:119744393:119744881:clu_16886_-
ENSG00000167491.17	6.6118164	6.6513222	6.6583563	-0.7166667	0.5000000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0395057	0.0465399	Branaplam-specific	-3.547966	GATAD2A	chr19:19474167:19492306:clu_35739_+
ENSG00000080845.17	5.4454116	5.1250684	5.3773074	-0.8166667	0.6333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.3203432	-0.0681042	Branaplam-specific	-3.535267	DLGAP4	chr20:36499321:36499588:clu_37170_+
ENSG00000151233.11	4.0694815	2.9167005	4.0148087	-0.9833333	-0.6833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-1.1527810	-0.0546728	Branaplam-specific	-3.487187	GXYLT1	chr12:42087947:42095151:clu_23541_-
ENSG00000139116.18	5.2251809	5.1192651	5.2784859	-0.7166667	-0.5000000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.1059158	0.0533050	Branaplam-specific	-3.473336	KIF21A	chr12:39370261:39441962:clu_23535_-
ENSG00000108061.12	6.6597812	6.5503495	6.4688532	0.0666667	-0.6333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.1094316	-0.1909279	Branaplam-specific	-3.422720	SHOC2	chr10:110952323:110964125:clu_20120_+
ENSG00000130475.14	4.8883909	4.7554484	4.8709263	-0.9833333	0.3000000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.1329426	-0.0174646	Branaplam-specific	-3.391896	FCHO1	chr19:17772714:17774239:clu_35675_+
ENSG00000166974.13	5.3297854	5.5865519	5.3556426	-0.1500000	0.9333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.2567665	0.0258572	Branaplam-specific	-3.348989	MAPRE2	chr18:35135191:35140295:clu_33544_+
ENSG00000197386.12	7.8928033	4.9106655	7.1861617	-0.8333333	-0.8666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-2.9821378	-0.7066416	Branaplam-specific	-3.346746	HTT	chr4:3213736:3213958:clu_9322_+
ENSG00000127554.13	4.9440687	4.9929410	5.0031897	-0.6666667	0.3333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0488723	0.0591209	Branaplam-specific	-3.315597	GFER	chr16:1985262:1985866:clu_29158_+
ENSG00000180901.11	5.3235507	5.3641595	5.4693225	-0.5833333	0.4500000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0406088	0.1457718	Branaplam-specific	-3.297018	KCTD2	chr17:75060221:75062120:clu_33161_+
ENSG00000132394.11	4.7444785	4.9776270	4.9637693	-0.4666667	-0.2333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.2331485	0.2192908	Branaplam-specific	-3.285066	EEFSEC	chr3:128391145:128408069:clu_7629_+
ENSG00000107263.18	7.7481426	8.0216906	7.9613528	0.9333333	0.9666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.2735480	0.2132102	Branaplam-specific	-3.249082	RAPGEF1	chr9:131643417:131647635:clu_18483_-
ENSG00000135363.12	4.3804710	4.2886085	4.4726029	-0.3166667	-0.0333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0918626	0.0921319	Branaplam-specific	-3.238942	LMO2	chr11:33864817:33866992:clu_21326_-
ENSG00000156642.17	5.8592412	5.9143566	5.8188535	0.9000000	0.6333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0551154	-0.0403877	Branaplam-specific	-3.206832	NPTN	chr15:73592137:73597022:clu_28832_-
ENSG00000126581.13	6.1942389	6.4487329	6.2525491	0.9833333	0.8333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.2544940	0.0583102	Branaplam-specific	-3.183238	BECN1	chr17:42810928:42811292:clu_31645_-
ENSG00000196843.17	6.6276038	6.6349427	6.6359595	-0.0166667	0.5666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0073389	0.0083558	Branaplam-specific	-3.167849	ARID5A	chr2:96549459:96549753:clu_6009_+
ENSG00000285733.1	-Inf	-Inf	-Inf	NA	NA	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	NaN	NaN	Branaplam-specific	-3.141239	AL031315.1	chr6:169660766:169661703:clu_14487_-
ENSG00000184465.16	0.7275724	0.3019907	0.5411633	-0.9166667	-0.5166667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.4255818	-0.1864092	Branaplam-specific	-3.141239	WDR27	chr6:169660766:169661703:clu_14487_-
ENSG00000100281.14	4.6081853	4.5670729	4.6862757	-0.8333333	-0.6000000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0411124	0.0780904	Branaplam-specific	-3.090861	HMGXB4	chr22:35267514:35283962:clu_38658_+
ENSG00000136732.16	6.2975339	6.1987359	6.1234450	-0.8500000	-0.6333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0987981	-0.1740889	Branaplam-specific	-3.077982	GYPC	chr2:126663569:126690255:clu_6174_+
ENSG00000126773.13	5.1310343	5.0410041	5.1415178	0.1500000	0.6833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0900302	0.0104835	Branaplam-specific	-3.013184	PCNX4	chr14:60124310:60125637:clu_27223_+
ENSG00000204899.6	4.8599721	4.6337219	4.8393279	-0.9333333	-0.6833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.2262502	-0.0206442	Branaplam-specific	-2.991499	MZT1	chr13:72719097:72725642:clu_25814_-
ENSG00000163875.15	5.4606052	5.3918624	5.4006212	-0.7833333	0.4833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0687428	-0.0599841	Branaplam-specific	-2.964981	MEAF6	chr1:37493814:37494140:clu_580_-
ENSG00000116473.14	7.6765605	7.6621394	7.5971973	-0.4500000	-0.8666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0144210	-0.0793632	Branaplam-specific	-2.956315	RAP1A	chr1:111627526:111691334:clu_3075_+
ENSG00000106028.11	6.8109793	6.0446829	6.7728359	-0.9333333	-0.7500000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.7662965	-0.0381434	Branaplam-specific	-2.948600	SSBP1	chr7:141741459:141742169:clu_16288_+
ENSG00000278845.5	6.0796456	6.1821307	6.0841568	0.9166667	0.7333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.1024851	0.0045111	Branaplam-specific	-2.928467	MRPL45	chr17:38312661:38318687:clu_32705_+
ENSG00000175220.12	5.6868493	5.2503579	5.8641623	-0.9000000	-0.2333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.4364914	0.1773130	Branaplam-specific	-2.885549	ARHGAP1	chr11:46696156:46697021:clu_21372_-
ENSG00000113558.19	6.6634023	6.1644871	6.6943265	-0.9833333	-0.3333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.4989152	0.0309241	Branaplam-specific	-2.876467	SKP1	chr5:134174514:134175284:clu_12180_-
ENSG00000272772.1	-Inf	-Inf	-5.1170482	-0.1369306	-0.1460593	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	NaN	Inf	Branaplam-specific	-2.876467	AC104109.3	chr5:134174514:134175284:clu_12180_-
ENSG00000138185.20	7.9964849	8.0054224	7.9008041	-0.3500000	-0.1500000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0089375	-0.0956808	Branaplam-specific	-2.835834	ENTPD1	chr10:95756776:95823237:clu_19972_+
ENSG00000118454.13	4.8260367	4.6132229	4.9503861	-0.9500000	0.1166667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.2128138	0.1243494	Branaplam-specific	-2.807663	ANKRD13C	chr1:70270956:70274781:clu_878_-
