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Knit directory: flex-fusion-probes/
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Load the probe design table, which records the 50 bp probe sequence for each custom fusion probe.
probe_information <- read_csv(here("data", "analysis_input", "probe_information.csv"),
show_col_types = FALSE)The initial probe design guide recommended placing a T at position 25 (the ligation point). This turned out to be non-essential. What matters is the dinucleotide spanning positions 25–26, which is the ligation junction dinucleotide. Here we check how this dinucleotide affects performance using Calandra’s list of favourable dinucleotides from the 10x probe set.
probe_information$dinucleotide <- str_sub(probe_information$Probes, start = 25, end = 26)
# Favourable dinucleotides identified from the 10x Chromium probe set (Calandra et al.)
list_of_good_dinucleotides <- c("TA", "TC", "TG", "TT", "CT", "CA", "AT")
print("Good dinucleotides from 10x's probe set:")[1] "Good dinucleotides from 10x's probe set:"print(list_of_good_dinucleotides)[1] "TA" "TC" "TG" "TT" "CT" "CA" "AT"probe_information$dinucleotide_recommended <- probe_information$dinucleotide %in% list_of_good_dinucleotides
print("Number of probes with a recommended ligation dinucleotide:")[1] "Number of probes with a recommended ligation dinucleotide:"table(probe_information$dinucleotide_recommended)
FALSE TRUE
6 21 Fusions whose probes do not have a recommended ligation dinucleotide:
print(glue(
"Gene 1: {probe_information$`Gene 1`[!probe_information$dinucleotide_recommended]}, ",
"Gene 2: {probe_information$`Gene 2`[!probe_information$dinucleotide_recommended]}, ",
"Dinucleotide: {probe_information$dinucleotide[!probe_information$dinucleotide_recommended]}"
))Gene 1: FOXA1, Gene 2: TTC6, Dinucleotide: CC
Gene 1: ATXN7, Gene 2: AL355306.2(91741) AL499605.1(328037), Dinucleotide: AG
Gene 1: AGFG1, Gene 2: SCYGR1(4229) MIR5703(79954), Dinucleotide: AG
Gene 1: GCN1, Gene 2: MSI1, Dinucleotide: AC
Gene 1: P2RY8, Gene 2: CRLF2, Dinucleotide: AC
Gene 1: BRD9, Gene 2: NUTM1, Dinucleotide: ACStandardise the fusion name format to match the other data sources.
probe_information$fusion <- str_c(probe_information$`Gene 1`, "-", probe_information$`Gene 2`, "-fusion") %>%
gsub(pattern = "[^[:alnum:]]", replacement = "-") %>%
str_replace_all("\\--", "-")
# Set rownames for downstream merging
probe_information <- data.frame(probe_information, row.names = probe_information$fusion)
probe_information Gene.1
FOXA1-TTC6-fusion FOXA1
ARFGEF2-SULF2-fusion ARFGEF2
BCAS4-BCAS3-fusion BCAS4
YWHAE-MYO1C-fusion YWHAE
ATXN7-AL355306-2-91741-AL499605-1-328037-fusion ATXN7
ZNF217-SULF2-fusion ZNF217
ATP9A-RNU7-92P-41182-AL357558-2-5192-fusion ATP9A
DEPDC1B-ELOVL7-fusion DEPDC1B
DDX42-SLC2A10-4301-RN7SKP33-118685-fusion DDX42
NCOA3-AL499605-1-36653-AL596327-1-198826-fusion NCOA3
ATP9A-APCDD1L-fusion ATP9A
RPS6KB1-DIAPH3-fusion RPS6KB1
PREX1-LINC01754-44376-RPL35AP-21511-fusion PREX1
RSBN1-AP4B1-AS1-fusion RSBN1
EIF2AK3-RPIA-4348-ANKRD36BP2-10530-fusion EIF2AK3
TRAPPC4-DSCAML1-fusion TRAPPC4
TTC6-AL121790-1-fusion TTC6
AGFG1-SCYGR1-4229-MIR5703-79954-fusion AGFG1
BCAS3-SNTN-39526-AC104162-1-23281-fusion BCAS3
SNX14-SNHG5-fusion SNX14
GCN1-MSI1-fusion GCN1
USP31-CRYL1-fusion USP31
SGF29-AC244669-2-fusion SGF29
ATXN7L3-FAM171A2-fusion ATXN7L3
P2RY8-CRLF2-fusion P2RY8
BRD9-NUTM1-fusion BRD9
NR3C1-ZSCAN26-fusion NR3C1
Gene.2
FOXA1-TTC6-fusion TTC6
ARFGEF2-SULF2-fusion SULF2
BCAS4-BCAS3-fusion BCAS3
YWHAE-MYO1C-fusion MYO1C
ATXN7-AL355306-2-91741-AL499605-1-328037-fusion AL355306.2(91741) AL499605.1(328037)
ZNF217-SULF2-fusion SULF2
ATP9A-RNU7-92P-41182-AL357558-2-5192-fusion RNU7-92P(41182) AL357558.2(5192)
DEPDC1B-ELOVL7-fusion ELOVL7
DDX42-SLC2A10-4301-RN7SKP33-118685-fusion SLC2A10(4301) RN7SKP33(118685)
NCOA3-AL499605-1-36653-AL596327-1-198826-fusion AL499605.1(36653) AL596327.1(198826)
ATP9A-APCDD1L-fusion APCDD1L
RPS6KB1-DIAPH3-fusion DIAPH3
PREX1-LINC01754-44376-RPL35AP-21511-fusion LINC01754(44376) RPL35AP(21511)
RSBN1-AP4B1-AS1-fusion AP4B1-AS1
EIF2AK3-RPIA-4348-ANKRD36BP2-10530-fusion RPIA(4348) ANKRD36BP2(10530)
