Closed EeSsSs closed 3 months ago
ncborcherding
commented
3 months ago Hey @EeSsSs
What is the output of your sessionInfo()
Also it would be immensely helpful to make a reproducible example: please see Hadley's rundown of a reproducible example . If data privacy is a concern, please make an example with the built-in data from scRepertoire.
Thanks, Nick
EeSsSs
commented
3 months ago Thank you for coming back to me Nick. I have now included the sessionInfo in my original comment, together with the reproducible info on the datasets. Is this the correct way? I did not know how to make a reproducible example of a complete Seurat object..
ncborcherding
commented
3 months ago @EeSsSs
Apologies for the delay - found the issue in combineExpression() with when chain != "both". Fixed now in the dev version and will get it into the master branch later this week.
Nick
EeSsSs
commented
3 months ago Thank you!
Op ma 15 jul 2024 om 19:08 schreef theHumanBorch @.***>:
@EeSsSs https://github.com/EeSsSs
Apologies for the delay - found the issue in combineExpression() with when chain != "both". Fixed now in the dev version and will get it into the master branch later this week.
Nick
— Reply to this email directly, view it on GitHub https://github.com/ncborcherding/scRepertoire/issues/390#issuecomment-2228994122, or unsubscribe https://github.com/notifications/unsubscribe-auth/ALRTBY3BYOF6TD6NN7FZLY3ZMP62NAVCNFSM6AAAAABKSSDB5SVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDEMRYHE4TIMJSGI . You are receiving this because you were mentioned.Message ID: @.***>
I would like to explore the cloneSizes of my dataset using either both chains or only the TCR-beta chain. When I use the chain='both' parameter, I get my results as expected. However, when I run chain='TRB' or chain='TRA', I get the error: Error in FUN(X[[i]], ...) : object 'full.clone' not found. My combineTCR-dataframe looks as follows, as far as I can see the column names are similar to the result in the combineTCR tutorial
Code: FSP_filtered_TCR <- combineExpression(FSP_TCR_combinedorphanB,FSP_filtered,group.by = 'donor_id', cloneCall = 'aa', chain = 'TRB') vs FSP_filtered_TCR <- combineExpression(FSP_TCR_combinedorphanB,FSP_filtered,group.by = 'donor_id', cloneCall = 'aa', chain = 'both')
FSP_filtered@meta.data <- dput(FSP_filtered@meta.data[1:20,]) structure(list(orig.ident = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), levels = "FSP", class = "factor"), nCount_RNA = c(7765, 2009, 6849, 2095, 7366, 7067, 6345, 1861, 5330, 4832, 5518, 3334, 4840, 3250, 5663, 11043, 8738, 5711, 10586, 6900), nFeature_RNA = c(2640L, 1024L, 2487L, 1167L, 2249L, 2846L, 2200L, 987L, 2161L, 1736L, 2196L, 1329L, 1809L, 1402L, 2042L, 3585L, 2820L, 2207L, 3199L, 2374L), nCount_ADT = c(1700, 883, 1957, 1046, 1866, 2212, 1922, 235, 1647, 2586, 1355, 736, 1178, 373, 2590, 1593, 1307, 959, 2104, 1417), nFeature_ADT = c(10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L), percent.mt = c(2.17643271088216, 3.18566450970632, 1.53307052124398, 4.43914081145585, 1.09964702688026, 2.51874911560775, 3.16784869976359, 1.45083288554541, 1.03189493433396, 0.227649006622517, 1.30482058716926, 1.9496100779844, 1.17768595041322, 1.53846153846154, 3.23150273706516, 1.59376980892873, 0.858319981689174, 1.34827525827351, 1.2469299074249, 1.59420289855072), percent.ribo = c(33.650998068255, 30.9109009457442, 32.5886990801577, 22.1957040572792, 40.9448818897638, 22.824395075704, 32.2773837667455, 29.8226759806556, 26.1350844277674, 38.5140728476821, 29.0685030808264, 37.4025194961008, 38.1818181818182, 31.0153846153846, 35.2993113190888, 28.226025536539, 37.1023117418174, 29.0316932236036, 35.4713772907614, 33.7826086956522), S.Score = c(-0.0740353956283032, -0.0723471837596801, -0.0708561234725496, -0.0103838028239838, -0.0974760753166953, 0.0387584337777187, -0.0703057701616523, -0.0293300153363912, -0.0947863191282281, -0.00916448458189195, -0.0145284897259919, -0.043216755714151, 0.0118163174494839, -0.0928201090587158, 0.0522764914747454, 0.092645791529207, -0.0659372809781483, 0.00663062497793063, -0.0335308420124335, -0.0279848478020128), G2M.Score = c(-0.132691539293379, -0.101102980340982, -0.116213017576823, -0.0680104276129055, -0.0651503755810307, 1.04523903163742, -0.124250324768246, -0.0819383687416872, -0.0663687707109106, -0.0652238825720866, -0.0822126544282594, -0.0881114567087572, -0.0179395862439813, -0.00219514374548674, 0.0284525473829916, -0.0312508504587002, -0.0702732590397545, 0.0130257391482406, -0.0299327493742494, -0.0781575065481768 ), Phase = c("G1", "G1", "G1", "G1", "G1", "G2M", "G1", "G1", "G1", "G1", "G1", "G1", "S", "G1", "S", "S", "G1", "G2M", "G1", "G1"), donor_id = c("donor5", "unassigned", "donor5", "donor3", "donor2", "donor4", "donor5", "doublet", "doublet", "donor4", "donor2", "donor2", "donor1", "doublet", "donor0", NA, "donor4", "donor1", "doublet", "donor0"), hash.ID = structure(c(2L, 3L, 2L, 4L, 5L, 1L, 2L, 3L, 2L, 6L, 5L, 5L, 7L, 3L, 1L, NA, 6L, 7L, 1L, 8L), levels = c("Doublet", "L3", "Negative", "L4", "L5", "L2", "L1", "L6"), class = "factor"), organ = c("Spleen", "Spleen", "Spleen", "Spleen", "Spleen", "Spleen", "Spleen", "Spleen", "Spleen", "Spleen", "Spleen", "Spleen", "Spleen", "Spleen", "Spleen", NA, "Spleen", "Spleen", "Spleen", "Spleen" ), subject = structure(c(6L, 7L, 6L, 4L, 3L, 5L, 6L, 8L, 8L, 5L, 3L, 3L, 2L, 8L, 1L, NA, 5L, 2L, 8L, 1L), levels = c("d009_18", "d007_21", "d010_21", "d008_23", "d004_18", "d006_21", "unassigned", "doublet"), class = "factor"), gestation = structure(c(2L, 4L, 2L, 3L, 2L, 1L, 2L, 5L, 5L, 1L, 2L, 2L, 2L, 5L, 1L, NA, 1L, 2L, 5L, 1L), levels = c("18", "21", "23", "unassigned", "doublet"), class = "factor"), RNA_snn_res.0.1 = structure(c(2L, 2L, 1L, 4L, 2L, 3L, 1L, 2L, 4L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 3L, 