ENSG00000165025.15	7.1479192	7.0854354	7.2593485	-0.9666667	-0.5333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0624838	0.1114293	Branaplam-specific	-2.803027	SYK	chr9:90826767:90843858:clu_18994_+
ENSG00000126653.18	4.8593663	4.6659263	4.8114702	-0.9166667	0.4333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.1934400	-0.0478962	Branaplam-specific	-2.798763	NSRP1	chr17:30183823:30184615:clu_32603_+
ENSG00000065150.21	8.3889944	8.4050400	8.3266076	-0.4166667	-0.7166667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0160456	-0.0623867	Branaplam-specific	-2.785237	IPO5	chr13:97985520:97989062:clu_26220_+
ENSG00000197150.12	5.2848027	4.8937680	5.4143332	-0.9000000	0.4500000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.3910347	0.1295306	Branaplam-specific	-2.783347	ABCB8	chr7:151031291:151032844:clu_16345_+
ENSG00000117419.16	5.3792829	5.4247010	5.3474975	-0.6666667	0.1333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0454181	-0.0317854	Branaplam-specific	-2.762573	ERI3	chr1:44313228:44318141:clu_682_-
ENSG00000112851.14	6.0480217	5.4251715	6.1021203	-0.9333333	-0.5666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.6228502	0.0540986	Branaplam-specific	-2.751726	ERBIN	chr5:66051538:66053406:clu_11009_+
ENSG00000139826.6	4.2150254	4.1879643	4.1141730	-0.6833333	0.5166667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0270611	-0.1008524	Branaplam-specific	-2.748700	ABHD13	chr13:108218659:108221329:clu_26257_+
ENSG00000130818.12	2.6949993	3.2434385	2.7686482	0.9166667	0.7500000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.5484392	0.0736488	Branaplam-specific	-2.737337	ZNF426	chr19:9533966:9534239:clu_34286_-
ENSG00000197329.12	5.5318634	5.2577726	5.5384825	0.1500000	0.6000000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.2740908	0.0066191	Branaplam-specific	-2.734313	PELI1	chr2:64108379:64112563:clu_4503_-
ENSG00000170627.11	4.8964738	3.2305763	4.4556520	-0.9500000	-0.9833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-1.6658975	-0.4408218	Branaplam-specific	-2.732351	GTSF1	chr12:54463297:54468825:clu_23735_-
ENSG00000125991.19	7.2077209	7.2163758	7.2842313	0.6500000	0.8000000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0086549	0.0765104	Branaplam-specific	-2.711622	ERGIC3	chr20:35554386:35555044:clu_37148_+
ENSG00000070882.13	5.1022965	5.0162362	5.1308793	-0.8500000	-0.2833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0860603	0.0285828	Branaplam-specific	-2.711605	OSBPL3	chr7:24892621:24898513:clu_14672_-
ENSG00000082146.13	4.0901520	4.3404109	4.0850756	-0.4166667	0.2666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.2502589	-0.0050764	Branaplam-specific	-2.667072	STRADB	chr2:201471111:201472955:clu_6553_+
ENSG00000101109.12	7.1971436	7.1499022	7.3565307	0.2500000	0.5166667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0472414	0.1593871	Branaplam-specific	-2.666348	STK4	chr20:44979965:44981829:clu_37255_+
ENSG00000197150.12	5.2848027	4.8937680	5.4143332	-0.9000000	0.4500000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.3910347	0.1295306	Branaplam-specific	-2.631513	ABCB8	chr7:151031291:151033605:clu_16345_+
ENSG00000100852.13	4.0440229	4.2487641	4.1201617	0.2333333	0.4666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.2047412	0.0761389	Branaplam-specific	-2.547770	ARHGAP5	chr14:32150566:32152423:clu_27094_+
ENSG00000060237.17	7.9237791	8.0417713	8.0869115	-0.7166667	0.5333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.1179922	0.1631324	Branaplam-specific	-2.540969	WNK1	chr12:895196:896071:clu_24436_+
ENSG00000180628.15	6.6337140	6.8000239	6.7122781	0.8333333	0.6166667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.1663099	0.0785641	Branaplam-specific	-2.539899	PCGF5	chr10:91236063:91240484:clu_19925_+
ENSG00000120029.13	5.5698725	5.5713299	5.5790500	-0.6833333	-0.5833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0014574	0.0091774	Branaplam-specific	-2.535363	ARMH3	chr10:101847620:101848400:clu_20869_-
ENSG00000185009.12	6.6747080	6.5325570	6.6298859	-0.9000000	-0.5833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.1421510	-0.0448221	Branaplam-specific	-2.534809	AP3M1	chr10:74124524:74126126:clu_20670_-
ENSG00000106785.15	6.4574479	6.0040059	6.5449525	-0.9833333	0.8333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.4534420	0.0875046	Branaplam-specific	-2.522308	TRIM14	chr9:98095029:98095320:clu_18214_-
ENSG00000170627.11	4.8964738	3.2305763	4.4556520	-0.9500000	-0.9833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-1.6658975	-0.4408218	Branaplam-specific	-2.494362	GTSF1	chr12:54465167:54468825:clu_23735_-
ENSG00000182628.13	5.7537633	5.5277458	5.6078919	-0.9500000	-0.8333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.2260175	-0.1458715	Branaplam-specific	-2.465174	SKA2	chr17:59112345:59119396:clu_31885_-
ENSG00000116212.15	5.1342687	5.1684266	5.0390349	-0.5500000	-0.8833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0341580	-0.0952338	Branaplam-specific	-2.458638	LRRC42	chr1:53947981:53951986:clu_2767_+
ENSG00000154511.12	5.1856157	4.8842182	4.9868952	-0.9833333	-0.7666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.3013975	-0.1987205	Branaplam-specific	-2.435005	DIPK1A	chr1:92876430:92907900:clu_992_-
ENSG00000100979.15	3.3330269	3.2667253	3.2048799	0.6500000	0.7833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0663015	-0.1281470	Branaplam-specific	-2.429309	PLTP	chr20:45910070:45911152:clu_36765_-
ENSG00000116353.16	4.2802065	3.8425590	4.3165372	-0.9000000	-0.7333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.4376474	0.0363308	Branaplam-specific	-2.415464	MECR	chr1:29206905:29211124:clu_462_-
ENSG00000165406.16	5.7545129	5.8927478	5.8762440	-0.4333333	0.8833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.1382349	0.1217311	Branaplam-specific	-2.413024	MARCHF8	chr10:45533289:45534787:clu_20491_-
ENSG00000115084.15	3.5913508	3.6849094	3.9341607	-0.6166667	0.4666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0935586	0.3428099	Branaplam-specific	-2.381796	SLC35F5	chr2:113725537:113728025:clu_4856_-
ENSG00000178397.13	-Inf	-Inf	-6.1170482	NA	0.1369306	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	NaN	Inf	Branaplam-specific	-2.381226	FAM220A	chr7:6331235:6347587:clu_14603_-
ENSG00000286075.1	-Inf	-Inf	-Inf	NA	NA	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	NaN	NaN	Branaplam-specific	-2.381226	AC009412.1	chr7:6331235:6347587:clu_14603_-
