[R] Truncation of character fields in a data frame

[Luigi Marongiu]

Dear all,
I am reading a txt file into the R environment to create a data frame,
however I have notice that some entries have a truncated version of a
field, so for instance I get "Astro" instead of "Astro 1-Astro 1" and
"Sapo" for "Sapo #1-Sapo_1" and "Sapo #2-Sapo_2", but I also get
"Adeno 40/41 EH-Adeno_40-41_EH" so the problem is not in the spaces
between the words. The txt file is a simple tab delimited file
generated from excel which I read with:

bad.data<-read.table(
    "test_df.txt",
    header=TRUE,
    row.names=1,
    dec = ".",
    sep="\t",
    stringsAsFactors = FALSE,
    fill = TRUE
)

[the fill = TRUE was introduced because in the real case I got an
error of a missing line.]

I can recreate this file as follows:
sample <- c(rep("p.001", 48), rep("p.547", 48))
target <- c("Adeno 1-Adeno 1",    "Adeno 40/41 EH-AIQJCT3",    "Astro
1-Astro 1",    "Sapo 1-Sapo 1",    "Sapo 2-Sapo 2",    "Enterovirus
1-Enterovirus 1",    "Parechovirus-Parechovirus",    "HEV 1-HEV 1",
"IC PDV control-AIRSA0B",    "Rotavirus cam-Rotavirus cam",
"18S-Hs99999901_s1",    "Noro gp II-Noro gp II",    "Noro gp 1-Noro gp
1",    "Noro gp 1 mod33-Noro gp 1 mod33",    "C difficile
GDH-AIS086J",    "C difficile Tox B-C difficile Tox B",    "VTX
1-AIT97CR",    "BT control Man-AIVI5IZ",    "E. coli vtx 2-E. coli vtx
2",    "Campy spp-AIWR3O7",    "Salmonella ttr-AIX01VF",    "Crypto
CP2-AIY9Z1N",    "Green Fluorescent Protein-AI0IX7V",    "Adeno
2-Adeno 2",    "Adeno 40_41 Oly-AI1RWD3",    "Astro 2 Liu-AI20UKB",
"Giardia lambia 1-AI39SQJ",    "Rotavirus Liu-Rotavirus Liu 2",
"Enterovirus Bruges-Enterovirus 2 Br",    "HAV 1-Hepatitis A 1",
"HEV 2-AI5IQWR",    "MS2 control-AI6RO2Z",    "Rotarix NSP2-AI70M87",
  "CMV br-CMV br",    "IC Rnase P-AI89LFF",    "Salmonella hil
A-Salmonella hil A",    "Shigella ipa H-AIAA0K8",    "Enteroagg E.
coli-AIBJYRG",    "Campy jejuni-AICSWXO",    "Campy coli-AID1U3W",
"Yersinia enterocolitica-AIFAS94",    "Bacterial 16S-Bacterial 16S",
 "Aeromonas hydrophilia-Aeromonas hydrophilia",    "V
cholerae-AIGJRGC",    "Dientamoeba fragilis-AIHSPMK",    "Entamoeba
histolytica-AII1NSS",    "Crypto 2 J-AIKALY0",    "Giardia lambia
rev-AILJJ48",    "Adeno #1-Adeno_1",    "Adeno 40/41
EH-Adeno_40-41_EH",    "Astro #1-Astro_1",    "Sapo #1-Sapo_1",
"Sapo #2-Sapo_2",    "Enterovirus #1-Enterovirus_1",
"Parechovirus-Parechovirus",    "HEV #1-HEV_1",    "C coli jejuni
Liu-C_coli_jejuni_Li",    "Rotavirus cam-Rotavirus_cam",    "IC 18s-IC
18s",    "Noro gp II-Noro_gp_II",    "Noro gp 1-Noro_gp_1",    "Noro
gp 1 mod33-Noro_gp_1_mod33",    "C difficile GDH-C-difficile_GDH",
"C difficile Tox B-C_difficile_T_B",    "E. coli vtx 1-E_coli_vtx_1",
  "BT control Man-BT_control_Man",    "E. coli vtx 2-E_coli_vtx_2",
"Campy spp NEW-Campy_spp_NEW",    "Salmonella ttr-Salmonella_ttr",
"Cryptosporidium spp CP2-Cryptos_spp_CP2",    "C jejuni
#2-C_jejuni_2",    "Adeno #2-Adeno_2",    "Adeno 40/41
Oly-Adeno_40-41_Oly",    "Astro Liu #2-Astro_Liu_2",    "Giardia
lambia #1-Giardia_lambia_1",    "Rotavirus Liu #2-Rotavirus_Liu_2",
"Enterovirus #2 Br-Enterovirus_2_Br",    "Hepatitis A
#1-Hepatitis_A_1",    "HEV #2-HEV_2",    "MS2 control-MS2_control",
"Rotarix NSP2 Bris-Rotarix_NSP2_Bri",    "CMV br-CMV_br",    "Rnase P
control-Rnase_P_control",    "Salmonella hil A-Salmonella_hil_A",
"Shigella ipa H-Shigella_ipa_H",    "Enteroagg E.
coli-Enteroagg_E_coli",    "V parahaemolyticus-V_p_haemolyticus",
"Campy coli-Campy_coli",    "Yersinia
enterocolitica-Y_enterocolitica",    "Bacterial 16S-Bacterial_16S",
"Aeromonas hydrophilia-Aero_hydrophilia",    "Vibrio
cholerae-Vibrio_cholerae",    "Dientamoeba fragilis-Dien_fragilis",
"Entamoeba histolytica-Enta_histolytica",    "Cryptosporidium spp #2
J-Crypto_spp_2_J",    "Giardia lambia #2 rev-Giardia_lambia_r")
ct <- c(NA,    NA,    NA,    NA,    NA,    NA,    NA,    NA,    NA,
NA,    18.793,    NA,    NA,    NA,    NA,    NA,    NA,    33.302,
NA,    32.388,    NA,    NA,    NA,    NA,    NA,    NA,    NA,    NA,
   NA,    NA,    NA,    31.398,    NA,    NA,    NA,    NA,    NA,
NA,    NA,    NA,    NA,    8.115,    NA,    NA,    NA,    NA,    NA,
  NA,    NA,    NA,    NA,    NA,    NA,    NA,    NA,    NA,    NA,
 NA,    21.161,    NA,    NA,    NA,    NA,    NA,    NA,    31.302,
 NA,    29.785,    NA,    NA,    NA,    NA,    NA,    NA,    NA,
NA,    NA,    NA,    NA,    31.212,    42.967,    NA,    33.503,
NA,    NA,    NA,    NA,    NA,    NA,    9.584,    NA,    NA,    NA,
  NA,    NA,    NA)