TRAPPC4-DSCAML1-fusion DSCAML1
TTC6-AL121790-1-fusion AL121790.1
AGFG1-SCYGR1-4229-MIR5703-79954-fusion SCYGR1(4229) MIR5703(79954)
BCAS3-SNTN-39526-AC104162-1-23281-fusion SNTN(39526) AC104162.1(23281)
SNX14-SNHG5-fusion SNHG5
GCN1-MSI1-fusion MSI1
USP31-CRYL1-fusion CRYL1
SGF29-AC244669-2-fusion AC244669.2
ATXN7L3-FAM171A2-fusion FAM171A2
P2RY8-CRLF2-fusion CRLF2
BRD9-NUTM1-fusion NUTM1
NR3C1-ZSCAN26-fusion ZSCAN26
mRNA
FOXA1-TTC6-fusion ATGGCGTACGCGCCGTCCAACCTGGGCCGCAGCCATTCCCACTTTTCTTA
ARFGEF2-SULF2-fusion GTGGCGCTCGGTTCCATGCAGGTGATGAACAAGACCCGGCGCATCATGGA
BCAS4-BCAS3-fusion ATCCTGGGGCCGAGGTACCTTTGACAGGAGCGTGACCCTGCTGGAGGTGT
YWHAE-MYO1C-fusion AGCGATACGACGGCCCTGGGCAGTGACGGGGTTCGGGTGACCATGGAGAG
ATXN7-AL355306-2-91741-AL499605-1-328037-fusion GAAAAACCGCGAAGTCATGGGGCTCTGTCGGGAAGGTTAAGGTACCAAAA
ZNF217-SULF2-fusion CCCGAGGACTCGCCCCGGTCTGCAAACACTCGACTGCCTTTGCCGAAAGC
ATP9A-RNU7-92P-41182-AL357558-2-5192-fusion CACCTATGAAAGCAAACGTATGGGCATCATCGTGCGGGTGTGTGAAGCTG
DEPDC1B-ELOVL7-fusion CAGTGTACTGGGTGGTTTGGGAACATTCCATGCCCTTCTAAATACAGCTG
DDX42-SLC2A10-4301-RN7SKP33-118685-fusion TCAATCTTCGGGCCAGGGTGGGTATATGGTGGTCAGCTTTCACCATGAAG
NCOA3-AL499605-1-36653-AL596327-1-198826-fusion CCGATTTAAAGCTGAGCTGCGAGGAAAATGGCGGCGGGAGGTTAGCCACC
ATP9A-APCDD1L-fusion CTGTGGTCGCATCAGCACCACGTGCAGCCGTGCCCAGCCTGTGGCCTCAT
RPS6KB1-DIAPH3-fusion GGAAGACACTGCCTGAAAATCAGAAAGTGCAGTTGACAGAAGGGTCACGT
PREX1-LINC01754-44376-RPL35AP-21511-fusion TGCTGGCTCAGGCTCTATTCTAGATACTGAGGATACAGCCCTGAAAAGAC
RSBN1-AP4B1-AS1-fusion CCCCAAGAGAGGTTCTCAAGAAGGAAAAGGAGCAGACACCTACCTATGGC
EIF2AK3-RPIA-4348-ANKRD36BP2-10530-fusion TTGCTTGGTGTCATCCAGCCTTAGCAAACCAGAGTGTGGAGACCAGAACA
TRAPPC4-DSCAML1-fusion TGCCTATCAGACTTAGTGAGCGGCTACCCAGGACCAGGCATGAAACAAAG
TTC6-AL121790-1-fusion CTGCGGCTAAGAGCAGCATTGCAGAAGCTGCTTCCATGTCCTTAAGGTGA
AGFG1-SCYGR1-4229-MIR5703-79954-fusion AACAGTCATGCAGATGGAGTCTCTCTGCGCCGAGTTTGGAGTTCAGTGGC
BCAS3-SNTN-39526-AC104162-1-23281-fusion TGCTCCACAGTTTGGATCTTTGTTGAGTGCCTGGGTAGAGCATCCAGAAA
SNX14-SNHG5-fusion CTCCCTGCTTCTTAACAGTTAGTTGAATCCATGGACATGAAACCCACAGA
GCN1-MSI1-fusion ATCCTCAGTGAACTTGGGAAGTGTGTTGCTGGAAAAGCCATTCCTCTCAC
USP31-CRYL1-fusion GACCCTGGAGTACACCCCGCAGCACAGCCGCGACTTCAAGGAATGTGTTC
SGF29-AC244669-2-fusion TCCCGGACTCGCCATGTGAGGACACAGCATCTGTGGCAACAAGGAGCCAT
ATXN7L3-FAM171A2-fusion GGAAATGTCTTTGTCTGGCCTGGATAACAGCAAACTAGAGGTGCCCGCTC
P2RY8-CRLF2-fusion TTCTGCACAGGCATGGGGCGGCTGGTTCTGCTGTGGGGAGCTGCCGTCTT
BRD9-NUTM1-fusion GAGAAGTTATCAGCCCAGTGCTTCGTTCCCTGGCCCGGCTGAAGCCCACT
NR3C1-ZSCAN26-fusion CTTCCCTGGTCGAACAGTTTTTTCTAATGGCTATTCAAGGACCCAGACCA
Probes
FOXA1-TTC6-fusion TAAGAAAAGTGGGAATGGCTGCGGCCCAGGTTGGACGGCGCGTACGCCAT
ARFGEF2-SULF2-fusion TCCATGATGCGCCGGGTCTTGTTCATCACCTGCATGGAACCGAGCGCCAC
BCAS4-BCAS3-fusion ACACCTCCAGCAGGGTCACGCTCCTGTCAAAGGTACCTCGGCCCCAGGAT
YWHAE-MYO1C-fusion CTCTCCATGGTCACCCGAACCCCGTCACTGCCCAGGGCCGTCGTATCGCT
ATXN7-AL355306-2-91741-AL499605-1-328037-fusion TTTTGGTACCTTAACCTTCCCGACAGAGCCCCATGACTTCGCGGTTTTTC
ZNF217-SULF2-fusion GCTTTCGGCAAAGGCAGTCGAGTGTTTGCAGACCGGGGCGAGTCCTCGGG
ATP9A-RNU7-92P-41182-AL357558-2-5192-fusion CAGCTTCACACACCCGCACGATGATGCCCATACGTTTGCTTTCATAGGTG
DEPDC1B-ELOVL7-fusion CAGCTGTATTTAGAAGGGCATGGAATGTTCCCAAACCACCCAGTACACTG
DDX42-SLC2A10-4301-RN7SKP33-118685-fusion CTTCATGGTGAAAGCTGACCACCATATACCCACCCTGGCCCGAAGATTGA
NCOA3-AL499605-1-36653-AL596327-1-198826-fusion GGTGGCTAACCTCCCGCCGCCATTTTCCTCGCAGCTCAGCTTTAAATCGG
ATP9A-APCDD1L-fusion ATGAGGCCACAGGCTGGGCACGGCTGCACGTGGTGCTGATGCGACCACAG
RPS6KB1-DIAPH3-fusion ACGTGACCCTTCTGTCAACTGCACTTTCTGATTTTCAGGCAGTGTCTTCC
PREX1-LINC01754-44376-RPL35AP-21511-fusion GTCTTTTCAGGGCTGTATCCTCAGTATCTAGAATAGAGCCTGAGCCAGCA
RSBN1-AP4B1-AS1-fusion GCCATAGGTAGGTGTCTGCTCCTTTTCCTTCTTGAGAACCTCTCTTGGGG
EIF2AK3-RPIA-4348-ANKRD36BP2-10530-fusion TGTTCTGGTCTCCACACTCTGGTTTGCTAAGGCTGGATGACACCAAGCAA
TRAPPC4-DSCAML1-fusion CTTTGTTTCATGCCTGGTCCTGGGTAGCCGCTCACTAAGTCTGATAGGCA
TTC6-AL121790-1-fusion TCACCTTAAGGACATGGAAGCAGCTTCTGCAATGCTGCTCTTAGCCGCAG
AGFG1-SCYGR1-4229-MIR5703-79954-fusion GCCACTGAACTCCAAACTCGGCGCAGAGAGACTCCATCTGCATGACTGTT
BCAS3-SNTN-39526-AC104162-1-23281-fusion TTTCTGGATGCTCTACCCAGGCACTCAACAAAGATCCAAACTGTGGAGCA
SNX14-SNHG5-fusion TCTGTGGGTTTCATGTCCATGGATTCAACTAACTGTTAAGAAGCAGGGAG