ENSG00000147586.10	3.5316801	3.5007705	3.6692214	-0.7833333	-0.8500000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0309096	0.1375413	Branaplam-specific	-2.342313	MRPS28	chr8:79940504:80002999:clu_16719_-
ENSG00000276418.5	-Inf	-6.1574410	-4.5320857	0.4500000	-0.3333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	Inf	Inf	Branaplam-specific	-2.342313	AC036214.3	chr8:79940504:80002999:clu_16719_-
ENSG00000196295.12	1.7486049	1.5840260	1.9436477	-0.9333333	0.3166667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.1645788	0.1950428	Branaplam-specific	-2.297164	GARS1-DT	chr7:30585479:30586244:clu_14706_-
ENSG00000008018.9	7.6105603	6.4940593	7.6388825	-0.9833333	-0.1833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-1.1165011	0.0283222	Branaplam-specific	-2.280594	PSMB1	chr6:170543730:170544321:clu_14498_-
ENSG00000181007.9	1.9254386	2.3019907	1.8885763	0.8500000	0.8833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.3765520	-0.0368623	Branaplam-specific	-2.275857	ZFP82	chr19:36394110:36400285:clu_34677_-
ENSG00000064652.11	1.3213263	1.2604116	1.4679143	-0.4333333	0.1500000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0609147	0.1465880	Branaplam-specific	-2.260318	SNX24	chr5:122898236:122936734:clu_11310_+
ENSG00000141068.14	5.8475194	6.0987677	6.1482738	0.6333333	0.3666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.2512483	0.3007544	Branaplam-specific	-2.252941	KSR1	chr17:27608630:27609196:clu_32556_+
ENSG00000189091.13	8.2776651	8.4029516	8.4148206	-0.5666667	-0.4666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.1252865	0.1371555	Branaplam-specific	-2.251402	SF3B3	chr16:70544249:70544438:clu_29930_+
ENSG00000026751.17	9.1854115	8.8787327	8.9119370	-0.3000000	-0.0666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.3066789	-0.2734746	Branaplam-specific	-2.246607	SLAMF7	chr1:160751423:160752186:clu_3431_+
ENSG00000122359.18	7.6498416	6.2896423	7.5345641	-0.9666667	-0.9500000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-1.3601993	-0.1152775	Branaplam-specific	-2.240435	ANXA11	chr10:80155912:80156378:clu_20706_-
ENSG00000113719.16	7.5501986	7.5005473	7.4881998	-0.8500000	0.1333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0496512	-0.0619988	Branaplam-specific	-2.233131	ERGIC1	chr5:172837337:172888699:clu_11596_+
ENSG00000138698.15	5.4944600	5.6202253	5.4513830	-0.4500000	-0.7833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.1257654	-0.0430770	Branaplam-specific	-2.220561	RAP1GDS1	chr4:98328826:98343139:clu_9700_+
ENSG00000189091.13	8.2776651	8.4029516	8.4148206	-0.5666667	-0.4666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.1252865	0.1371555	Branaplam-specific	-2.209715	SF3B3	chr16:70527429:70528873:clu_29929_+
ENSG00000115840.14	5.5526802	4.9379561	5.5799193	-0.9666667	-0.1500000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.6147242	0.0272391	Branaplam-specific	-2.208868	SLC25A12	chr2:171787947:171790741:clu_5068_-
ENSG00000167081.18	5.3475640	5.0713777	5.1798680	-0.9000000	-0.9166667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.2761862	-0.1676960	Branaplam-specific	-2.197212	PBX3	chr9:125964198:125965831:clu_19202_+
ENSG00000180104.16	6.1625641	5.4927133	6.2344432	-0.9500000	-0.6666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.6698509	0.0718791	Branaplam-specific	-2.126322	EXOC3	chr5:466552:466727:clu_10796_+
ENSG00000134852.15	3.8881696	3.8964849	3.8645191	0.0000000	0.7166667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0083154	-0.0236505	Branaplam-specific	-2.103294	CLOCK	chr4:55482828:55484224:clu_10284_-
ENSG00000117228.10	6.2113174	6.2289605	6.3039646	0.8000000	0.8833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0176431	0.0926473	Branaplam-specific	-2.094464	GBP1	chr1:89063253:89064701:clu_961_-
ENSG00000176407.18	6.1227173	6.0800678	6.1379803	0.7166667	0.3666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0426495	0.0152631	Branaplam-specific	-2.092161	KCMF1	chr2:85034167:85035016:clu_5943_+
ENSG00000142634.13	7.3680775	7.5167513	7.6087441	-0.3333333	0.0500000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.1486738	0.2406666	Branaplam-specific	-2.086733	EFHD2	chr1:15426830:15427150:clu_2238_+
ENSG00000234127.9	7.2326711	7.3382892	7.3170587	1.0000000	0.9833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.1056181	0.0843876	Branaplam-specific	-2.073400	TRIM26	chr6:30201138:30203828:clu_13671_-
ENSG00000047621.12	4.8199364	4.5481914	4.6830428	-0.9166667	-0.7166667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.2717450	-0.1368936	Branaplam-specific	-2.068560	C12orf4	chr12:4536219:4537380:clu_23341_-
ENSG00000146757.14	4.2245115	4.2927393	3.9940874	0.7000000	0.0333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0682278	-0.2304240	Branaplam-specific	-2.056343	ZNF92	chr7:65390943:65398341:clu_15756_+
ENSG00000172469.16	5.5678175	5.2116111	5.3902509	-0.9500000	-0.7333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.3562064	-0.1775666	Branaplam-specific	-2.016101	MANEA	chr6:95581911:95586402:clu_13187_+
ENSG00000185920.16	4.0582967	4.2551289	4.3434077	0.3000000	0.6333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.1968322	0.2851109	Branaplam-specific	-2.013666	PTCH1	chr9:95447451:95447869:clu_18182_-
ENSG00000107290.14	7.5088671	7.1713742	7.3764320	-0.7500000	-0.7333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.3374929	-0.1324351	Risdiplam-specific	2.002415	SETX	chr9:132281574:132283219:clu_18490_-
ENSG00000123983.14	6.1040022	5.9942099	6.0578775	-0.8666667	-0.7333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.1097923	-0.0461247	Risdiplam-specific	2.015697	ACSL3	chr2:222878159:222887830:clu_6716_+
ENSG00000115415.20	10.4388782	9.7878886	9.3949206	-0.9333333	-0.9500000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.6509896	-1.0439576	Risdiplam-specific	2.103504	STAT1	chr2:190977025:190978528:clu_5141_-
ENSG00000100485.12	4.5238499	4.4526611	3.8429537	-0.7833333	-0.8500000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0711888	-0.6808962	Risdiplam-specific	2.140344	SOS2	chr14:50130762:50133808:clu_26550_-
ENSG00000160293.17	6.2055016	6.4723710	6.3220035	-0.2333333	-0.1500000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.2668694	0.1165019	Risdiplam-specific	2.252860	VAV2	chr9:133833378:133834272:clu_18541_-
ENSG00000256646.7	-Inf	-Inf	-Inf	-0.2738613	-0.2008316	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	NaN	NaN	Risdiplam-specific	2.261174	AC010132.3	chr7:42927459:42927968:clu_14760_-