good.data <- data.frame(sample, target, ct, stringsAsFactors = FALSE)

and the structure of these object is the same:
> str(good.data)
'data.frame':    96 obs. of  3 variables:
 $ sample: chr  "p.001" "p.001" "p.001" "p.001" ...
 $ target: chr  "Adeno 1-Adeno 1" "Adeno 40/41 EH-AIQJCT3" "Astro
1-Astro 1" "Sapo 1-Sapo 1" ...
 $ ct    : num  NA NA NA NA NA NA NA NA NA NA ...
> str(bad.data)
'data.frame':    96 obs. of  3 variables:
 $ Sample: chr  "p.001" "p.001" "p.001" "p.001" ...
 $ Target: chr  "Adeno 1-Adeno 1" "Adeno 40/41 EH-AIQJCT3" "Astro
1-Astro 1" "Sapo 1-Sapo 1" ...
 $ Ct    : num  NA NA NA NA NA NA NA NA NA NA ...

however in the good.data case the problem with truncation does not
occur, so for instance I get the required "Astro #1-Astro_1", "Sapo
#1-Sapo_1" and "Sapo #2-Sapo_2 ".
The problem must therefore be in the format of the txt file and the
read function, possibly in the # character present in the names.
Could somebody explain me what such problem is and how to avoid it?
Many thanks
Best regards
Luigi