GCN1-MSI1-fusion GTGAGAGGAATGGCTTTTCCAGCAACACACTTCCCAAGTTCACTGAGGAT
USP31-CRYL1-fusion GAACACATTCCTTGAAGTCGCGGCTGTGCTGCGGGGTGTACTCCAGGGTC
SGF29-AC244669-2-fusion ATGGCTCCTTGTTGCCACAGATGCTGTGTCCTCACATGGCGAGTCCGGGA
ATXN7L3-FAM171A2-fusion GAGCGGGCACCTCTAGTTTGCTGTTATCCAGGCCAGACAAAGACATTTCC
P2RY8-CRLF2-fusion AAGACGGCAGCTCCCCACAGCAGAACCAGCCGCCCCATGCCTGTGCAGAA
BRD9-NUTM1-fusion AGTGGGCTTCAGCCGGGCCAGGGAACGAAGCACTGGGCTGATAACTTCTC
NR3C1-ZSCAN26-fusion TGGTCTGGGTCCTTGAATAGCCATTAGAAAAAACTGTTCGACCAGGGAAG
GC_first_half GC_second_half
FOXA1-TTC6-fusion 0.52 0.68
ARFGEF2-SULF2-fusion 0.56 0.64
BCAS4-BCAS3-fusion 0.64 0.60
YWHAE-MYO1C-fusion 0.64 0.68
ATXN7-AL355306-2-91741-AL499605-1-328037-fusion 0.44 0.56
ZNF217-SULF2-fusion 0.56 0.72
ATP9A-RNU7-92P-41182-AL357558-2-5192-fusion 0.56 0.48
DEPDC1B-ELOVL7-fusion 0.44 0.52
DDX42-SLC2A10-4301-RN7SKP33-118685-fusion 0.48 0.56
NCOA3-AL499605-1-36653-AL596327-1-198826-fusion 0.64 0.52
ATP9A-APCDD1L-fusion 0.68 0.64
RPS6KB1-DIAPH3-fusion 0.52 0.44
PREX1-LINC01754-44376-RPL35AP-21511-fusion 0.48 0.48
RSBN1-AP4B1-AS1-fusion 0.52 0.52
EIF2AK3-RPIA-4348-ANKRD36BP2-10530-fusion 0.48 0.52
TRAPPC4-DSCAML1-fusion 0.52 0.52
TTC6-AL121790-1-fusion 0.48 0.56
AGFG1-SCYGR1-4229-MIR5703-79954-fusion 0.60 0.48
BCAS3-SNTN-39526-AC104162-1-23281-fusion 0.52 0.44
SNX14-SNHG5-fusion 0.44 0.44
GCN1-MSI1-fusion 0.48 0.48
USP31-CRYL1-fusion 0.52 0.68
SGF29-AC244669-2-fusion 0.52 0.64
ATXN7L3-FAM171A2-fusion 0.56 0.48
P2RY8-CRLF2-fusion 0.60 0.68
BRD9-NUTM1-fusion 0.68 0.52
NR3C1-ZSCAN26-fusion 0.48 0.44
Deviation_of_break_in_Probe
FOXA1-TTC6-fusion -9
ARFGEF2-SULF2-fusion 15
BCAS4-BCAS3-fusion 11
YWHAE-MYO1C-fusion 13
ATXN7-AL355306-2-91741-AL499605-1-328037-fusion -10
ZNF217-SULF2-fusion 19
ATP9A-RNU7-92P-41182-AL357558-2-5192-fusion -12
DEPDC1B-ELOVL7-fusion 14
DDX42-SLC2A10-4301-RN7SKP33-118685-fusion 14
NCOA3-AL499605-1-36653-AL596327-1-198826-fusion -15
ATP9A-APCDD1L-fusion 10
RPS6KB1-DIAPH3-fusion 10
PREX1-LINC01754-44376-RPL35AP-21511-fusion 14
RSBN1-AP4B1-AS1-fusion 14
EIF2AK3-RPIA-4348-ANKRD36BP2-10530-fusion -9
TRAPPC4-DSCAML1-fusion 15
TTC6-AL121790-1-fusion 9
AGFG1-SCYGR1-4229-MIR5703-79954-fusion 12
BCAS3-SNTN-39526-AC104162-1-23281-fusion 11
SNX14-SNHG5-fusion 7
GCN1-MSI1-fusion -12
USP31-CRYL1-fusion -15
SGF29-AC244669-2-fusion 14
ATXN7L3-FAM171A2-fusion -15
P2RY8-CRLF2-fusion 15
BRD9-NUTM1-fusion 12
NR3C1-ZSCAN26-fusion -14
Amount_of_gene_1
FOXA1-TTC6-fusion 34
ARFGEF2-SULF2-fusion 10
BCAS4-BCAS3-fusion 14
YWHAE-MYO1C-fusion 12
ATXN7-AL355306-2-91741-AL499605-1-328037-fusion 35
ZNF217-SULF2-fusion 6
ATP9A-RNU7-92P-41182-AL357558-2-5192-fusion 37
DEPDC1B-ELOVL7-fusion 11
DDX42-SLC2A10-4301-RN7SKP33-118685-fusion 11
NCOA3-AL499605-1-36653-AL596327-1-198826-fusion 40
ATP9A-APCDD1L-fusion 15
RPS6KB1-DIAPH3-fusion 15
PREX1-LINC01754-44376-RPL35AP-21511-fusion 11
RSBN1-AP4B1-AS1-fusion 11
EIF2AK3-RPIA-4348-ANKRD36BP2-10530-fusion 34
TRAPPC4-DSCAML1-fusion 10
TTC6-AL121790-1-fusion 16
AGFG1-SCYGR1-4229-MIR5703-79954-fusion 13
BCAS3-SNTN-39526-AC104162-1-23281-fusion 14
SNX14-SNHG5-fusion 18
GCN1-MSI1-fusion 37
USP31-CRYL1-fusion 40
SGF29-AC244669-2-fusion 11
ATXN7L3-FAM171A2-fusion 40
P2RY8-CRLF2-fusion 10
BRD9-NUTM1-fusion 13
NR3C1-ZSCAN26-fusion 39
Amount_of_gene_2
FOXA1-TTC6-fusion 16
ARFGEF2-SULF2-fusion 40
BCAS4-BCAS3-fusion 36
YWHAE-MYO1C-fusion 38
ATXN7-AL355306-2-91741-AL499605-1-328037-fusion 15
ZNF217-SULF2-fusion 44
ATP9A-RNU7-92P-41182-AL357558-2-5192-fusion 13
DEPDC1B-ELOVL7-fusion 39
DDX42-SLC2A10-4301-RN7SKP33-118685-fusion 39
NCOA3-AL499605-1-36653-AL596327-1-198826-fusion 10
ATP9A-APCDD1L-fusion 35
RPS6KB1-DIAPH3-fusion 35
PREX1-LINC01754-44376-RPL35AP-21511-fusion 39
RSBN1-AP4B1-AS1-fusion 39
EIF2AK3-RPIA-4348-ANKRD36BP2-10530-fusion 16
TRAPPC4-DSCAML1-fusion 40
TTC6-AL121790-1-fusion 34
AGFG1-SCYGR1-4229-MIR5703-79954-fusion 37
BCAS3-SNTN-39526-AC104162-1-23281-fusion 36
SNX14-SNHG5-fusion 32
GCN1-MSI1-fusion 13
USP31-CRYL1-fusion 10
SGF29-AC244669-2-fusion 39
ATXN7L3-FAM171A2-fusion 10
P2RY8-CRLF2-fusion 40
BRD9-NUTM1-fusion 37
NR3C1-ZSCAN26-fusion 11
Homo_polymer_present
FOXA1-TTC6-fusion TRUE
ARFGEF2-SULF2-fusion FALSE
BCAS4-BCAS3-fusion TRUE
