Create Illumina Sample Sheet and metadata

How to use this

To run this Rmarkdown, open it in Rstudio and from the knit drop-down menu, choose Knit with parameters

What does this do

It creates the Illumina Sample sheet and the metadata.csv file that you need for running the pipeline. You need to double check the output - weird things happen all the time.

Required input

You need an input file with at least the following columns:

Sample_name: Avoid spaces - for compatibility with MiSeq’s sample sheet, use hyphen “-” instead of underscores "_" or full stops “.”
Well: in the 96-well plate used for the Nextera reaction.
PrimerF: using IUPAC wildcard character
PrimerR: ditto
Locus: Name of the locus, again without spaces.
i7_Index_Name: Adapter used to identify samples. Format is N7XX
i5_Index_Name: Adapter used to identify samples. Format is N5XX

Load the Illumina adapters

Nextera_Adapters_i7 <- read_csv(here("data_sub","Nextera_adapters_i7.csv"))

## Parsed with column specification:
## cols(
##   i7_Index_Name = col_character(),
##   Bases_in_Adapter_i7 = col_character(),
##   Bases_for_Sample_Sheet_i7 = col_character()
## )

Nextera_Adapters_i5 <- read_csv(here("data_sub","Nextera_adapters_i5.csv"))

## Parsed with column specification:
## cols(
##   i5_Index_Name = col_character(),
##   Bases_in_Adapter_i5 = col_character(),
##   Bases_for_Sample_Sheet_i5 = col_character()
## )

Loading the metadata you want to sequence

init.metadata <- read_csv(params$input.metadata)

## Parsed with column specification:
## cols(
##   Sample_name = col_character(),
##   Well = col_character(),
##   Row = col_character(),
##   Column = col_double(),
##   i7_Index_Name = col_character(),
##   i5_Index_Name = col_character(),
##   Qubit = col_double(),
##   PrimerF = col_character(),
##   PrimerR = col_character(),
##   Locus = col_character()
## )

init.metadata

## # A tibble: 88 x 10
##    Sample_name Well  Row   Column i7_Index_Name i5_Index_Name Qubit PrimerF
##    <chr>       <chr> <chr>  <dbl> <chr>         <chr>         <dbl> <chr>  
##  1 Sample_1_C… A1    A          1 N701          N502           4.78 GGWACW…
##  2 Sample_2_C… B1    B          1 N701          N503           5.43 GGWACW…
##  3 Sample_7_C… C1    C          1 N701          N504          13.4  GGWACW…
##  4 Tilapia_CO… D1    D          1 N701          N505          11    GGWACW…
##  5 Sample_24_… E1    E          1 N701          N506           0.8  GGWACW…
##  6 Sample_48_… F1    F          1 N701          N507           6.4  GGWACW…
##  7 Sample_33_… G1    G          1 N701          N508           6.6  GGWACW…
##  8 Sample_35_… H1    H          1 N701          N517           3.75 GGWACW…
##  9 Sample_39_… A2    A          2 N702          N502           1.07 GGWACW…
## 10 Sample_38_… B2    B          2 N702          N503           3.01 GGWACW…
## # … with 78 more rows, and 2 more variables: PrimerR <chr>, Locus <chr>

Check that the metadata has all needed fields

init.metadata %>% 
  rownames_to_column("Sample_number") %>% 
  mutate_all(as.character) %>% 
  pivot_longer(-Sample_number, names_to = "Variable", values_to = "Value") %>% 
  summarise(Sample_name = case_when(sum(str_detect(Variable, "Sample")) > 0 ~ "Present",
                                 TRUE                                    ~ "Absent"),
         Well        = case_when(sum(str_detect(Variable, "Well")) > 0 ~ "Present",
                                 TRUE                                    ~ "Absent"),
         PrimerF    = case_when(sum(str_detect(Variable, "PrimerF")) > 0 ~ "Present",
                                 TRUE                                    ~ "Absent"),
         PrimerR    = case_when(sum(str_detect(Variable, "PrimerR")) > 0 ~ "Present",
                                 TRUE                                    ~ "Absent"),
         
         i5_Adapter  = case_when(sum(str_detect(Variable, "i5_Index_Name")) > 0 ~ "Present",
                                 TRUE                                    ~ "Absent"),
         i7_Adapter  = case_when(sum(str_detect(Variable, "i7_Index_Name")) > 0 ~ "Present",
                                 TRUE                                    ~ "Absent")) -> Checks
  


if(sum(str_detect(Checks,"Absent")) > 0){ knitr::knit_exit(append = "## ERROR: Initial metadata is missing some of the key column names: 