2L), levels = c("0", "1", "2", "3", "4"), class = "factor"), RNA_snn_res.0.2 = structure(c(2L, 2L, 1L, 3L, 2L, 6L, 1L, 2L, 3L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 4L, 2L), levels = c("0", "1", "2", "3", "4", "5", "6"), class = "factor"), RNA_snn_res.0.3 = structure(c(2L, 2L, 1L, 3L, 2L, 5L, 1L, 2L, 3L, 2L, 6L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 4L, 2L), levels = c("0", "1", "2", "3", "4", "5", "6", "7", "8"), class = "factor"), RNA_snn_res.0.4 = structure(c(1L, 1L, 2L, 5L, 1L, 8L, 2L, 1L, 5L, 1L, 3L, 3L, 2L, 1L, 1L, 1L, 1L, 1L, 4L, 1L), levels = c("0", "1", "2", "3", "4", "5", "6", "7", "8", "9"), class = "factor"), RNA_snn_res.0.5 = structure(c(1L, 1L, 2L, 3L, 1L, 9L, 2L, 1L, 3L, 1L, 7L, 5L, 2L, 1L, 1L, 1L, 1L, 1L, 4L, 1L), levels = c("0", "1", "2", "3", "4", "5", "6", "7", "8", "9", "10"), class = "factor"), RNA_snn_res.0.6 = structure(c(2L, 2L, 1L, 3L, 2L, 11L, 1L, 2L, 3L, 2L, 7L, 6L, 1L, 2L, 2L, 2L, 2L, 2L, 4L, 2L), levels = c("0", "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14"), class = "factor"), RNA_snn_res.0.7 = structure(c(2L, 2L, 1L, 3L, 2L, 12L, 1L, 2L, 3L, 2L, 7L, 6L, 1L, 2L, 2L, 2L, 2L, 2L, 4L, 2L), levels = c("0", "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14"), class = "factor"), RNA_snn_res.0.8 = structure(c(2L, 2L, 1L, 3L, 2L, 12L, 1L, 2L, 3L, 2L, 7L, 5L, 1L, 2L, 2L, 2L, 2L, 2L, 4L, 2L), levels = c("0", "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14"), class = "factor"), RNA_snn_res.0.9 = structure(c(2L, 2L, 1L, 3L, 13L, 12L, 1L, 2L, 3L, 5L, 7L, 6L, 1L, 2L, 2L, 2L, 2L, 2L, 4L, 2L), levels = c("0", "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15"), class = "factor"), RNA_snn_res.1 = structure(c(1L, 1L, 3L, 4L, 14L, 12L, 3L, 1L, 4L, 1L, 8L, 6L, 6L, 1L, 1L, 1L, 1L, 1L, 5L, 1L), levels = c("0", "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16"), class = "factor"), seurat_clusters = structure(c(1L, 1L, 3L, 4L, 14L, 12L, 3L, 1L, 4L, 1L, 8L, 6L, 6L, 1L, 1L, 1L, 1L, 1L, 5L, 1L), levels = c("0", "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16"), class = "factor"), pANN_0.25_0.2_875 = c(0.326229939489608, 0.233096553538543, 0.344646145751118, 0.203630623520126, 0.275190739279137, 0.366482504604052, 0.322283609576427, 0.123914759273875, 0.398316232570376, 0.226256248355696, 0.259142330965535, 0.152065245987898, 0.183635885293344, 0.242304656669298, 0.24388318863457, 0.449092344119968, 0.317811102341489, 0.283346487766377, 0.425151275980005, 0.318863456985004), DF.classifications_0.25_0.2_875 = c("Singlet", "Singlet", "Singlet", "Singlet", "Singlet", "Singlet", "Singlet", "Singlet", "Singlet", "Singlet", "Singlet", "Singlet", "Singlet", "Singlet", "Singlet", "Doublet", "Singlet", "Singlet", "Singlet", "Singlet" ), CD4_ADT = c(1.11683981685083, 0.791873072764484, 2.47826007463373, 1.01754452050554, 0.268687942247982, 2.51245908144789, 2.23655134822189, 0.883254029269942, 