YWHAE-MYO1C-fusion TRUE
ATXN7-AL355306-2-91741-AL499605-1-328037-fusion TRUE
ZNF217-SULF2-fusion TRUE
ATP9A-RNU7-92P-41182-AL357558-2-5192-fusion FALSE
DEPDC1B-ELOVL7-fusion FALSE
DDX42-SLC2A10-4301-RN7SKP33-118685-fusion FALSE
NCOA3-AL499605-1-36653-AL596327-1-198826-fusion TRUE
ATP9A-APCDD1L-fusion FALSE
RPS6KB1-DIAPH3-fusion TRUE
PREX1-LINC01754-44376-RPL35AP-21511-fusion TRUE
RSBN1-AP4B1-AS1-fusion TRUE
EIF2AK3-RPIA-4348-ANKRD36BP2-10530-fusion FALSE
TRAPPC4-DSCAML1-fusion FALSE
TTC6-AL121790-1-fusion FALSE
AGFG1-SCYGR1-4229-MIR5703-79954-fusion FALSE
BCAS3-SNTN-39526-AC104162-1-23281-fusion FALSE
SNX14-SNHG5-fusion FALSE
GCN1-MSI1-fusion TRUE
USP31-CRYL1-fusion TRUE
SGF29-AC244669-2-fusion FALSE
ATXN7L3-FAM171A2-fusion FALSE
P2RY8-CRLF2-fusion TRUE
BRD9-NUTM1-fusion FALSE
NR3C1-ZSCAN26-fusion TRUE
dinucleotide
FOXA1-TTC6-fusion CC
ARFGEF2-SULF2-fusion AT
BCAS4-BCAS3-fusion TG
YWHAE-MYO1C-fusion TC
ATXN7-AL355306-2-91741-AL499605-1-328037-fusion AG
ZNF217-SULF2-fusion TT
ATP9A-RNU7-92P-41182-AL357558-2-5192-fusion TG
DEPDC1B-ELOVL7-fusion AT
DDX42-SLC2A10-4301-RN7SKP33-118685-fusion TA
NCOA3-AL499605-1-36653-AL596327-1-198826-fusion TT
ATP9A-APCDD1L-fusion TG
RPS6KB1-DIAPH3-fusion TT
PREX1-LINC01754-44376-RPL35AP-21511-fusion TA
RSBN1-AP4B1-AS1-fusion TT
EIF2AK3-RPIA-4348-ANKRD36BP2-10530-fusion TG
TRAPPC4-DSCAML1-fusion TA
TTC6-AL121790-1-fusion TT
AGFG1-SCYGR1-4229-MIR5703-79954-fusion AG
BCAS3-SNTN-39526-AC104162-1-23281-fusion TC
SNX14-SNHG5-fusion TC
GCN1-MSI1-fusion AC
USP31-CRYL1-fusion TG
SGF29-AC244669-2-fusion TG
ATXN7L3-FAM171A2-fusion TA
P2RY8-CRLF2-fusion AC
BRD9-NUTM1-fusion AC
NR3C1-ZSCAN26-fusion TA
dinucleotide_recommended
FOXA1-TTC6-fusion FALSE
ARFGEF2-SULF2-fusion TRUE
BCAS4-BCAS3-fusion TRUE
YWHAE-MYO1C-fusion TRUE
ATXN7-AL355306-2-91741-AL499605-1-328037-fusion FALSE
ZNF217-SULF2-fusion TRUE
ATP9A-RNU7-92P-41182-AL357558-2-5192-fusion TRUE
DEPDC1B-ELOVL7-fusion TRUE
DDX42-SLC2A10-4301-RN7SKP33-118685-fusion TRUE
NCOA3-AL499605-1-36653-AL596327-1-198826-fusion TRUE
ATP9A-APCDD1L-fusion TRUE
RPS6KB1-DIAPH3-fusion TRUE
PREX1-LINC01754-44376-RPL35AP-21511-fusion TRUE
RSBN1-AP4B1-AS1-fusion TRUE
EIF2AK3-RPIA-4348-ANKRD36BP2-10530-fusion TRUE
TRAPPC4-DSCAML1-fusion TRUE
TTC6-AL121790-1-fusion TRUE
AGFG1-SCYGR1-4229-MIR5703-79954-fusion FALSE
BCAS3-SNTN-39526-AC104162-1-23281-fusion TRUE
SNX14-SNHG5-fusion TRUE
GCN1-MSI1-fusion FALSE
USP31-CRYL1-fusion TRUE
SGF29-AC244669-2-fusion TRUE
ATXN7L3-FAM171A2-fusion TRUE
P2RY8-CRLF2-fusion FALSE
BRD9-NUTM1-fusion FALSE
NR3C1-ZSCAN26-fusion TRUE
fusion
FOXA1-TTC6-fusion FOXA1-TTC6-fusion
ARFGEF2-SULF2-fusion ARFGEF2-SULF2-fusion
BCAS4-BCAS3-fusion BCAS4-BCAS3-fusion
YWHAE-MYO1C-fusion YWHAE-MYO1C-fusion
ATXN7-AL355306-2-91741-AL499605-1-328037-fusion ATXN7-AL355306-2-91741-AL499605-1-328037-fusion
ZNF217-SULF2-fusion ZNF217-SULF2-fusion
ATP9A-RNU7-92P-41182-AL357558-2-5192-fusion ATP9A-RNU7-92P-41182-AL357558-2-5192-fusion
DEPDC1B-ELOVL7-fusion DEPDC1B-ELOVL7-fusion
DDX42-SLC2A10-4301-RN7SKP33-118685-fusion DDX42-SLC2A10-4301-RN7SKP33-118685-fusion
NCOA3-AL499605-1-36653-AL596327-1-198826-fusion NCOA3-AL499605-1-36653-AL596327-1-198826-fusion
ATP9A-APCDD1L-fusion ATP9A-APCDD1L-fusion
RPS6KB1-DIAPH3-fusion RPS6KB1-DIAPH3-fusion
PREX1-LINC01754-44376-RPL35AP-21511-fusion PREX1-LINC01754-44376-RPL35AP-21511-fusion
RSBN1-AP4B1-AS1-fusion RSBN1-AP4B1-AS1-fusion
EIF2AK3-RPIA-4348-ANKRD36BP2-10530-fusion EIF2AK3-RPIA-4348-ANKRD36BP2-10530-fusion
TRAPPC4-DSCAML1-fusion TRAPPC4-DSCAML1-fusion
TTC6-AL121790-1-fusion TTC6-AL121790-1-fusion
AGFG1-SCYGR1-4229-MIR5703-79954-fusion AGFG1-SCYGR1-4229-MIR5703-79954-fusion
BCAS3-SNTN-39526-AC104162-1-23281-fusion BCAS3-SNTN-39526-AC104162-1-23281-fusion
SNX14-SNHG5-fusion SNX14-SNHG5-fusion
GCN1-MSI1-fusion GCN1-MSI1-fusion
USP31-CRYL1-fusion USP31-CRYL1-fusion
SGF29-AC244669-2-fusion SGF29-AC244669-2-fusion
ATXN7L3-FAM171A2-fusion ATXN7L3-FAM171A2-fusion
P2RY8-CRLF2-fusion P2RY8-CRLF2-fusion
BRD9-NUTM1-fusion BRD9-NUTM1-fusion
NR3C1-ZSCAN26-fusion NR3C1-ZSCAN26-fusionLoad the Arriba results for the MCF7 bulk RNA-seq runs. These are used to cross-validate fusion detection in the single-cell data.