                                                           - Sample_name
                                                           - Well
                                                           - PrimerF
                                                           - PrimerR
                                                           - Plate
                                                           - i5_Index_Name
                                                           - i7_Index_Name
                                                           
                                                           ### Change the column names / add the infromation to your csv file")}

The i5 and i7 indices can start by either N, S, or H. But the sequence is the same. Let’s make sure that they are compatible with the Nextera Indices file

init.metadata %>% 
  mutate(i5_Index_Name = str_replace(i5_Index_Name, "^[EHNS]", "N"),
         i7_Index_Name = str_replace(i7_Index_Name, "^[HN]", "N")) -> init.metadata

Make the check that all the indices are present

case_when(nrow(anti_join(init.metadata, Nextera_Adapters_i5)) + nrow(anti_join(init.metadata, Nextera_Adapters_i7)) == 0 ~ "All indices present in the  dataset",
           # == 0 ~ "Pass i7",
          TRUE                                                     ~ "Either some of the i5 or the i7 indices are not present in the Nextera Indices list - That will result in NAs in the final Sample Sheet")

## Joining, by = "i5_Index_Name"

## Joining, by = "i7_Index_Name"

## [1] "All indices present in the  dataset"

Load the Illumina SampleSheet template

template.sample.sheet <- read_lines(here("data_sub","SampleSheet.csv"))

Locate all the lines in which the new parameters are going to be written

date.row  <- str_which(template.sample.sheet, "^\\Date")
Assay.row <- str_which(template.sample.sheet, "^Assay")
Index.row <- str_which(template.sample.sheet, "^Index Adapters")
Reads.row <- str_which(template.sample.sheet, "^\\[Reads]")
data.start <- str_which(template.sample.sheet, "^\\[Data]")
data.header <- str_which(template.sample.sheet, "^Sample_ID")

Merge metadata with illumina adapters

init.metadata %>% 
  left_join(Nextera_Adapters_i7) %>% 
  left_join(Nextera_Adapters_i5) -> metadata

## Joining, by = "i7_Index_Name"

## Joining, by = "i5_Index_Name"

Fill Illumina SampleSheet

In the case where there are many loci represented on each sample, usually you have them in the same well. If this is the case, your Illumina samplesheet will have fewer entries (rows) than your metadata sheet. In the Illumina sampleSheet, there are two parts: one that refers to the whole plate, and one that specificies the samples run.

Parameters that refer to the whole sequencing run

These include date of analysis,

template.sample.sheet[date.row] <- paste0("Date,",params$date)

template.sample.sheet[Assay.row] <- paste0("Assay," ,params$Assay)
template.sample.sheet[Index.row] <- paste0("Index Adapters,",params$Index_Adapters)
template.sample.sheet[Reads.row +1 ] <- template.sample.sheet[Reads.row + 2] <- params$Cycles_per_pairend

Then with the rest of the dataset - collapsing first by primers

metadata %>% 
  group_by( i5_Index_Name,i7_Index_Name ) %>% 
  tally() -> occurrence.of.combos

if(max(occurrence.of.combos$n > 1 )){
  print("There are combinations of barcodes assigned to more than 1 sample - Please Check they have different PCR primers so you can separate them after")
  metadata %>% 
  group_by(i5_Adapter,i7_Adapter ) %>% 
    slice(1) -> metadata.for.sample.sheet
  print ("Keeping the first occurence of each combo for your samplesheet")}else{metadata.for.sample.sheet <- metadata}

Fill in metadata

We are going to assume that the Illumina always returns files with the format Sample_name Sample_number _L001_R [1-2] ’_001.fastq`. So let’s fill the metadata accordingly.

Step1 Get the filenames

sample.data %>% 
  mutate(Sample_name = str_replace_all(Sample_ID,pattern = "[\\.|_]",replacement = "-")) %>%
  rownames_to_column("Sample_number") %>% 
  mutate(file1 = paste0(Sample_name, "_S", Sample_number, "_L001_R1_001.fastq"),
         file2 = paste0(Sample_name, "_S", Sample_number, "_L001_R2_001.fastq")) %>% 
  select(i7_Index_Name = I7_Index_ID, i5_Index_Name = I5_Index_ID, file1, file2) -> filenames