2.04206478402807, 0.238104257647166, 2.23233049047037, 2.18424533301505, 2.27893712196837, 0.5680916527347, 0.262672852328498, 0.214626440674391, 0.196395257941802, 1.15873680676986, 2.69636978044339, 0.341164395850222), CD8_ADT = c(1.57170516811142, 1.36808977008972, 0.327721232690515, 1.81022722043909, 2.51062788894182, 0.959155588755894, 0.661968538804572, 1.14946748947059, 1.85134669493369, 2.24492440505505, 0.838559978510677, 0.904387237717268, 0.285197893276344, 1.57370275136779, 2.22728900356946, 1.98980999642868, 2.64051844293718, 1.78173409578312, 0.419466875996471, 2.05425822773632), CD4CD8_ADT_double = c(FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE)), row.names = c("AAACCTGAGAGACTTA-1", "AAACCTGAGAGTAATC-1", "AAACCTGAGATCACGG-1", "AAACCTGAGATCGATA-1", "AAACCTGAGCACCGCT-1", "AAACCTGAGGACGAAA-1", "AAACCTGAGTGTACGG-1", "AAACCTGCACAGTCGC-1", "AAACCTGCACGAAATA-1", "AAACCTGCACTTCTGC-1", "AAACCTGCAGCCACCA-1", "AAACCTGCAGGGAGAG-1", "AAACCTGCAGGTGGAT-1", "AAACCTGCATGGTCTA-1", "AAACCTGGTACACCGC-1", "AAACCTGGTACAGTTC-1", "AAACCTGGTAGCACGA-1", "AAACCTGGTATAGGTA-1", "AAACCTGGTCTAAAGA-1", "AAACCTGGTTCCGTCT-1" ), class = "data.frame")
FSP_TCR_combinedorphanB <- dput(FSP_TCR_combinedorphanB$FSP[1:20,]) structure(list(barcode = c("AAACCTGAGAGACTTA-1", "AAACCTGAGAGTAATC-1", "AAACCTGAGATCACGG-1", "AAACCTGAGCACCGCT-1", "AAACCTGAGGACGAAA-1", "AAACCTGAGTGTACGG-1", "AAACCTGCACGAAATA-1", "AAACCTGCACTTCTGC-1", "AAACCTGCAGCCACCA-1", "AAACCTGCAGGGAGAG-1", "AAACCTGCAGGTGGAT-1", "AAACCTGCATGGTCTA-1", "AAACCTGGTACACCGC-1", "AAACCTGGTACAGTTC-1", "AAACCTGGTAGCACGA-1", "AAACCTGGTATAGGTA-1", "AAACCTGGTCTAAAGA-1", "AAACCTGGTTCCGTCT-1", "AAACCTGGTTCTGGTA-1", "AAACCTGTCATGCATG-1" ), sample = c("FSP", "FSP", "FSP", "FSP", "FSP", "FSP", "FSP", "FSP", "FSP", "FSP", "FSP", "FSP", "FSP", "FSP", "FSP", "FSP", "FSP", "FSP", "FSP", "FSP"), TCR1 = c("TRAV26-1.TRAJ29.TRAC", "TRAV21.TRAJ27.TRAC", "TRAV41.TRAJ49.TRAC", "TRAV12-2.TRAJ41.TRAC", NA, "TRAV24.TRAJ16.TRAC", "TRAV8-3.TRAJ27.TRAC", "TRAV1-1.TRAJ12.TRAC", NA, "TRAV35.TRAJ28.TRAC", "TRAV2.TRAJ29.TRAC", NA, "TRAV13-1.TRAJ6.TRAC", "TRAV41.TRAJ41.TRAC", "TRAV19.TRAJ32.TRAC", "TRAV3.TRAJ28.TRAC", "TRAV8-3.TRAJ21.TRAC", "TRAV21.TRAJ52.TRAC", "TRAV17.TRAJ22.TRAC", "TRAV13-1.TRAJ52.TRAC"), cdr3_aa1 = c("CIAPDPNTPLVF", "CAVRGRVTNAGKSTF", "CAVRSGNQFYF", "CAVNSNSGYALNF", NA, "CAFGGQKLLF", "CAVDTNAGKSTF", "CAVLMDSSYKLIF", NA, "CAVAYSGAGSYQLTF", "CAVSGNTPLVF", NA, "CATSGGSYIPTF", "CAVNSNSGYALNF", "CALSEAYGGATNKLIF", "CAVRDPYSGAGSYQLTF", "CAVGAEYNFNKFYF", "CAVNAGGTSYGKLTF", "CALSGSARQLTF", "CAAVVTGGTSYGKLTF"), cdr3_nt1 = c("TGCATCGCGCCTGACCCAAACACACCTCTTGTCTTT", "TGTGCTGTGAGAGGCCGTGTCACCAATGCAGGCAAATCAACCTTT", "TGTGCTGTCAGATCCGGTAACCAGTTCTATTTT", "TGTGCCGTGAACTCAAATTCCGGGTATGCACTCAACTTC", NA, "TGTGCCTTTGGAGGCCAGAAGCTGCTCTTT", "TGTGCTGTGGATACCAATGCAGGCAAATCAACCTTT", "TGCGCTGTGTTAATGGATAGCAGCTATAAATTGATCTTC", NA, "TGTGCTGTTGCATACTCTGGGGCTGGGAGTTACCAACTCACTTTC", "TGTGCTGTTTCAGGAAACACACCTCTTGTCTTT", NA, "TGTGCAACATCAGGAGGAAGCTACATACCTACATTT", "TGTGCTGTTAACTCAAATTCCGGGTATGCACTCAACTTC", "TGTGCTCTGAGTGAGGCTTATGGTGGTGCTACAAACAAGCTCATCTTT", "TGTGCTGTGAGAGACCCATACTCTGGGGCTGGGAGTTACCAACTCACTTTC", "TGTGCTGTGGGTGCCGAATACAACTTCAACAAATTTTACTTT", "TGTGCTGTTAATGCTGGTGGTACTAGCTATGGAAAGCTGACATTT", "TGTGCCCTTTCTGGTTCTGCAAGGCAACTGACCTTT", "TGTGCAGCTGTCGTGACTGGTGGTACTAGCTATGGAAAGCTGACATTT" ), TCR2 = c("TRBV2.NA.TRBJ2-5.TRBC2", "TRBV4-3.NA.TRBJ2-7.TRBC2", "TRBV5-5.NA.TRBJ1-2.TRBC1", "TRBV7-2.NA.TRBJ2-1.TRBC2", "TRBV7-2.TRBD1.TRBJ2-7.TRBC2", "TRBV3-1.NA.TRBJ2-1.TRBC2", "TRBV30.NA.TRBJ2-3.TRBC2", "TRBV29-1.TRBD1.TRBJ1-2.TRBC1", "TRBV28.NA.TRBJ2-6.TRBC2", "TRBV30.NA.TRBJ2-1.TRBC2", "TRBV5-4.NA.TRBJ2-3.TRBC2", "TRBV6-5.NA.TRBJ2-2.TRBC2", "TRBV25-1.NA.TRBJ2-1.TRBC2", "TRBV5-1.NA.TRBJ2-7.TRBC2", "TRBV24-1.NA.TRBJ2-1.TRBC2", "TRBV4-1.NA.TRBJ2-7.TRBC2", "TRBV5-4.NA.TRBJ2-3.TRBC2", "TRBV5-6.TRBD1.TRBJ2-1.TRBC2", "TRBV11-2.NA.TRBJ2-1.TRBC2", "TRBV19.NA.TRBJ1-2.TRBC1" ), cdr3_aa2 = c("CASSEPGVETQYF", "CASSQTRQAPYEQYF", "CASSLSTGANYGYTF", "CASSLDTYNEQFF", "CASSWTGGAYEQYV", "CASSQGGGPYNEQFF", "CAWSVLAGADTQYF", "CSVEQGANYGYTF", "CASRDGSGANVLTF", "CAWSWGFYNEQFF", "CASSLRGGTDTQYF", "CASSANTGELFF", "CASSASGGAYNEQFF", "CASSLGDSYEQYF", "CATSSGGYNEQFF", "CASSQDSTRYEQYF", "CASSLPGGRGTDTQYF", "CASSWTGGNEQFF", "CASSLGYNEQFF", "CASSVTDRGSYGYTF"), cdr3_nt2 = c("TGTGCCAGCAGTGAGCCGGGGGTAGAGACCCAGTACTTC", "TGCGCCAGCAGCCAAACCCGACAGGCTCCCTACGAGCAGTACTTC", "TGTGCCAGCAGCCTTTCGACAGGGGCTAACTATGGCTACACCTTC", "TGTGCCAGCAGCTTAGACACCTACAATGAGCAGTTCTTC", "TGTGCCAGCAGCTGGACAGGGGGCGCCTACGAGCAGTACGTC", "TGTGCCAGCAGCCAAGGGGGGGGCCCCTACAATGAGCAGTTCTTC", "TGTGCCTGGAGTGTACTAGCGGGGGCAGATACGCAGTATTTT", "TGCAGCGTTGAACAGGGGGCTAACTATGGCTACACCTTC", "TGTGCCAGCAGAGACGGCTCTGGGGCCAACGTCCTGACTTTC", "TGTGCCTGGAGTTGGGGTTTCTACAATGAGCAGTTCTTC", "TGTGCCAGCAGCTTGCGGGGGGGCACAGATACGCAGTATTTT", "TGTGCCAGCAGTGCGAACACCGGGGAGCTGTTTTTT", "TGTGCCAGCAGTGCTAGCGGGGGGGCCTACAATGAGCAGTTCTTC", "TGCGCCAGCAGCTTGGGGGACAGCTACGAGCAGTACTTC", "TGTGCCACTTCCAGCGGGGGGTACAATGAGCAGTTCTTC", "TGCGCCAGCAGCCAAGATTCGACCCGCTACGAGCAGTACTTC", "TGTGCCAGCAGCTTGCCGGGGGGCCGGGGCACAGATACGCAGTATTTT", "TGTGCCAGCAGCTGGACAGGGGGCAATGAGCAGTTCTTC", "TGTGCCAGCAGCTTAGGGTACAATGAGCAGTTCTTC", "TGTGCCAGTAGTGTTACCGACAGGGGAAGCTATGGCTACACCTTC"), CTgene = c("TRAV26-1.TRAJ29.TRAC_TRBV2.NA.TRBJ2-5.TRBC2", "TRAV21.TRAJ27.TRAC_TRBV4-3.NA.TRBJ2-7.TRBC2", "TRAV41.TRAJ49.TRAC_TRBV5-5.NA.TRBJ1-2.TRBC1", "TRAV12-2.TRAJ41.TRAC_TRBV7-2.NA.TRBJ2-1.TRBC2", "NA_TRBV7-2.TRBD1.TRBJ2-7.TRBC2", "TRAV24.TRAJ16.TRAC_TRBV3-1.NA.TRBJ2-1.TRBC2", "TRAV8-3.TRAJ27.TRAC_TRBV30.NA.TRBJ2-3.TRBC2", "TRAV1-1.TRAJ12.TRAC_TRBV29-1.TRBD1.TRBJ1-2.TRBC1", "NA_TRBV28.NA.TRBJ2-6.TRBC2", "TRAV35.TRAJ28.TRAC_TRBV30.NA.TRBJ2-1.TRBC2", "TRAV2.TRAJ29.TRAC_TRBV5-4.NA.TRBJ2-3.TRBC2", "NA_TRBV6-5.NA.TRBJ2-2.TRBC2", "TRAV13-1.TRAJ6.TRAC_TRBV25-1.NA.TRBJ2-1.TRBC2", "TRAV41.TRAJ41.TRAC_TRBV5-1.NA.TRBJ2-7.TRBC2", "TRAV19.TRAJ32.TRAC_TRBV24-1.NA.TRBJ2-1.TRBC2", "TRAV3.TRAJ28.TRAC_TRBV4-1.NA.TRBJ2-7.TRBC2", "TRAV8-3.TRAJ21.TRAC_TRBV5-4.NA.TRBJ2-3.TRBC2", "TRAV21.TRAJ52.TRAC_TRBV5-6.TRBD1.TRBJ2-1.TRBC2", "TRAV17.TRAJ22.TRAC_TRBV11-2.NA.TRBJ2-1.TRBC2", "TRAV13-1.TRAJ52.TRAC_TRBV19.NA.TRBJ1-2.TRBC1"), CTnt = c("TGCATCGCGCCTGACCCAAACACACCTCTTGTCTTT_TGTGCCAGCAGTGAGCCGGGGGTAGAGACCCAGTACTTC", "TGTGCTGTGAGAGGCCGTGTCACCAATGCAGGCAAATCAACCTTT_TGCGCCAGCAGCCAAACCCGACAGGCTCCCTACGAGCAGTACTTC", "TGTGCTGTCAGATCCGGTAACCAGTTCTATTTT_TGTGCCAGCAGCCTTTCGACAGGGGCTAACTATGGCTACACCTTC", "TGTGCCGTGAACTCAAATTCCGGGTATGCACTCAACTTC_TGTGCCAGCAGCTTAGACACCTACAATGAGCAGTTCTTC", "NA_TGTGCCAGCAGCTGGACAGGGGGCGCCTACGAGCAGTACGTC", "TGTGCCTTTGGAGGCCAGAAGCTGCTCTTT_TGTGCCAGCAGCCAAGGGGGGGGCCCCTACAATGAGCAGTTCTTC", "TGTGCTGTGGATACCAATGCAGGCAAATCAACCTTT_TGTGCCTGGAGTGTACTAGCGGGGGCAGATACGCAGTATTTT", "TGCGCTGTGTTAATGGATAGCAGCTATAAATTGATCTTC_TGCAGCGTTGAACAGGGGGCTAACTATGGCTACACCTTC", "NA_TGTGCCAGCAGAGACGGCTCTGGGGCCAACGTCCTGACTTTC", "TGTGCTGTTGCATACTCTGGGGCTGGGAGTTACCAACTCACTTTC_TGTGCCTGGAGTTGGGGTTTCTACAATGAGCAGTTCTTC", "TGTGCTGTTTCAGGAAACACACCTCTTGTCTTT_TGTGCCAGCAGCTTGCGGGGGGGCACAGATACGCAGTATTTT", "NA_TGTGCCAGCAGTGCGAACACCGGGGAGCTGTTTTTT", "TGTGCAACATCAGGAGGAAGCTACATACCTACATTT_TGTGCCAGCAGTGCTAGCGGGGGGGCCTACAATGAGCAGTTCTTC", "TGTGCTGTTAACTCAAATTCCGGGTATGCACTCAACTTC_TGCGCCAGCAGCTTGGGGGACAGCTACGAGCAGTACTTC", "TGTGCTCTGAGTGAGGCTTATGGTGGTGCTACAAACAAGCTCATCTTT_TGTGCCACTTCCAGCGGGGGGTACAATGAGCAGTTCTTC", "TGTGCTGTGAGAGACCCATACTCTGGGGCTGGGAGTTACCAACTCACTTTC_TGCGCCAGCAGCCAAGATTCGACCCGCTACGAGCAGTACTTC", "TGTGCTGTGGGTGCCGAATACAACTTCAACAAATTTTACTTT_TGTGCCAGCAGCTTGCCGGGGGGCCGGGGCACAGATACGCAGTATTTT", "TGTGCTGTTAATGCTGGTGGTACTAGCTATGGAAAGCTGACATTT_TGTGCCAGCAGCTGGACAGGGGGCAATGAGCAGTTCTTC", "TGTGCCCTTTCTGGTTCTGCAAGGCAACTGACCTTT_TGTGCCAGCAGCTTAGGGTACAATGAGCAGTTCTTC", "TGTGCAGCTGTCGTGACTGGTGGTACTAGCTATGGAAAGCTGACATTT_TGTGCCAGTAGTGTTACCGACAGGGGAAGCTATGGCTACACCTTC" ), CTaa = c("CIAPDPNTPLVF_CASSEPGVETQYF", "CAVRGRVTNAGKSTF_CASSQTRQAPYEQYF", "CAVRSGNQFYF_CASSLSTGANYGYTF", "CAVNSNSGYALNF_CASSLDTYNEQFF", "NA_CASSWTGGAYEQYV", "CAFGGQKLLF_CASSQGGGPYNEQFF", "CAVDTNAGKSTF_CAWSVLAGADTQYF", "CAVLMDSSYKLIF_CSVEQGANYGYTF", "NA_CASRDGSGANVLTF", "CAVAYSGAGSYQLTF_CAWSWGFYNEQFF", "CAVSGNTPLVF_CASSLRGGTDTQYF", "NA_CASSANTGELFF", "CATSGGSYIPTF_CASSASGGAYNEQFF", "CAVNSNSGYALNF_CASSLGDSYEQYF", "CALSEAYGGATNKLIF_CATSSGGYNEQFF", "CAVRDPYSGAGSYQLTF_CASSQDSTRYEQYF", "CAVGAEYNFNKFYF_CASSLPGGRGTDTQYF", "CAVNAGGTSYGKLTF_CASSWTGGNEQFF", "CALSGSARQLTF_CASSLGYNEQFF", "CAAVVTGGTSYGKLTF_CASSVTDRGSYGYTF"), CTstrict = c("TRAV26-1.TRAJ29.TRAC;TGCATCGCGCCTGACCCAAACACACCTCTTGTCTTT_TRBV2.NA.TRBJ2-5.TRBC2;TGTGCCAGCAGTGAGCCGGGGGTAGAGACCCAGTACTTC", "TRAV21.TRAJ27.TRAC;TGTGCTGTGAGAGGCCGTGTCACCAATGCAGGCAAATCAACCTTT_TRBV4-3.NA.TRBJ2-7.TRBC2;TGCGCCAGCAGCCAAACCCGACAGGCTCCCTACGAGCAGTACTTC", "TRAV41.TRAJ49.TRAC;TGTGCTGTCAGATCCGGTAACCAGTTCTATTTT_TRBV5-5.NA.TRBJ1-2.TRBC1;TGTGCCAGCAGCCTTTCGACAGGGGCTAACTATGGCTACACCTTC", "TRAV12-2.TRAJ41.TRAC;TGTGCCGTGAACTCAAATTCCGGGTATGCACTCAACTTC_TRBV7-2.NA.TRBJ2-1.TRBC2;TGTGCCAGCAGCTTAGACACCTACAATGAGCAGTTCTTC", "NA;NA_TRBV7-2.TRBD1.TRBJ2-7.TRBC2;TGTGCCAGCAGCTGGACAGGGGGCGCCTACGAGCAGTACGTC", "TRAV24.TRAJ16.TRAC;TGTGCCTTTGGAGGCCAGAAGCTGCTCTTT_TRBV3-1.NA.TRBJ2-1.TRBC2;TGTGCCAGCAGCCAAGGGGGGGGCCCCTACAATGAGCAGTTCTTC", "TRAV8-3.TRAJ27.TRAC;TGTGCTGTGGATACCAATGCAGGCAAATCAACCTTT_TRBV30.NA.TRBJ2-3.TRBC2;TGTGCCTGGAGTGTACTAGCGGGGGCAGATACGCAGTATTTT", "TRAV1-1.TRAJ12.TRAC;TGCGCTGTGTTAATGGATAGCAGCTATAAATTGATCTTC_TRBV29-1.TRBD1.TRBJ1-2.TRBC1;TGCAGCGTTGAACAGGGGGCTAACTATGGCTACACCTTC", "NA;NA_TRBV28.NA.TRBJ2-6.TRBC2;TGTGCCAGCAGAGACGGCTCTGGGGCCAACGTCCTGACTTTC", "TRAV35.TRAJ28.TRAC;TGTGCTGTTGCATACTCTGGGGCTGGGAGTTACCAACTCACTTTC_TRBV30.NA.TRBJ2-1.TRBC2;TGTGCCTGGAGTTGGGGTTTCTACAATGAGCAGTTCTTC", "TRAV2.TRAJ29.TRAC;TGTGCTGTTTCAGGAAACACACCTCTTGTCTTT_TRBV5-4.NA.TRBJ2-3.TRBC2;TGTGCCAGCAGCTTGCGGGGGGGCACAGATACGCAGTATTTT", "NA;NA_TRBV6-5.NA.TRBJ2-2.TRBC2;TGTGCCAGCAGTGCGAACACCGGGGAGCTGTTTTTT", "TRAV13-1.TRAJ6.TRAC;TGTGCAACATCAGGAGGAAGCTACATACCTACATTT_TRBV25-1.NA.TRBJ2-1.TRBC2;TGTGCCAGCAGTGCTAGCGGGGGGGCCTACAATGAGCAGTTCTTC", "TRAV41.TRAJ41.TRAC;TGTGCTGTTAACTCAAATTCCGGGTATGCACTCAACTTC_TRBV5-1.NA.TRBJ2-7.TRBC2;TGCGCCAGCAGCTTGGGGGACAGCTACGAGCAGTACTTC", "TRAV19.TRAJ32.TRAC;TGTGCTCTGAGTGAGGCTTATGGTGGTGCTACAAACAAGCTCATCTTT_TRBV24-1.NA.TRBJ2-1.TRBC2;TGTGCCACTTCCAGCGGGGGGTACAATGAGCAGTTCTTC", "TRAV3.TRAJ28.TRAC;TGTGCTGTGAGAGACCCATACTCTGGGGCTGGGAGTTACCAACTCACTTTC_TRBV4-1.NA.TRBJ2-7.TRBC2;TGCGCCAGCAGCCAAGATTCGACCCGCTACGAGCAGTACTTC", "TRAV8-3.TRAJ21.TRAC;TGTGCTGTGGGTGCCGAATACAACTTCAACAAATTTTACTTT_TRBV5-4.NA.TRBJ2-3.TRBC2;TGTGCCAGCAGCTTGCCGGGGGGCCGGGGCACAGATACGCAGTATTTT", "TRAV21.TRAJ52.TRAC;TGTGCTGTTAATGCTGGTGGTACTAGCTATGGAAAGCTGACATTT_TRBV5-6.TRBD1.TRBJ2-1.TRBC2;TGTGCCAGCAGCTGGACAGGGGGCAATGAGCAGTTCTTC", "TRAV17.TRAJ22.TRAC;TGTGCCCTTTCTGGTTCTGCAAGGCAACTGACCTTT_TRBV11-2.NA.TRBJ2-1.TRBC2;TGTGCCAGCAGCTTAGGGTACAATGAGCAGTTCTTC", "TRAV13-1.TRAJ52.TRAC;TGTGCAGCTGTCGTGACTGGTGGTACTAGCTATGGAAAGCTGACATTT_TRBV19.NA.TRBJ1-2.TRBC1;TGTGCCAGTAGTGTTACCGACAGGGGAAGCTATGGCTACACCTTC" ), donor_id = c("donor5", "unassigned", "donor5", "donor2", "donor4", "donor5", "doublet", "donor4", "donor2", "donor2", "donor1", "doublet", "donor0", NA, "donor4", "donor1", "doublet", "donor0", "donor5", NA)), row.names = c(NA, 20L), class = "data.frame")
Matrix products: default
locale: [1] LC_COLLATE=Dutch_Netherlands.utf8 LC_CTYPE=Dutch_Netherlands.utf8 LC_MONETARY=Dutch_Netherlands.utf8 [4] LC_NUMERIC=C LC_TIME=Dutch_Netherlands.utf8
time zone: Europe/Amsterdam tzcode source: internal
attached base packages: [1] stats4 stats graphics grDevices utils datasets methods base
other attached packages: [1] stringr_1.5.1 scRepertoire_2.0.4 DoubletFinder_2.0.4 abdiv_0.2.0.9000
[5] glmGamPoi_1.14.3 apeglm_1.24.0 tibble_3.2.1 DESeq2_1.42.0
[9] readxl_1.4.3 AUCell_1.24.0 clustree_0.5.1 ggraph_2.2.0