relevant_arriba_mcf7 <- read_csv(here("data", "analysis_input", "relevant_arriba_mcf7.csv"),
show_col_types = FALSE)Standardise the fusion name format to be consistent with the probe information and single-cell data.
relevant_arriba_mcf7$fusion <- str_c(relevant_arriba_mcf7$gene1, "-", relevant_arriba_mcf7$gene2, "-fusion") %>%
gsub(pattern = "[[:punct:]]", replacement = "-") %>%
str_replace_all("\\--", "-")Arriba was run on three bulk replicates. Here we average the split read counts and coverage across replicates for each fusion.
relevant_arriba_mcf7$average_sum_split_reads <- relevant_arriba_mcf7$split_reads1 + relevant_arriba_mcf7$split_reads2
relevant_arriba_mcf7$average_sum_coverage <- relevant_arriba_mcf7$coverage1 + relevant_arriba_mcf7$coverage2
reduced_arriba_mcf7 <- relevant_arriba_mcf7 %>%
group_by(fusion) %>%
summarise(
average_sum_split_reads = sum(average_sum_split_reads) / 3,
average_sum_coverage = sum(average_sum_coverage) / 3
)
reduced_arriba_mcf7 <- arrange(reduced_arriba_mcf7, desc(average_sum_split_reads))
# Set rownames for downstream merging
reduced_arriba_mcf7 <- data.frame(reduced_arriba_mcf7, row.names = reduced_arriba_mcf7$fusion)
reduced_arriba_mcf7 fusion
BCAS4-BCAS3-fusion BCAS4-BCAS3-fusion
FOXA1-TTC6-fusion FOXA1-TTC6-fusion
YWHAE-MYO1C-fusion YWHAE-MYO1C-fusion
ARFGEF2-SULF2-fusion ARFGEF2-SULF2-fusion
ATXN7-AL355306-2-91741-AL499605-1-328037-fusion ATXN7-AL355306-2-91741-AL499605-1-328037-fusion
NCOA3-AL499605-1-36653-AL596327-1-198826-fusion NCOA3-AL499605-1-36653-AL596327-1-198826-fusion
ZNF217-SULF2-fusion ZNF217-SULF2-fusion
GCN1-MSI1-fusion GCN1-MSI1-fusion
DEPDC1B-ELOVL7-fusion DEPDC1B-ELOVL7-fusion
ATP9A-RNU7-92P-41182-AL357558-2-5192-fusion ATP9A-RNU7-92P-41182-AL357558-2-5192-fusion
ATP9A-APCDD1L-fusion ATP9A-APCDD1L-fusion
RPS6KB1-DIAPH3-fusion RPS6KB1-DIAPH3-fusion
DDX42-SLC2A10-4301-RN7SKP33-118685-fusion DDX42-SLC2A10-4301-RN7SKP33-118685-fusion
RSBN1-AP4B1-AS1-fusion RSBN1-AP4B1-AS1-fusion
ATXN7L3-FAM171A2-fusion ATXN7L3-FAM171A2-fusion
PREX1-LINC01754-44376-RPL35AP-21511-fusion PREX1-LINC01754-44376-RPL35AP-21511-fusion
EIF2AK3-RPIA-4348-ANKRD36BP2-10530-fusion EIF2AK3-RPIA-4348-ANKRD36BP2-10530-fusion
TTC6-AL121790-1-fusion TTC6-AL121790-1-fusion
AGFG1-SCYGR1-4229-MIR5703-79954-fusion AGFG1-SCYGR1-4229-MIR5703-79954-fusion
BCAS3-SNTN-39526-AC104162-1-23281-fusion BCAS3-SNTN-39526-AC104162-1-23281-fusion
USP31-CRYL1-fusion USP31-CRYL1-fusion
SNX14-SNHG5-fusion SNX14-SNHG5-fusion
SGF29-AC244669-2-fusion SGF29-AC244669-2-fusion
TRAPPC4-DSCAML1-fusion TRAPPC4-DSCAML1-fusion
average_sum_split_reads
BCAS4-BCAS3-fusion 612.33333
FOXA1-TTC6-fusion 609.66667
YWHAE-MYO1C-fusion 596.66667
ARFGEF2-SULF2-fusion 584.33333
ATXN7-AL355306-2-91741-AL499605-1-328037-fusion 496.00000
NCOA3-AL499605-1-36653-AL596327-1-198826-fusion 336.33333
ZNF217-SULF2-fusion 226.66667
GCN1-MSI1-fusion 98.66667
DEPDC1B-ELOVL7-fusion 91.66667
ATP9A-RNU7-92P-41182-AL357558-2-5192-fusion 80.66667
ATP9A-APCDD1L-fusion 66.33333
RPS6KB1-DIAPH3-fusion 65.33333
DDX42-SLC2A10-4301-RN7SKP33-118685-fusion 64.00000
RSBN1-AP4B1-AS1-fusion 62.00000
ATXN7L3-FAM171A2-fusion 61.00000
PREX1-LINC01754-44376-RPL35AP-21511-fusion 55.66667
EIF2AK3-RPIA-4348-ANKRD36BP2-10530-fusion 49.33333
TTC6-AL121790-1-fusion 48.00000
AGFG1-SCYGR1-4229-MIR5703-79954-fusion 37.00000
BCAS3-SNTN-39526-AC104162-1-23281-fusion 37.00000
USP31-CRYL1-fusion 33.33333
SNX14-SNHG5-fusion 31.33333
SGF29-AC244669-2-fusion 20.66667
TRAPPC4-DSCAML1-fusion 14.33333
average_sum_coverage
BCAS4-BCAS3-fusion 15126.6667
FOXA1-TTC6-fusion 10531.3333
YWHAE-MYO1C-fusion 7917.3333
ARFGEF2-SULF2-fusion 5216.3333
ATXN7-AL355306-2-91741-AL499605-1-328037-fusion 3400.6667
NCOA3-AL499605-1-36653-AL596327-1-198826-fusion 3706.0000
ZNF217-SULF2-fusion 2714.0000
GCN1-MSI1-fusion 1147.0000
DEPDC1B-ELOVL7-fusion 565.0000
ATP9A-RNU7-92P-41182-AL357558-2-5192-fusion 754.6667
ATP9A-APCDD1L-fusion 891.0000
RPS6KB1-DIAPH3-fusion 5192.0000
DDX42-SLC2A10-4301-RN7SKP33-118685-fusion 1071.6667
RSBN1-AP4B1-AS1-fusion 550.0000
ATXN7L3-FAM171A2-fusion 632.0000
PREX1-LINC01754-44376-RPL35AP-21511-fusion 4436.6667
EIF2AK3-RPIA-4348-ANKRD36BP2-10530-fusion 225.0000
TTC6-AL121790-1-fusion 186.6667
AGFG1-SCYGR1-4229-MIR5703-79954-fusion 580.3333
BCAS3-SNTN-39526-AC104162-1-23281-fusion 476.0000
USP31-CRYL1-fusion 517.6667
SNX14-SNHG5-fusion 481.0000
SGF29-AC244669-2-fusion 629.0000
TRAPPC4-DSCAML1-fusion 847.6667For each fusion, calculate the distance from each breakpoint to the nearest probe in the standard 10x Chromium Human Transcriptome Probe Set. Large distances may indicate that the endogenous probe coverage near the breakpoint is sparse, which could affect background levels.