ENSG00000106588.11	2.4132009	2.1824090	2.4939766	0.4333333	-0.0500000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.2307919	0.0807756	Risdiplam-specific	2.261174	PSMA2	chr7:42927459:42927968:clu_14760_-
ENSG00000119402.17	5.7926703	6.0848400	5.9770295	0.5666667	-0.2833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.2921696	0.1843591	Risdiplam-specific	2.268566	FBXW2	chr9:120772840:120775492:clu_18315_-
ENSG00000112701.18	5.8132585	5.3349130	5.5127637	-0.9500000	-0.9333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.4783455	-0.3004948	Risdiplam-specific	2.295573	SENP6	chr6:75621625:75621927:clu_13126_+
ENSG00000069869.16	3.7094266	3.9353162	3.7883388	-0.3166667	0.6666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.2258896	0.0789122	Risdiplam-specific	2.300576	NEDD4	chr15:55830586:55831834:clu_28648_-
ENSG00000205268.11	5.8922730	5.9970607	6.0890504	-0.4833333	-0.0166667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.1047877	0.1967774	Risdiplam-specific	2.306077	PDE7A	chr8:65719495:65721255:clu_16666_-
ENSG00000164292.13	3.9204349	3.7821383	4.1821598	-0.8833333	0.8166667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.1382966	0.2617249	Risdiplam-specific	2.311566	RHOBTB3	chr5:95760746:95763508:clu_11187_+
ENSG00000107263.18	7.7481426	8.0216906	7.9613528	0.9333333	0.9666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.2735480	0.2132102	Risdiplam-specific	2.345126	RAPGEF1	chr9:131602149:131603961:clu_18482_-
ENSG00000270800.3	-Inf	-6.1574410	-6.1170482	0.3729349	0.3168472	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	Inf	Inf	Risdiplam-specific	2.378209	RPS10-NUDT3	chr6:34417547:34417798:clu_13830_-
ENSG00000124614.16	0.0729407	0.6627380	1.0225031	0.9500000	0.7833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.5897973	0.9495625	Risdiplam-specific	2.378209	RPS10	chr6:34417547:34417798:clu_13830_-
ENSG00000268790.5	-Inf	-Inf	-6.1170482	0.4107919	-0.4016632	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	NaN	Inf	Risdiplam-specific	2.396985	AC008764.4	chr19:16654125:16655238:clu_34507_-
ENSG00000214046.8	4.3300136	4.2001110	4.2547284	-0.8000000	-0.9333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.1299025	-0.0752851	Risdiplam-specific	2.396985	SMIM7	chr19:16654125:16655238:clu_34507_-
ENSG00000079616.13	6.7642928	6.9745767	6.8425915	-0.3166667	-0.5666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.2102839	0.0782987	Risdiplam-specific	2.405511	KIF22	chr16:29797582:29798374:clu_29534_+
ENSG00000188822.8	4.6854929	4.5525044	4.6168145	-0.9833333	-0.1666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.1329885	-0.0686784	Risdiplam-specific	2.471255	CNR2	chr1:23875662:23909367:clu_390_-
ENSG00000158234.12	2.8341480	2.8924076	2.5729498	-0.2166667	-0.9833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0582596	-0.2611982	Risdiplam-specific	2.506330	FAIM	chr3:138616664:138619711:clu_7716_+
ENSG00000071189.21	4.3992788	4.0857330	4.3351930	-0.9666667	-0.7333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.3135458	-0.0640858	Risdiplam-specific	2.546995	SNX13	chr7:17834865:17838294:clu_14629_-
ENSG00000092931.11	3.8965532	3.4124147	3.6724854	-0.9333333	-0.8500000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.4841385	-0.2240678	Risdiplam-specific	2.582979	MFSD11	chr17:76744466:76745393:clu_33223_+
ENSG00000168310.11	6.6533029	6.5494867	6.4978916	-0.8833333	-0.7000000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.1038163	-0.1554113	Risdiplam-specific	2.602322	IRF2	chr4:184429070:184449329:clu_10752_-
ENSG00000082996.19	5.1709045	5.2782293	5.0628609	0.7500000	0.6000000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.1073248	-0.1080436	Risdiplam-specific	2.641557	RNF13	chr3:149955649:149960056:clu_7765_+
ENSG00000135974.10	4.1454717	3.9510835	3.9637693	-0.1500000	0.1166667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.1943882	-0.1817024	Risdiplam-specific	2.664718	C2orf49	chr2:105344358:105345315:clu_6075_+
ENSG00000056097.16	6.9803244	7.1103699	7.0268133	0.9000000	0.6666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.1300455	0.0464889	Risdiplam-specific	2.686858	ZFR	chr5:32420103:32421631:clu_11763_-
ENSG00000144228.9	4.6371177	4.5966114	4.5703275	0.1000000	-0.4666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0405063	-0.0667902	Risdiplam-specific	2.688732	SPOPL	chr2:138552357:138552554:clu_6236_+
ENSG00000197694.18	7.6158650	7.8129346	7.7234347	-0.6166667	-0.5833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.1970696	0.1075697	Risdiplam-specific	2.736914	SPTAN1	chr9:128621998:128624328:clu_19270_+
ENSG00000164187.7	4.0948224	4.2034061	4.0641040	-0.6500000	-0.5833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.1085837	-0.0307184	Risdiplam-specific	2.767962	LMBRD2	chr5:36109551:36109945:clu_11785_-
ENSG00000145725.19	5.7507703	5.5334301	5.6332400	-0.9833333	-0.7000000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.2173402	-0.1175302	Risdiplam-specific	2.820051	PPIP5K2	chr5:103157244:103158188:clu_11234_+
ENSG00000126457.21	8.9964156	8.8587580	8.5408842	-0.8166667	-1.0000000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.1376577	-0.4555314	Risdiplam-specific	2.855578	PRMT1	chr19:49685639:49686093:clu_36267_+
ENSG00000115942.9	4.9500416	4.9086482	4.8085062	-0.8666667	-0.8166667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0413934	-0.1415354	Risdiplam-specific	2.872134	ORC2	chr2:200913413:200913828:clu_5198_-
ENSG00000108651.10	6.0570631	6.1625134	6.0820106	-0.5166667	-0.5000000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.1054503	0.0249475	Risdiplam-specific	2.881977	UTP6	chr17:31880754:31882666:clu_31456_-
ENSG00000116095.11	4.1874370	4.3690583	4.3165372	0.9333333	0.9333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.1816212	0.1291002	Risdiplam-specific	2.906637	PLEKHA3	chr2:178489645:178490659:clu_6415_+
ENSG00000135677.11	6.2738119	6.4291643	6.2158275	-0.1833333	-0.7833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.1553524	-0.0579844	Risdiplam-specific	2.925520	GNS	chr12:64752757:64752845:clu_23876_-
ENSG00000153310.19	6.6416164	6.4650685	6.4758759	-0.8000000	-0.9333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.1765479	-0.1657405	Risdiplam-specific	2.929163	CYRIB	chr8:129903350:129925548:clu_16927_-