[13] MAST_1.28.0 SingleCellExperiment_1.24.0 SummarizedExperiment_1.32.0 Biobase_2.62.0
[17] GenomicRanges_1.54.1 GenomeInfoDb_1.38.6 IRanges_2.36.0 S4Vectors_0.40.2
[21] BiocGenerics_0.48.1 MatrixGenerics_1.14.0 matrixStats_1.2.0 patchwork_1.2.0
[25] Matrix_1.6-5 ggplot2_3.5.0 sctransform_0.4.1 dplyr_1.1.4
[29] Seurat_5.0.2 SeuratObject_5.0.1 sp_2.1-3
loaded via a namespace (and not attached): [1] spatstat.sparse_3.0-3 bitops_1.0-7 httr_1.4.7 RColorBrewer_1.1-3
[5] numDeriv_2016.8-1.1 tools_4.3.3 utf8_1.2.4 R6_2.5.1
[9] lazyeval_0.2.2 uwot_0.1.16 withr_3.0.0 gridExtra_2.3
[13] progressr_0.14.0 quantreg_5.98 cli_3.6.2 spatstat.explore_3.2-6
[17] fastDummies_1.7.3 iNEXT_3.0.1 mvtnorm_1.2-4 spatstat.data_3.1-2
[21] ggridges_0.5.6 pbapply_1.7-2 R.utils_2.12.3 stringdist_0.9.12
[25] parallelly_1.37.1 bbmle_1.0.25.1 VGAM_1.1-11 rstudioapi_0.16.0
[29] RSQLite_2.3.5 generics_0.1.3 ica_1.0-3 spatstat.random_3.2-3
[33] fansi_1.0.6 abind_1.4-5 R.methodsS3_1.8.2 terra_1.7-78
[37] lifecycle_1.0.4 SparseArray_1.2.4 Rtsne_0.17 grid_4.3.3
[41] blob_1.2.4 promises_1.2.1 crayon_1.5.3 bdsmatrix_1.3-7
[45] miniUI_0.1.1.1 lattice_0.22-5 cowplot_1.1.3 annotate_1.80.0
[49] KEGGREST_1.42.0 pillar_1.9.0 rjson_0.2.21 future.apply_1.11.2
[53] codetools_0.2-19 leiden_0.4.3.1 glue_1.7.0 data.table_1.15.2
[57] vctrs_0.6.5 png_0.1-8 spam_2.10-0 cellranger_1.1.0
[61] gtable_0.3.5 emdbook_1.3.13 cachem_1.0.8 S4Arrays_1.2.0
[65] mime_0.12 tidygraph_1.3.1 coda_0.19-4.1 survival_3.5-8
[69] fitdistrplus_1.1-11 ROCR_1.0-11 nlme_3.1-164 bit64_4.0.5
[73] RcppAnnoy_0.0.22 evd_2.3-7 irlba_2.3.5.1 KernSmooth_2.23-22
[77] colorspace_2.1-0 DBI_1.2.3 tidyselect_1.2.1 bit_4.0.5
[81] compiler_4.3.3 graph_1.80.0 SparseM_1.81 ggdendro_0.2.0
[85] DelayedArray_0.28.0 plotly_4.10.4 scales_1.3.0 lmtest_0.9-40
[89] digest_0.6.34 goftest_1.2-3 spatstat.utils_3.0-5 XVector_0.42.0
[93] htmltools_0.5.7 pkgconfig_2.0.3 sparseMatrixStats_1.14.0 fastmap_1.1.1
[97] rlang_1.1.3 htmlwidgets_1.6.4 shiny_1.8.1.1 DelayedMatrixStats_1.24.0 [101] farver_2.1.1 zoo_1.8-12 jsonlite_1.8.8 BiocParallel_1.36.0
[105] R.oo_1.26.0 RCurl_1.98-1.14 magrittr_2.0.3 GenomeInfoDbData_1.2.11
[109] dotCall64_1.1-1 munsell_0.5.1 Rcpp_1.0.12 evmix_2.12
[113] viridis_0.6.5 reticulate_1.35.0 truncdist_1.0-2 stringi_1.8.3
[117] ggalluvial_0.12.5 zlibbioc_1.48.0 MASS_7.3-60.0.1 plyr_1.8.9
[121] parallel_4.3.3 listenv_0.9.1 ggrepel_0.9.5 deldir_2.0-4
[125] Biostrings_2.70.2 graphlayouts_1.1.0 splines_4.3.3 hash_2.2.6.3
[129] tensor_1.5 locfit_1.5-9.9 igraph_2.0.2 spatstat.geom_3.2-9
[133] cubature_2.1.0 RcppHNSW_0.6.0 reshape2_1.4.4 XML_3.99-0.16.1
[137] tweenr_2.0.3 httpuv_1.6.14 MatrixModels_0.5-3 RANN_2.6.1
[141] tidyr_1.3.1 purrr_1.0.2 polyclip_1.10-6 future_1.33.2
[145] scattermore_1.2 ggforce_0.4.2 xtable_1.8-4 RSpectra_0.16-1
[149] later_1.3.2 viridisLite_0.4.2 gsl_2.1-8 memoise_2.0.1
[153] AnnotationDbi_1.64.1 cluster_2.1.6 globals_0.16.3 GSEABase_1.64.0