## Joining, by = c("i7_Index_Name", "i5_Index_Name")

Check that primer sequences do not include non-IUPAC characters

IUAPAC.char <- read_csv(here("data_sub","IUAPAC.csv"))

## Parsed with column specification:
## cols(
##   Nucleotide.symbol = col_character(),
##   Full.Name = col_character()
## )

IUPAC.char.1 <- paste(IUAPAC.char$Nucleotide.symbol, collapse = "")
IUPAC.char.1 <- paste0("[^",IUPAC.char.1,"]")

allprimers = paste0(metadata$PrimerR, metadata$PrimerF, collapse = "")

case_when(str_count(allprimers, IUPAC.char.1) > 0 ~ print("There are non-IUAPAC characters in your primers, changing them to N"))

## [1] "There are non-IUAPAC characters in your primers, changing them to N"

## [1] "There are non-IUAPAC characters in your primers, changing them to N"

metadata %>% 
  mutate_at(.vars = vars(starts_with("Primer")), function(x)str_replace_all(x, IUPAC.char.1, "N")) -> metadata

write_csv(metadata, file.path(params$output_dir,paste0( "metadata_",Sys.Date(),".csv")))

kable(metadata, align= "c", format = "html") %>%
      kable_styling(bootstrap_options= "striped", fixed_thead = T,full_width = T, position = "center") %>%
      column_spec(2, bold=T) %>%
  scroll_box(width = "1200px", height = "600px")