ENSG00000123066.8	4.5321318	4.3865575	4.5013373	-0.9166667	-0.6000000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.1455743	-0.0307945	Risdiplam-specific	2.939934	MED13L	chr12:115980938:115981539:clu_24180_-
ENSG00000138413.13	6.0595426	5.9872173	5.4322551	-0.8333333	-0.9333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0723253	-0.6272874	Risdiplam-specific	2.944458	IDH1	chr2:208240003:208240239:clu_5250_-
ENSG00000145050.19	7.8300980	7.4571539	7.7066176	-0.9833333	-0.8833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.3729441	-0.1234804	Risdiplam-specific	2.945036	MANF	chr3:51388522:51388905:clu_7328_+
ENSG00000083799.17	7.1540124	7.5326662	7.3407174	0.3333333	-0.2666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.3786538	0.1867050	Risdiplam-specific	2.991397	CYLD	chr16:50775855:50776179:clu_29701_+
ENSG00000093000.19	7.1753150	7.1531718	7.2170854	-0.2333333	-0.6166667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0221432	0.0417704	Risdiplam-specific	3.049978	NUP50	chr22:45176244:45178238:clu_38833_+
ENSG00000047365.12	4.3533805	4.0299111	4.5141288	-0.2333333	-0.2166667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.3234694	0.1607483	Risdiplam-specific	3.070286	ARAP2	chr4:36083450:36087571:clu_10183_-
ENSG00000047056.16	4.0255494	4.0434576	4.1473944	-0.1000000	-0.0500000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0179083	0.1218450	Risdiplam-specific	3.072126	WDR37	chr10:1102577:1102856:clu_19482_+
ENSG00000011376.12	6.1420513	6.0806652	6.1177692	-0.7833333	-0.7333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0613861	-0.0242821	Risdiplam-specific	3.127228	LARS2	chr3:45399692:45400245:clu_7222_+
ENSG00000156469.9	4.4749894	4.2551289	3.9422962	-0.9000000	-0.9000000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.2198605	-0.5326931	Risdiplam-specific	3.137840	MTERF3	chr8:96251095:96251582:clu_16790_-
ENSG00000112308.13	6.6352683	6.7454994	6.9682582	-0.3166667	0.9166667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.1102310	0.3329899	Risdiplam-specific	3.154727	C6orf62	chr6:24708911:24709324:clu_13621_-
ENSG00000105618.14	6.7530710	6.8565795	6.9014997	-0.4500000	-0.2500000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.1035086	0.1484288	Risdiplam-specific	3.184942	PRPF31	chr19:54128805:54129057:clu_36359_+
ENSG00000196116.8	5.4226531	5.3981068	5.3892594	0.5666667	0.0500000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0245462	-0.0333937	Risdiplam-specific	3.242623	TDRD7	chr9:97414385:97428460:clu_19043_+
ENSG00000139626.16	8.4289367	8.5256085	8.7186075	-0.6833333	0.6666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0966718	0.2896708	Risdiplam-specific	3.271285	ITGB7	chr12:53201194:53205722:clu_23706_-
ENSG00000103415.12	6.1555052	6.0952245	6.0569412	-0.8833333	-0.9000000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0602808	-0.0985641	Risdiplam-specific	3.271732	HMOX2	chr16:4488742:4505484:clu_29248_+
ENSG00000150753.12	8.7913377	8.8172873	8.7974771	-0.5333333	-0.7333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0259496	0.0061394	Risdiplam-specific	3.275364	CCT5	chr5:10264548:10264656:clu_10840_+
ENSG00000137878.17	-Inf	-Inf	-Inf	0.2738613	0.7137184	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	NaN	NaN	Risdiplam-specific	3.275735	GCOM1	chr15:57706955:57707467:clu_27933_+
ENSG00000255529.9	3.6339962	3.9019035	3.7393773	0.9166667	0.6500000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.2679073	0.1053811	Risdiplam-specific	3.275735	POLR2M	chr15:57706955:57707467:clu_27933_+
ENSG00000083720.13	6.8050233	6.7546999	6.7633006	-0.7666667	-0.7833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0503234	-0.0417228	Risdiplam-specific	3.340651	OXCT1	chr5:41731770:41734575:clu_11838_-
ENSG00000133028.12	5.8801698	4.4636952	4.9901689	-0.9833333	-0.9833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-1.4164747	-0.8900010	Risdiplam-specific	3.386642	SCO1	chr17:10695446:10695741:clu_31238_-
ENSG00000110075.14	6.7897693	6.7616086	6.7692199	-0.6666667	-0.7000000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0281607	-0.0205493	Risdiplam-specific	3.407066	PPP6R3	chr11:68602155:68603342:clu_22849_+
ENSG00000188352.12	6.2083491	6.1574255	5.8454863	-0.8500000	-0.8000000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0509237	-0.3628628	Risdiplam-specific	3.444138	FOCAD	chr9:20933250:20944627:clu_18769_+
ENSG00000130159.14	5.6697893	5.7517021	5.7067171	0.2666667	0.0833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0819128	0.0369277	Risdiplam-specific	3.486950	ECSIT	chr19:11519193:11523185:clu_34366_-
ENSG00000134779.15	6.4030684	6.4744182	6.2912815	-0.1500000	-0.7833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0713497	-0.1117869	Risdiplam-specific	3.490282	TPGS2	chr18:36805502:36805992:clu_33857_-
ENSG00000136908.17	5.4260049	5.3142343	5.2907506	-0.9333333	-0.7166667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.1117706	-0.1352542	Risdiplam-specific	3.562029	DPM2	chr9:127935780:127936160:clu_18414_-
ENSG00000008083.14	4.9448917	5.3880062	5.1473944	-0.0833333	0.7833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.4431145	0.2025027	Risdiplam-specific	3.661699	JARID2	chr6:15508186:15508340:clu_12557_+
ENSG00000102900.13	6.5508501	6.7217594	6.6187193	-0.3500000	-0.5833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.1709092	0.0678692	Risdiplam-specific	3.739712	NUP93	chr16:56750374:56758538:clu_29738_+
ENSG00000235162.9	7.0215562	6.8476572	6.9780191	-0.9833333	-0.7333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.1738990	-0.0435371	Risdiplam-specific	3.754437	C12orf75	chr12:105339289:105348602:clu_25254_+
ENSG00000146007.11	6.4357612	6.4700929	6.4008672	0.1166667	-0.7166667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0343318	-0.0348940	Risdiplam-specific	3.761796	ZMAT2	chr5:140701912:140702006:clu_11430_+
ENSG00000176142.13	4.9523113	4.8752936	5.0597483	-0.8000000	-0.4666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0770177	0.1074370	Risdiplam-specific	3.805878	TMEM39A	chr3:119438103:119444873:clu_8706_-
ENSG00000159063.13	5.2528677	5.1835218	4.7347008	-0.6666667	-0.9833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0693459	-0.5181668	Risdiplam-specific	3.900791	ALG8	chr11:78106946:78108970:clu_21818_-
ENSG00000168297.16	4.4572719	4.5264309	4.3976658	0.2000000	0.7000000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0691590	-0.0596060	Risdiplam-specific	3.991608	PXK	chr3:58335452:58365874:clu_7408_+