probe_pos <- import(here("data", "analysis_input",
"Chromium_Human_Transcriptome_Probe_Set_v1.1.0_GRCh38-2024-A.bed"),
format = "bed")Extract breakpoint coordinates from the Arriba output.
distance_mcf7 <- relevant_arriba_mcf7[c("fusion", "breakpoint2_chr", "breakpoint1_chr",
"breakpoint1_bp", "breakpoint2_bp")]
# Remove duplicate rows (same fusion detected across multiple replicates)
distance_mcf7 <- distance_mcf7[!duplicated(distance_mcf7), ]Functions to compute the distance from each breakpoint to the nearest 10x probe using IRanges.
check_distance <- function(chromosome, base, probe_pos) {
distance <- distanceToNearest(GRanges(chromosome, IRanges(base, base)), probe_pos)
distance@elementMetadata@listData$distance
}
fusion_distance <- function(arriba_row, probe_pos) {
arriba_row <- as.data.frame(t(arriba_row))
distance_1 <- check_distance(arriba_row$breakpoint1_chr, as.numeric(arriba_row$breakpoint1_bp), probe_pos)
distance_2 <- check_distance(arriba_row$breakpoint2_chr, as.numeric(arriba_row$breakpoint2_bp), probe_pos)
return(c(distance_1, distance_2))
}list_of_distances <- apply(distance_mcf7, 1, fusion_distance, probe_pos)
list_of_distances <- as.data.frame(t(list_of_distances))
colnames(list_of_distances) <- c("fusion1_bp_distance", "fusion2_bp_distance")
rownames(list_of_distances) <- distance_mcf7$fusion
list_of_distances fusion1_bp_distance
FOXA1-TTC6-fusion 281
ARFGEF2-SULF2-fusion 43946
BCAS4-BCAS3-fusion 23088
YWHAE-MYO1C-fusion 36973
ATXN7-AL355306-2-91741-AL499605-1-328037-fusion 69723
ZNF217-SULF2-fusion 11557
ATP9A-RNU7-92P-41182-AL357558-2-5192-fusion 10308
DEPDC1B-ELOVL7-fusion 123
DDX42-SLC2A10-4301-RN7SKP33-118685-fusion 2692
NCOA3-AL499605-1-36653-AL596327-1-198826-fusion 133318
ATP9A-APCDD1L-fusion 17945
RPS6KB1-DIAPH3-fusion 32716
PREX1-LINC01754-44376-RPL35AP-21511-fusion 26826
RSBN1-AP4B1-AS1-fusion 14052
EIF2AK3-RPIA-4348-ANKRD36BP2-10530-fusion 27694
TRAPPC4-DSCAML1-fusion 72
TTC6-AL121790-1-fusion 3346
AGFG1-SCYGR1-4229-MIR5703-79954-fusion 150
BCAS3-SNTN-39526-AC104162-1-23281-fusion 67761
SNX14-SNHG5-fusion 19224
GCN1-MSI1-fusion 26
USP31-CRYL1-fusion 40932
SGF29-AC244669-2-fusion 15944
ATXN7L3-FAM171A2-fusion 409
fusion2_bp_distance
FOXA1-TTC6-fusion 102085
ARFGEF2-SULF2-fusion 70992
BCAS4-BCAS3-fusion 33429
YWHAE-MYO1C-fusion 3434
ATXN7-AL355306-2-91741-AL499605-1-328037-fusion 840542
ZNF217-SULF2-fusion 120455
ATP9A-RNU7-92P-41182-AL357558-2-5192-fusion 279655
DEPDC1B-ELOVL7-fusion 6583
DDX42-SLC2A10-4301-RN7SKP33-118685-fusion 11159
NCOA3-AL499605-1-36653-AL596327-1-198826-fusion 475450
ATP9A-APCDD1L-fusion 464
RPS6KB1-DIAPH3-fusion 212596
PREX1-LINC01754-44376-RPL35AP-21511-fusion 174494
RSBN1-AP4B1-AS1-fusion 107
EIF2AK3-RPIA-4348-ANKRD36BP2-10530-fusion 19542
TRAPPC4-DSCAML1-fusion 43577
TTC6-AL121790-1-fusion 27148
AGFG1-SCYGR1-4229-MIR5703-79954-fusion 25957
BCAS3-SNTN-39526-AC104162-1-23281-fusion 58681
SNX14-SNHG5-fusion 29128
GCN1-MSI1-fusion 5832
USP31-CRYL1-fusion 26384
SGF29-AC244669-2-fusion 54085
ATXN7L3-FAM171A2-fusion 1459Load the MCF7 Seurat object (post-quality control and clustering) and compute per-fusion expression statistics from the single-cell data.
file <- here("data", "RDS", "mcf7_processed.seu.rds")
seu_mcf_clustering <- readRDS(file)# Count the number of cells in which a given gene/fusion is detected (count > 0)
count_cells <- function(gene, object) {
counts <- object[["RNA"]]$counts
sum(counts[gene, ] > 0)
}# Subset to fusions with at least one count
fusions_seu <- seu_mcf_clustering[str_detect(rownames(seu_mcf_clustering), "fusion") &
rowSums(seu_mcf_clustering[["RNA"]]$counts) > 0]
fusion_list <- rownames(fusions_seu)
# Total UMI counts per fusion across all cells
fusion_reads_mcf7 <- rowSums(fusions_seu[["RNA"]]$counts)
# Number of cells each fusion is detected in
fusions_cell_nums <- unlist(lapply(fusion_list, count_cells, fusions_seu))
# Fraction of cells each fusion is detected in
ncells <- ncol(fusions_seu[["RNA"]]$counts)
percent_of_cells <- fusions_cell_nums / ncells
# Mean UMI per expressing cell
average_reads_per_expressed_cell <- fusion_reads_mcf7 / fusions_cell_nums
stats <- data.frame(fusion_list, fusions_cell_nums, percent_of_cells,
fusion_reads_mcf7, average_reads_per_expressed_cell)
stats fusion_list
FOXA1-TTC6-fusion FOXA1-TTC6-fusion
ARFGEF2-SULF2-fusion ARFGEF2-SULF2-fusion
BCAS4-BCAS3-fusion BCAS4-BCAS3-fusion
YWHAE-MYO1C-fusion YWHAE-MYO1C-fusion
ATXN7-AL355306-2-91741-AL499605-1-328037-fusion ATXN7-AL355306-2-91741-AL499605-1-328037-fusion
ZNF217-SULF2-fusion ZNF217-SULF2-fusion
ATP9A-RNU7-92P-41182-AL357558-2-5192-fusion ATP9A-RNU7-92P-41182-AL357558-2-5192-fusion