Sample_name	file1	file2	i7_Index_Name	i5_Index_Name	Well	PrimerF	PrimerR	Locus
Sample_1_COI.1	Sample-1-COI-1_S1_L001_R1_001.fastq	Sample-1-COI-1_S1_L001_R2_001.fastq	N701	N502	A1	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_2_COI.1	Sample-2-COI-1_S2_L001_R1_001.fastq	Sample-2-COI-1_S2_L001_R2_001.fastq	N701	N503	B1	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_7_COI.1	Sample-7-COI-1_S3_L001_R1_001.fastq	Sample-7-COI-1_S3_L001_R2_001.fastq	N701	N504	C1	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Tilapia_COI.2	Tilapia-COI-2_S4_L001_R1_001.fastq	Tilapia-COI-2_S4_L001_R2_001.fastq	N701	N505	D1	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_24_COI.1	Sample-24-COI-1_S5_L001_R1_001.fastq	Sample-24-COI-1_S5_L001_R2_001.fastq	N701	N506	E1	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_48_COI.1	Sample-48-COI-1_S6_L001_R1_001.fastq	Sample-48-COI-1_S6_L001_R2_001.fastq	N701	N507	F1	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_33_COI.1	Sample-33-COI-1_S7_L001_R1_001.fastq	Sample-33-COI-1_S7_L001_R2_001.fastq	N701	N508	G1	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_35_COI.1	Sample-35-COI-1_S8_L001_R1_001.fastq	Sample-35-COI-1_S8_L001_R2_001.fastq	N701	N517	H1	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_39_COI.1	Sample-39-COI-1_S9_L001_R1_001.fastq	Sample-39-COI-1_S9_L001_R2_001.fastq	N702	N502	A2	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_38_COI.1	Sample-38-COI-1_S10_L001_R1_001.fastq	Sample-38-COI-1_S10_L001_R2_001.fastq	N702	N503	B2	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_41_COI.1	Sample-41-COI-1_S11_L001_R1_001.fastq	Sample-41-COI-1_S11_L001_R2_001.fastq	N702	N504	C2	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_44_COI.1	Sample-44-COI-1_S12_L001_R1_001.fastq	Sample-44-COI-1_S12_L001_R2_001.fastq	N702	N505	D2	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_45_COI.1	Sample-45-COI-1_S13_L001_R1_001.fastq	Sample-45-COI-1_S13_L001_R2_001.fastq	N702	N506	E2	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_46_COI.1	Sample-46-COI-1_S14_L001_R1_001.fastq	Sample-46-COI-1_S14_L001_R2_001.fastq	N702	N507	F2	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_52_COI.1	Sample-52-COI-1_S15_L001_R1_001.fastq	Sample-52-COI-1_S15_L001_R2_001.fastq	N702	N508	G2	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_161_COI.1	Sample-161-COI-1_S16_L001_R1_001.fastq	Sample-161-COI-1_S16_L001_R2_001.fastq	N702	N517	H2	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_53_COI.1	Sample-53-COI-1_S17_L001_R1_001.fastq	Sample-53-COI-1_S17_L001_R2_001.fastq	N712	N502	A3	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_55_COI.1	Sample-55-COI-1_S18_L001_R1_001.fastq	Sample-55-COI-1_S18_L001_R2_001.fastq	N712	N503	B3	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_57_COI.1	Sample-57-COI-1_S19_L001_R1_001.fastq	Sample-57-COI-1_S19_L001_R2_001.fastq	N712	N504	C3	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_59_COI.1	Sample-59-COI-1_S20_L001_R1_001.fastq	Sample-59-COI-1_S20_L001_R2_001.fastq	N712	N505	D3	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_62_COI.1	Sample-62-COI-1_S21_L001_R1_001.fastq	Sample-62-COI-1_S21_L001_R2_001.fastq	N712	N506	E3	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_60_COI.1	Sample-60-COI-1_S22_L001_R1_001.fastq	Sample-60-COI-1_S22_L001_R2_001.fastq	N712	N507	F3	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_63_COI.1	Sample-63-COI-1_S23_L001_R1_001.fastq	Sample-63-COI-1_S23_L001_R2_001.fastq	N712	N508	G3	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_65_COI.1	Sample-65-COI-1_S24_L001_R1_001.fastq	Sample-65-COI-1_S24_L001_R2_001.fastq	N712	N517	H3	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_67_COI.1	Sample-67-COI-1_S25_L001_R1_001.fastq	Sample-67-COI-1_S25_L001_R2_001.fastq	N704	N502	A4	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_68_COI.1	Sample-68-COI-1_S26_L001_R1_001.fastq	Sample-68-COI-1_S26_L001_R2_001.fastq	N704	N503	B4	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_70_COI.1	Sample-70-COI-1_S27_L001_R1_001.fastq	Sample-70-COI-1_S27_L001_R2_001.fastq	N704	N504	C4	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_72_COI.1	Sample-72-COI-1_S28_L001_R1_001.fastq	