ENSG00000079332.15	5.9944819	5.9859423	5.9895147	-0.3333333	-0.7000000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0085396	-0.0049672	Risdiplam-specific	4.011891	SAR1A	chr10:70161931:70166276:clu_20604_-
ENSG00000119414.11	6.3319944	6.1776702	6.1881585	-0.7833333	-0.9500000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.1543241	-0.1438358	Risdiplam-specific	4.112416	PPP6C	chr9:125149921:125152231:clu_18381_-
ENSG00000111252.11	6.0629114	6.0055797	6.3426395	-0.9333333	0.2333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0573317	0.2797282	Risdiplam-specific	4.151962	SH2B3	chr12:111419288:111446753:clu_25326_+
ENSG00000122643.22	6.6406786	6.5065618	6.6123601	0.6166667	0.6833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.1341168	-0.0283185	Risdiplam-specific	4.343214	NT5C3A	chr7:33024108:33024481:clu_14717_-
ENSG00000283398.1	-4.7981191	-4.5724785	-5.1170482	0.3166667	0.2666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.2256407	-0.3189291	Risdiplam-specific	4.608559	AC114737.4	chr7:76965967:76968399:clu_15875_+
ENSG00000173064.13	5.4954924	5.4998775	5.7980842	-0.6666667	0.5833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0043851	0.3025919	Risdiplam-specific	4.671793	HECTD4	chr12:112319742:112335777:clu_24159_-
ENSG00000177885.15	8.4372479	8.7097412	8.6053858	0.9000000	0.4666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.2724933	0.1681379	Risdiplam-specific	4.821942	GRB2	chr17:75332797:75387905:clu_32044_-
ENSG00000112159.12	5.4312820	5.2391638	5.5182164	-0.8166667	-0.6666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.1921182	0.0869344	Risdiplam-specific	4.910025	MDN1	chr6:89655968:89656376:clu_14100_-
ENSG00000118596.12	3.7831582	3.8467795	3.7898424	-0.5833333	-0.6666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0636214	0.0066842	Risdiplam-specific	4.924104	SLC16A7	chr12:59618477:59655152:clu_25000_+
ENSG00000149089.13	5.2158789	5.3263748	5.1213565	0.2833333	-0.8166667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.1104960	-0.0945223	Risdiplam-specific	5.036669	APIP	chr11:34895110:34911973:clu_21332_-
ENSG00000135272.11	6.8400399	6.8520378	6.9162027	-0.1000000	0.2333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0119979	0.0761628	Risdiplam-specific	5.123147	MDFIC	chr7:114960429:114979506:clu_16148_+
ENSG00000268746.1	-Inf	-Inf	-Inf	-0.0456435	0.2738613	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	NaN	NaN	Risdiplam-specific	5.171954	AC010519.1	chr19:47698067:47698634:clu_36191_+
ENSG00000063169.10	4.1399160	4.3233492	4.1473944	0.3833333	-0.2000000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.1834332	0.0074783	Risdiplam-specific	5.171954	BICRA	chr19:47698067:47698634:clu_36191_+
ENSG00000185019.17	3.5534098	3.6801870	3.6741147	-0.1166667	0.7333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.1267772	0.1207049	Risdiplam-specific	5.180906	UBOX5	chr20:3149260:3155865:clu_36520_-
ENSG00000215251.4	5.7330058	5.6710923	5.5575854	0.1000000	-0.9000000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0619135	-0.1754204	Risdiplam-specific	5.180906	FASTKD5	chr20:3149260:3155865:clu_36520_-
ENSG00000138182.14	5.4225883	5.3488666	5.1992333	-0.7000000	-0.8166667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0737216	-0.2233549	Risdiplam-specific	5.393297	KIF20B	chr10:89719706:89719788:clu_19913_+
ENSG00000184840.12	8.2545954	8.1966018	8.2168758	-0.9500000	-0.6500000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0579936	-0.0377196	Risdiplam-specific	5.427913	TMED9	chr5:177595102:177595267:clu_11649_+
ENSG00000154001.14	6.1977946	6.3468815	6.2492740	0.7666667	0.6333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.1490869	0.0514794	Risdiplam-specific	5.687174	PPP2R5E	chr14:63453885:63539292:clu_26656_-
ENSG00000132383.12	7.7774015	7.6521262	7.6758437	-0.9833333	-0.8500000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.1252753	-0.1015578	Risdiplam-specific	6.285142	RPA1	chr17:1841833:1842803:clu_32269_+
ENSG00000102531.16	5.9941860	5.8126649	5.8716365	-0.9333333	-0.6666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.1815210	-0.1225495	Risdiplam-specific	6.386338	FNDC3A	chr13:49130167:49131137:clu_26127_+
ENSG00000033030.15	4.4037055	4.4378165	3.6692214	0.6833333	-0.9833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0341110	-0.7344841	Risdiplam-specific	6.732944	ZCCHC8	chr12:122478292:122478664:clu_24289_-
ENSG00000165806.21	4.8915779	4.7777241	4.7502305	-0.3333333	-0.8833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.1138538	-0.1413474	Risdiplam-specific	6.869295	CASP7	chr10:113717753:113721032:clu_20133_+
ENSG00000155324.10	3.4373384	3.6499140	3.7174228	-0.2666667	0.2666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.2125755	0.2800844	Risdiplam-specific	7.089980	GRAMD2B	chr5:126466336:126469677:clu_11318_+
ENSG00000162694.14	3.5415857	3.6140485	3.0850756	0.6000000	-0.8000000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0724629	-0.4565101	Risdiplam-specific	7.608560	EXTL2	chr1:100877903:100878394:clu_1036_-
ENSG00000196422.11	2.3726765	2.4535838	2.6773676	0.5833333	0.3333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0809074	0.3046912	Risdiplam-specific	10.672749	PPP1R26	chr9:135484289:135484449:clu_19406_+
ENSG00000243147.8	4.6638297	4.7517021	4.5141288	0.2833333	-0.7833333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0878724	-0.1497009	Risdiplam-specific	10.674744	MRPL33	chr2:27773647:27774424:clu_5580_+
ENSG00000163697.17	4.8469728	4.9073018	4.9280288	-0.5500000	-0.6333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.0603290	0.0810560	Risdiplam-specific	12.729286	APBB2	chr4:41014398:41032584:clu_10225_-
ENSG00000154864.12	6.4592491	5.8319535	6.0927097	-0.9000000	-0.8000000	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.6272956	-0.3665394	Risdiplam-specific	15.785807	PIEZO2	chr18:10773629:10774006:clu_33760_-
ENSG00000070061.15	5.5878630	5.4909166	5.6378393	-0.7166667	-0.5333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-0.0969464	0.0499763	Risdiplam-specific	17.798155	ELP1	chr9:108931201:108933271:clu_18237_-
ENSG00000165475.15	3.9468619	0.7373768	3.5375878	-0.9833333	-0.9333333	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	-3.2094851	-0.4092741	Risdiplam-specific	21.628056	CRYL1	chr13:20404741:20405904:clu_25569_-
ENSG00000144036.16	2.7150069	3.1486207	2.7347008	0.9833333	0.6666667	Branaplam_100_LCL_polyA_1	Risdiplam_316_LCL_polyA_1	0.4336138	0.0196939	Risdiplam-specific	24.606656	EXOC6B	chr2:72179461:72182894:clu_4568_-