DEPDC1B-ELOVL7-fusion DEPDC1B-ELOVL7-fusion
DDX42-SLC2A10-4301-RN7SKP33-118685-fusion DDX42-SLC2A10-4301-RN7SKP33-118685-fusion
NCOA3-AL499605-1-36653-AL596327-1-198826-fusion NCOA3-AL499605-1-36653-AL596327-1-198826-fusion
ATP9A-APCDD1L-fusion ATP9A-APCDD1L-fusion
RPS6KB1-DIAPH3-fusion RPS6KB1-DIAPH3-fusion
PREX1-LINC01754-44376-RPL35AP-21511-fusion PREX1-LINC01754-44376-RPL35AP-21511-fusion
RSBN1-AP4B1-AS1-fusion RSBN1-AP4B1-AS1-fusion
EIF2AK3-RPIA-4348-ANKRD36BP2-10530-fusion EIF2AK3-RPIA-4348-ANKRD36BP2-10530-fusion
TRAPPC4-DSCAML1-fusion TRAPPC4-DSCAML1-fusion
TTC6-AL121790-1-fusion TTC6-AL121790-1-fusion
AGFG1-SCYGR1-4229-MIR5703-79954-fusion AGFG1-SCYGR1-4229-MIR5703-79954-fusion
BCAS3-SNTN-39526-AC104162-1-23281-fusion BCAS3-SNTN-39526-AC104162-1-23281-fusion
SNX14-SNHG5-fusion SNX14-SNHG5-fusion
GCN1-MSI1-fusion GCN1-MSI1-fusion
USP31-CRYL1-fusion USP31-CRYL1-fusion
SGF29-AC244669-2-fusion SGF29-AC244669-2-fusion
ATXN7L3-FAM171A2-fusion ATXN7L3-FAM171A2-fusion
fusions_cell_nums
FOXA1-TTC6-fusion 1994
ARFGEF2-SULF2-fusion 6838
BCAS4-BCAS3-fusion 6848
YWHAE-MYO1C-fusion 3071
ATXN7-AL355306-2-91741-AL499605-1-328037-fusion 488
ZNF217-SULF2-fusion 5933
ATP9A-RNU7-92P-41182-AL357558-2-5192-fusion 575
DEPDC1B-ELOVL7-fusion 3487
DDX42-SLC2A10-4301-RN7SKP33-118685-fusion 1543
NCOA3-AL499605-1-36653-AL596327-1-198826-fusion 7048
ATP9A-APCDD1L-fusion 52
RPS6KB1-DIAPH3-fusion 1795
PREX1-LINC01754-44376-RPL35AP-21511-fusion 327
RSBN1-AP4B1-AS1-fusion 944
EIF2AK3-RPIA-4348-ANKRD36BP2-10530-fusion 993
TRAPPC4-DSCAML1-fusion 374
TTC6-AL121790-1-fusion 591
AGFG1-SCYGR1-4229-MIR5703-79954-fusion 186
BCAS3-SNTN-39526-AC104162-1-23281-fusion 777
SNX14-SNHG5-fusion 96
GCN1-MSI1-fusion 199
USP31-CRYL1-fusion 2055
SGF29-AC244669-2-fusion 727
ATXN7L3-FAM171A2-fusion 3533
percent_of_cells
FOXA1-TTC6-fusion 0.279781114
ARFGEF2-SULF2-fusion 0.959449979
BCAS4-BCAS3-fusion 0.960853094
YWHAE-MYO1C-fusion 0.430896590
ATXN7-AL355306-2-91741-AL499605-1-328037-fusion 0.068472008
ZNF217-SULF2-fusion 0.832468079
ATP9A-RNU7-92P-41182-AL357558-2-5192-fusion 0.080679108
DEPDC1B-ELOVL7-fusion 0.489266171
DDX42-SLC2A10-4301-RN7SKP33-118685-fusion 0.216500631
NCOA3-AL499605-1-36653-AL596327-1-198826-fusion 0.988915392
ATP9A-APCDD1L-fusion 0.007296198
RPS6KB1-DIAPH3-fusion 0.251859127
PREX1-LINC01754-44376-RPL35AP-21511-fusion 0.045881858
RSBN1-AP4B1-AS1-fusion 0.132454048
EIF2AK3-RPIA-4348-ANKRD36BP2-10530-fusion 0.139329311
TRAPPC4-DSCAML1-fusion 0.052476498
TTC6-AL121790-1-fusion 0.082924091
AGFG1-SCYGR1-4229-MIR5703-79954-fusion 0.026097937
BCAS3-SNTN-39526-AC104162-1-23281-fusion 0.109022029
SNX14-SNHG5-fusion 0.013469903
GCN1-MSI1-fusion 0.027921987
USP31-CRYL1-fusion 0.288340115
SGF29-AC244669-2-fusion 0.102006454
ATXN7L3-FAM171A2-fusion 0.495720500
fusion_reads_mcf7
FOXA1-TTC6-fusion 2598
ARFGEF2-SULF2-fusion 52438
BCAS4-BCAS3-fusion 65626
YWHAE-MYO1C-fusion 4591
ATXN7-AL355306-2-91741-AL499605-1-328037-fusion 520
ZNF217-SULF2-fusion 21112
ATP9A-RNU7-92P-41182-AL357558-2-5192-fusion 610
DEPDC1B-ELOVL7-fusion 7578
DDX42-SLC2A10-4301-RN7SKP33-118685-fusion 1877
NCOA3-AL499605-1-36653-AL596327-1-198826-fusion 114906
ATP9A-APCDD1L-fusion 53
RPS6KB1-DIAPH3-fusion 2293
PREX1-LINC01754-44376-RPL35AP-21511-fusion 344
RSBN1-AP4B1-AS1-fusion 1078
EIF2AK3-RPIA-4348-ANKRD36BP2-10530-fusion 1104
TRAPPC4-DSCAML1-fusion 383
TTC6-AL121790-1-fusion 640
AGFG1-SCYGR1-4229-MIR5703-79954-fusion 192
BCAS3-SNTN-39526-AC104162-1-23281-fusion 867
SNX14-SNHG5-fusion 98
GCN1-MSI1-fusion 208
USP31-CRYL1-fusion 2616
SGF29-AC244669-2-fusion 780
ATXN7L3-FAM171A2-fusion 5855
average_reads_per_expressed_cell
FOXA1-TTC6-fusion 1.302909
ARFGEF2-SULF2-fusion 7.668617
BCAS4-BCAS3-fusion 9.583236
YWHAE-MYO1C-fusion 1.494953
ATXN7-AL355306-2-91741-AL499605-1-328037-fusion 1.065574
ZNF217-SULF2-fusion 3.558402
ATP9A-RNU7-92P-41182-AL357558-2-5192-fusion 1.060870
DEPDC1B-ELOVL7-fusion 2.173215
DDX42-SLC2A10-4301-RN7SKP33-118685-fusion 1.216461
NCOA3-AL499605-1-36653-AL596327-1-198826-fusion 16.303348
ATP9A-APCDD1L-fusion 1.019231
RPS6KB1-DIAPH3-fusion 1.277437
PREX1-LINC01754-44376-RPL35AP-21511-fusion 1.051988
RSBN1-AP4B1-AS1-fusion 1.141949
EIF2AK3-RPIA-4348-ANKRD36BP2-10530-fusion 1.111782
TRAPPC4-DSCAML1-fusion 1.024064
TTC6-AL121790-1-fusion 1.082910
AGFG1-SCYGR1-4229-MIR5703-79954-fusion 1.032258
BCAS3-SNTN-39526-AC104162-1-23281-fusion 1.115830
SNX14-SNHG5-fusion 1.020833
GCN1-MSI1-fusion 1.045226
USP31-CRYL1-fusion 1.272993
SGF29-AC244669-2-fusion 1.072902
ATXN7L3-FAM171A2-fusion 1.657232Combine single-cell fusion statistics with Arriba bulk results, probe design information, and breakpoint distances into a single summary table.