Sample-72-COI-1_S28_L001_R2_001.fastq	N704	N505	D4	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_74_COI.1	Sample-74-COI-1_S29_L001_R1_001.fastq	Sample-74-COI-1_S29_L001_R2_001.fastq	N704	N506	E4	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_77_COI.1	Sample-77-COI-1_S30_L001_R1_001.fastq	Sample-77-COI-1_S30_L001_R2_001.fastq	N704	N507	F4	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_79_COI.1	Sample-79-COI-1_S31_L001_R1_001.fastq	Sample-79-COI-1_S31_L001_R2_001.fastq	N704	N508	G4	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_76_COI.1	Sample-76-COI-1_S32_L001_R1_001.fastq	Sample-76-COI-1_S32_L001_R2_001.fastq	N704	N517	H4	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_1_COI.2	Sample-1-COI-2_S33_L001_R1_001.fastq	Sample-1-COI-2_S33_L001_R2_001.fastq	N705	N502	A5	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_2_COI.2	Sample-2-COI-2_S34_L001_R1_001.fastq	Sample-2-COI-2_S34_L001_R2_001.fastq	N705	N503	B5	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_7_COI.2	Sample-7-COI-2_S35_L001_R1_001.fastq	Sample-7-COI-2_S35_L001_R2_001.fastq	N705	N504	C5	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_19_COI.2	Sample-19-COI-2_S36_L001_R1_001.fastq	Sample-19-COI-2_S36_L001_R2_001.fastq	N705	N505	D5	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_24_COI.2	Sample-24-COI-2_S37_L001_R1_001.fastq	Sample-24-COI-2_S37_L001_R2_001.fastq	N705	N506	E5	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_48_COI.2	Sample-48-COI-2_S38_L001_R1_001.fastq	Sample-48-COI-2_S38_L001_R2_001.fastq	N705	N507	F5	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_33_COI.2	Sample-33-COI-2_S39_L001_R1_001.fastq	Sample-33-COI-2_S39_L001_R2_001.fastq	N705	N508	G5	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_35_COI.2	Sample-35-COI-2_S40_L001_R1_001.fastq	Sample-35-COI-2_S40_L001_R2_001.fastq	N705	N517	H5	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_39_COI.2	Sample-39-COI-2_S41_L001_R1_001.fastq	Sample-39-COI-2_S41_L001_R2_001.fastq	N706	N502	A6	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_38_COI.2	Sample-38-COI-2_S42_L001_R1_001.fastq	Sample-38-COI-2_S42_L001_R2_001.fastq	N706	N503	B6	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_41_COI.2	Sample-41-COI-2_S43_L001_R1_001.fastq	Sample-41-COI-2_S43_L001_R2_001.fastq	N706	N504	C6	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_44_COI.2	Sample-44-COI-2_S44_L001_R1_001.fastq	Sample-44-COI-2_S44_L001_R2_001.fastq	N706	N505	D6	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_45_COI.2	Sample-45-COI-2_S45_L001_R1_001.fastq	Sample-45-COI-2_S45_L001_R2_001.fastq	N706	N506	E6	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_46_COI.2	Sample-46-COI-2_S46_L001_R1_001.fastq	Sample-46-COI-2_S46_L001_R2_001.fastq	N706	N507	F6	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_52_COI.2	Sample-52-COI-2_S47_L001_R1_001.fastq	Sample-52-COI-2_S47_L001_R2_001.fastq	N706	N508	G6	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_161_COI.2	Sample-161-COI-2_S48_L001_R1_001.fastq	Sample-161-COI-2_S48_L001_R2_001.fastq	N706	N517	H6	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_53_COI.2	Sample-53-COI-2_S49_L001_R1_001.fastq	Sample-53-COI-2_S49_L001_R2_001.fastq	N707	N502	A7	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_55_COI.2	Sample-55-COI-2_S50_L001_R1_001.fastq	Sample-55-COI-2_S50_L001_R2_001.fastq	N707	N503	B7	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_57_COI.2	Sample-57-COI-2_S51_L001_R1_001.fastq	Sample-57-COI-2_S51_L001_R2_001.fastq	N707	N504	C7	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_59_COI.2	Sample-59-COI-2_S52_L001_R1_001.fastq	Sample-59-COI-2_S52_L001_R2_001.fastq	N707	N505	D7	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_62_COI.2	Sample-62-COI-2_S53_L001_R1_001.fastq	Sample-62-COI-2_S53_L001_R2_001.fastq	N707	N506	E7	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_60_COI.2	Sample-60-COI-2_S54_L001_R1_001.fastq	Sample-60-COI-2_S54_L001_R2_001.fastq	N707	N507	F7	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_63_COI.2	Sample-63-COI-2_S55_L001_R1_001.fastq	Sample-63-COI-2_S55_L001_R2_001.fastq	N707	N508	G7	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_65_COI.2	