Yang noted that we didn’t see FOXM1 or LRKK2 on this list. Let’s investigate why.

SpecificEffects %>%
  filter(gene_names %in% c("FOXM1", "LRRK2"))

# A tibble: 0 × 5
# … with 5 variables: Color <chr>, log2Ratio <dbl>, gene_names <chr>,
#   gene_ids <chr>, junc <chr>

GA.GT.Introns %>%
  separate_rows(gene_names, gene_ids, sep=',') %>%
  filter(gene_names %in% c("FOXM1", "LRRK2", "HTT", "STAT1"))

# A tibble: 8 × 34
  junc        `#Chrom`  start    end gid   strand.y seq   Donor.score gene_names
  <chr>       <chr>     <dbl>  <dbl> <chr> <chr>    <chr>       <dbl> <chr>     
1 chr12:2859… chr12    2.86e6 2.86e6 chr1… -        ATGA…        4.63 FOXM1     
2 chr12:4022… chr12    4.02e7 4.02e7 chr1… +        ATGA…        3.60 LRRK2     
3 chr2:19097… chr2     1.91e8 1.91e8 chr2… -        AGGA…        4.83 STAT1     
4 chr2:19101… chr2     1.91e8 1.91e8 chr2… -        CAGA…        5.99 STAT1     
5 chr2:19101… chr2     1.91e8 1.91e8 chr2… -        CAGA…        5.99 STAT1     
6 chr4:32137… chr4     3.21e6 3.21e6 chr4… +        CAGA…        5.53 HTT       
7 chr4:32152… chr4     3.22e6 3.22e6 chr4… +        CAGA…        5.41 HTT       
8 chr4:32152… chr4     3.22e6 3.22e6 chr4… +        CAGA…        5.41 HTT       
# … with 25 more variables: gene_ids <chr>, SpliceDonor <chr>,
#   UpstreamSpliceAcceptor <chr>, IntronType <chr>, Steepness <dbl>,
#   LowerLimit <dbl>, UpperLimit <dbl>, ED50_Branaplam <dbl>, ED50_C2C5 <dbl>,
#   ED50_Risdiplam <dbl>, spearman.coef.Branaplam <dbl>,
#   spearman.coef.C2C5 <dbl>, spearman.coef.Risdiplam <dbl>,
#   EC.Ratio.Test.Estimate_Branaplam.C2C5 <dbl>,
#   EC.Ratio.Test.Estimate_Branaplam.Risdiplam <dbl>, …