stats <- stats %>%
cbind(reduced_arriba_mcf7[stats$fusion_list, ]) %>%
cbind(probe_information[stats$fusion_list, ]) %>%
cbind(list_of_distances[stats$fusion_list, ])
# Remove redundant columns carried over from the merge sources
stats <- stats[, !names(stats) %in% c("fusion", "Gene.1", "Gene.2", "Probe_fusion")]# Save on first run only; delete the file manually to force regeneration.
out <- here("data", "RDS", "mcf7_fusion_stats.rds")
if (!file.exists(out)) saveRDS(stats, out)sessioninfo::session_info()─ Session info ───────────────────────────────────────────────────────────────
setting value
version R version 4.4.1 (2024-06-14)
os macOS 15.5
system aarch64, darwin20
ui X11
language (EN)
collate en_US.UTF-8
ctype en_US.UTF-8
tz Australia/Melbourne
date 2026-07-15
pandoc 3.8.3 @ /Applications/RStudio.app/Contents/Resources/app/quarto/bin/tools/aarch64/ (via rmarkdown)
quarto 1.9.38 @ /Applications/RStudio.app/Contents/Resources/app/quarto/bin/quarto
─ Packages ───────────────────────────────────────────────────────────────────
! package * version date (UTC) lib source
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[1] /Users/maksimovicjovana/Library/CloudStorage/OneDrive-PeterMac/Desktop/projects/my_research/flex-fusion-probes/renv/library/macos/R-4.4/aarch64-apple-darwin20
[2] /Users/maksimovicjovana/Library/Caches/org.R-project.R/R/renv/sandbox/macos/R-4.4/aarch64-apple-darwin20/f7156815
* ── Packages attached to the search path.
P ── Loaded and on-disk path mismatch.
──────────────────────────────────────────────────────────────────────────────
sessionInfo()R version 4.4.1 (2024-06-14)
Platform: aarch64-apple-darwin20
Running under: macOS 15.5
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRlapack.dylib; LAPACK version 3.12.0
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
time zone: Australia/Melbourne
tzcode source: internal
attached base packages:
[1] stats4 stats graphics grDevices datasets utils methods
[8] base
other attached packages:
[1] rtracklayer_1.66.0 GenomicRanges_1.58.0 GenomeInfoDb_1.42.3
[4] IRanges_2.40.1 S4Vectors_0.44.0 BiocGenerics_0.52.0
[7] readr_2.1.5 glue_1.8.0 stringr_1.6.0
[10] Seurat_5.3.0 SeuratObject_5.1.0 sp_2.2-0
[13] dplyr_1.1.4 here_1.0.1 workflowr_1.7.1
loaded via a namespace (and not attached):
[1] RcppAnnoy_0.0.22 splines_4.4.1
[3] later_1.4.2 BiocIO_1.16.0
[5] bitops_1.0-9 tibble_3.2.1
[7] polyclip_1.10-7 XML_3.99-0.18
[9] fastDummies_1.7.5 lifecycle_1.0.4
[11] rprojroot_2.0.4 vroom_1.6.5
[13] globals_0.18.0 processx_3.8.6
[15] lattice_0.22-6 MASS_7.3-60.2
[17] magrittr_2.0.3 plotly_4.10.4
[19] sass_0.4.10 rmarkdown_2.29
[21] jquerylib_0.1.4 yaml_2.3.10
[23] httpuv_1.6.16 sctransform_0.4.2
[25] spam_2.11-1 sessioninfo_1.2.3
[27] spatstat.sparse_3.1-0 reticulate_1.42.0
[29] cowplot_1.1.3 pbapply_1.7-4
[31] RColorBrewer_1.1-3 abind_1.4-8
[33] zlibbioc_1.52.0 Rtsne_0.17
[35] purrr_1.0.4 RCurl_1.98-1.17
[37] git2r_0.36.2 GenomeInfoDbData_1.2.13
[39] ggrepel_0.9.6 irlba_2.3.5.1
[41] listenv_0.9.1 spatstat.utils_3.1-4
[43] goftest_1.2-3 RSpectra_0.16-2
[45] spatstat.random_3.4-1 fitdistrplus_1.2-2
[47] parallelly_1.45.0 DelayedArray_0.32.0
[49] codetools_0.2-20 tidyselect_1.2.1
[51] UCSC.utils_1.2.0 farver_2.1.2
[53] matrixStats_1.5.0 spatstat.explore_3.4-3
[55] GenomicAlignments_1.42.0 jsonlite_2.0.0
[57] progressr_0.15.1 ggridges_0.5.6
[59] survival_3.6-4 tools_4.4.1
[61] ica_1.0-3 Rcpp_1.1.1-1.1
[63] SparseArray_1.6.2 gridExtra_2.3
[65] xfun_0.56 MatrixGenerics_1.18.1
[67] BiocManager_1.30.27 fastmap_1.2.0
[69] callr_3.7.6 digest_0.6.37
[71] R6_2.6.1 mime_0.13
[73] colorspace_2.1-1 scattermore_1.2
[75] tensor_1.5 spatstat.data_3.1-6
[77] tidyr_1.3.1 generics_0.1.4
[79] renv_1.1.4 data.table_1.18.2.1
[81] S4Arrays_1.6.0 httr_1.4.7
[83] htmlwidgets_1.6.4 whisker_0.4.1
[85] uwot_0.2.3 pkgconfig_2.0.3
[87] gtable_0.3.6 lmtest_0.9-40
[89] S7_0.2.0 XVector_0.46.0
[91] htmltools_0.5.8.1 dotCall64_1.2
[93] scales_1.4.0 Biobase_2.66.0
[95] png_0.1-8 spatstat.univar_3.1-3
[97] knitr_1.50 rstudioapi_0.17.1
[99] tzdb_0.5.0 reshape2_1.4.4
[101] rjson_0.2.23 nlme_3.1-164
[103] curl_6.2.3 cachem_1.1.0
[105] zoo_1.8-14 KernSmooth_2.23-24
[107] parallel_4.4.1 miniUI_0.1.2
[109] restfulr_0.0.15 pillar_1.10.2
[111] grid_4.4.1 vctrs_0.6.5
[113] RANN_2.6.2 promises_1.3.3
[115] xtable_1.8-4 cluster_2.1.6
[117] evaluate_1.0.3 cli_3.6.5
[119] compiler_4.4.1 Rsamtools_2.22.0
[121] rlang_1.1.6 crayon_1.5.3
[123] future.apply_1.11.3 ps_1.9.1
[125] getPass_0.2-4 plyr_1.8.9
[127] fs_1.6.6 stringi_1.8.7
[129] viridisLite_0.4.2 deldir_2.0-4
[131] BiocParallel_1.40.2 Biostrings_2.74.1
[133] lazyeval_0.2.2 spatstat.geom_3.4-1
[135] Matrix_1.7-0 RcppHNSW_0.6.0
[137] hms_1.1.3 patchwork_1.3.0
[139] bit64_4.6.0-1 future_1.49.0
[141] ggplot2_4.0.2 shiny_1.10.0
[143] SummarizedExperiment_1.36.0 ROCR_1.0-11
[145] igraph_2.1.4 bslib_0.9.0
[147] bit_4.6.0