GA.GT.Introns.OfInterest <- 
  GA.GT.Introns %>%
  separate_rows(gene_names, gene_ids, sep=',') %>%
  filter(gene_names %in% c("FOXM1", "LRRK2", "HTT", "STAT1")) %>%
  pull(junc)


GeneExpressionData.tidy %>%
  filter(hgnc_symbol %in% c("FOXM1", "LRRK2", "HTT", "STAT1")) %>%
  ggplot(aes(color=treatment)) +
  geom_line(aes(x=dose.nM, y=log2(CPM))) +
  scale_x_continuous(trans="log1p", limits=c(0, 10000), breaks=c(10000, 3160, 1000, 316, 100, 31.6, 10, 3.16, 1, 0.316, 0)) +
  facet_wrap(~hgnc_symbol, scales = "free_y") +
  theme_bw() +
  theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust=1, size=3)) +
  labs(title="Dose response effects on gene expression genes of interest")

Version	Author	Date
e11b282	Benjmain Fair	2023-03-08

…oops, with the x-axis in nanomolar units its kind of annoying to interpret. Let’s just plot the x-axis dose rank, instead of nanomolar units, since each of the titration curves cover similar effective dosages.

GeneExpressionData.tidy %>%
  filter(hgnc_symbol %in% c("FOXM1", "LRRK2", "HTT", "STAT1")) %>%
  group_by(treatment) %>%
  mutate(DoseRank = dense_rank(dose.nM)) %>%
  ungroup() %>%
  ggplot(aes(color=treatment)) +
  geom_line(aes(x=DoseRank, y=log2(CPM))) +
  facet_wrap(~hgnc_symbol, scales = "free_y") +
  theme_bw() +
  labs(title="Dose response effects on gene expression genes of interest")

Version	Author	Date
e11b282	Benjmain Fair	2023-03-08

SplicingData.tidy <- read_tsv("../code/DoseResponseData/LCL/TidySplicingDoseData.txt.gz")

SplicingData.tidy %>%
  filter(junc %in% GA.GT.Introns.OfInterest) %>%
  group_by(treatment) %>%
  mutate(DoseRank = dense_rank(dose.nM)) %>%
  ungroup() %>%
  mutate(label = paste(gene_names, junc, sep='\n')) %>%
  ggplot(aes(color=treatment)) +
  geom_line(aes(x=DoseRank, y=PSI)) +
  facet_wrap(~label, scales = "free_y") +
  theme_bw() +
  theme(strip.text.x = element_text(size = 5)) +
  labs(title="All GAGT introns in genes of interest", y="Intronic PSI")

Version	Author	Date
e11b282	Benjmain Fair	2023-03-08

Ok, so I can see the dose response gene expression effects on those genes. And also here are the dose response splicing effects for all the detected GAGT introns (and passed default leafcutter cluster filters) in those genes. The intron in FOXM1 is not in the large table because it didn’t pass my filters for specific splicing effects, and that seems understandable looking at the splicing data. The LRRK2 intron isn’t in the long table because I didn’t even attempt fitting a dose-response curve to the splicing data because I filtered for introns with spearman > 0.9 in at least one treatment. Perhaps that is a bit too strict to capture these introns that only start to show effects at the high doses.

sessionInfo()

R version 4.2.0 (2022-04-22)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)

Matrix products: default
BLAS/LAPACK: /software/openblas-0.3.13-el7-x86_64/lib/libopenblas_haswellp-r0.3.13.so

locale:
 [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C         LC_TIME=C           
 [4] LC_COLLATE=C         LC_MONETARY=C        LC_MESSAGES=C       
 [7] LC_PAPER=C           LC_NAME=C            LC_ADDRESS=C        
[10] LC_TELEPHONE=C       LC_MEASUREMENT=C     LC_IDENTIFICATION=C 

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] forcats_0.5.1   stringr_1.4.0   dplyr_1.0.9     purrr_0.3.4    
[5] readr_2.1.2     tidyr_1.2.0     tibble_3.1.7    ggplot2_3.3.6  
[9] tidyverse_1.3.1

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.8.3     lubridate_1.8.0  assertthat_0.2.1 rprojroot_2.0.3 
 [5] digest_0.6.29    utf8_1.2.2       R6_2.5.1         cellranger_1.1.0
 [9] backports_1.4.1  reprex_2.0.1     evaluate_0.15    highr_0.9       
[13] httr_1.4.3       pillar_1.7.0     rlang_1.0.2      readxl_1.4.0    
[17] rstudioapi_0.13  whisker_0.4      jquerylib_0.1.4  rmarkdown_2.14  
[21] labeling_0.4.2   bit_4.0.4        munsell_0.5.0    broom_0.8.0     
[25] compiler_4.2.0   httpuv_1.6.5     modelr_0.1.8     xfun_0.30       
[29] pkgconfig_2.0.3  htmltools_0.5.2  tidyselect_1.1.2 workflowr_1.7.0 
[33] fansi_1.0.3      crayon_1.5.1     tzdb_0.3.0       dbplyr_2.1.1    
[37] withr_2.5.0      later_1.3.0      grid_4.2.0       jsonlite_1.8.0  
[41] gtable_0.3.0     lifecycle_1.0.1  DBI_1.1.2        git2r_0.30.1    
[45] magrittr_2.0.3   scales_1.2.0     vroom_1.5.7      cli_3.3.0       
[49] stringi_1.7.6    farver_2.1.0     fs_1.5.2         promises_1.2.0.1
[53] xml2_1.3.3       bslib_0.3.1      ellipsis_0.3.2   generics_0.1.2  
[57] vctrs_0.4.1      tools_4.2.0      bit64_4.0.5      glue_1.6.2      
[61] hms_1.1.1        parallel_4.2.0   fastmap_1.1.0    yaml_2.3.5      
[65] colorspace_2.0-3 rvest_1.0.2      knitr_1.39       haven_2.5.0     
[69] sass_0.4.1

Check introns with unique specificities

2023-03-06

Recheck list of risdi/brana-specific introns

Update, 20230308