Sample-65-COI-2_S56_L001_R1_001.fastq	Sample-65-COI-2_S56_L001_R2_001.fastq	N707	N517	H7	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_67_COI.2	Sample-67-COI-2_S57_L001_R1_001.fastq	Sample-67-COI-2_S57_L001_R2_001.fastq	N708	N502	A8	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_68_COI.2	Sample-68-COI-2_S58_L001_R1_001.fastq	Sample-68-COI-2_S58_L001_R2_001.fastq	N708	N503	B8	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_70_COI.2	Sample-70-COI-2_S59_L001_R1_001.fastq	Sample-70-COI-2_S59_L001_R2_001.fastq	N708	N504	C8	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_72_COI.2	Sample-72-COI-2_S60_L001_R1_001.fastq	Sample-72-COI-2_S60_L001_R2_001.fastq	N708	N505	D8	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_74_COI.2	Sample-74-COI-2_S61_L001_R1_001.fastq	Sample-74-COI-2_S61_L001_R2_001.fastq	N708	N506	E8	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_77_COI.2	Sample-77-COI-2_S62_L001_R1_001.fastq	Sample-77-COI-2_S62_L001_R2_001.fastq	N708	N507	F8	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_79_COI.2	Sample-79-COI-2_S63_L001_R1_001.fastq	Sample-79-COI-2_S63_L001_R2_001.fastq	N708	N508	G8	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_76_COI.2	Sample-76-COI-2_S64_L001_R1_001.fastq	Sample-76-COI-2_S64_L001_R2_001.fastq	N715	N517	H8	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Tilapia_COI.1	Tilapia-COI-1_S65_L001_R1_001.fastq	Tilapia-COI-1_S65_L001_R2_001.fastq	N709	N502	A9	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_51_COI.1	Sample-51-COI-1_S66_L001_R1_001.fastq	Sample-51-COI-1_S66_L001_R2_001.fastq	N709	N503	B9	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_51_COI.2	Sample-51-COI-2_S67_L001_R1_001.fastq	Sample-51-COI-2_S67_L001_R2_001.fastq	N709	N504	C9	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_19_COI.1	Sample-19-COI-1_S68_L001_R1_001.fastq	Sample-19-COI-1_S68_L001_R2_001.fastq	N709	N505	D9	GGWACWGGWTGAACWGTWTAYCCYCC	GTANACYTCNGGRTGNCCRAARAAYCA	COI_Leray
Sample_33_16S.1	Sample-33-16S-1_S69_L001_R1_001.fastq	Sample-33-16S-1_S69_L001_R2_001.fastq	N709	N506	E9	GYAATCACTTGTCTTTTAAATGAAGACC	GGATTGCGCTGTTATCCCTA	16S_Prey
Sample_33_16S.2	Sample-33-16S-2_S70_L001_R1_001.fastq	Sample-33-16S-2_S70_L001_R2_001.fastq	N709	N507	F9	GYAATCACTTGTCTTTTAAATGAAGACC	GGATTGCGCTGTTATCCCTA	16S_Prey
Sample_20_16S.1	Sample-20-16S-1_S71_L001_R1_001.fastq	Sample-20-16S-1_S71_L001_R2_001.fastq	N709	N508	G9	GYAATCACTTGTCTTTTAAATGAAGACC	GGATTGCGCTGTTATCCCTA	16S_Prey
Sample_38_16S.1	Sample-38-16S-1_S72_L001_R1_001.fastq	Sample-38-16S-1_S72_L001_R2_001.fastq	N709	N517	H9	GYAATCACTTGTCTTTTAAATGAAGACC	GGATTGCGCTGTTATCCCTA	16S_Prey
Sample_38_16S.2	Sample-38-16S-2_S73_L001_R1_001.fastq	Sample-38-16S-2_S73_L001_R2_001.fastq	N710	N502	A10	GYAATCACTTGTCTTTTAAATGAAGACC	GGATTGCGCTGTTATCCCTA	16S_Prey
Sample_38_16S.3	Sample-38-16S-3_S74_L001_R1_001.fastq	Sample-38-16S-3_S74_L001_R2_001.fastq	N710	N503	B10	GYAATCACTTGTCTTTTAAATGAAGACC	GGATTGCGCTGTTATCCCTA	16S_Prey
Sample_25_16S.1	Sample-25-16S-1_S75_L001_R1_001.fastq	Sample-25-16S-1_S75_L001_R2_001.fastq	N710	N504	C10	GYAATCACTTGTCTTTTAAATGAAGACC	GGATTGCGCTGTTATCCCTA	16S_Prey
Sample_39_16S.1	Sample-39-16S-1_S76_L001_R1_001.fastq	Sample-39-16S-1_S76_L001_R2_001.fastq	N710	N505	D10	GYAATCACTTGTCTTTTAAATGAAGACC	GGATTGCGCTGTTATCCCTA	16S_Prey
Sample_39_16S.2	Sample-39-16S-2_S77_L001_R1_001.fastq	Sample-39-16S-2_S77_L001_R2_001.fastq	N710	N506	E10	GYAATCACTTGTCTTTTAAATGAAGACC	GGATTGCGCTGTTATCCCTA	16S_Prey
Sample_39_16S.3	Sample-39-16S-3_S78_L001_R1_001.fastq	Sample-39-16S-3_S78_L001_R2_001.fastq	N710	N507	F10	GYAATCACTTGTCTTTTAAATGAAGACC	GGATTGCGCTGTTATCCCTA	16S_Prey
Tilapia_16S.1	Tilapia-16S-1_S79_L001_R1_001.fastq	Tilapia-16S-1_S79_L001_R2_001.fastq	N710	N508	G10	GYAATCACTTGTCTTTTAAATGAAGACC	GGATTGCGCTGTTATCCCTA	16S_Prey
Sample_48_16S.1	Sample-48-16S-1_S80_L001_R1_001.fastq	Sample-48-16S-1_S80_L001_R2_001.fastq	N710	N517	H10	GYAATCACTTGTCTTTTAAATGAAGACC	GGATTGCGCTGTTATCCCTA	16S_Prey
Sample_72_16S.1	Sample-72-16S-1_S81_L001_R1_001.fastq	Sample-72-16S-1_S81_L001_R2_001.fastq	N711	N502	A11	GYAATCACTTGTCTTTTAAATGAAGACC	GGATTGCGCTGTTATCCCTA	16S_Prey
Sample_72_16S.2	Sample-72-16S-2_S82_L001_R1_001.fastq	Sample-72-16S-2_S82_L001_R2_001.fastq	N711	N503	B11	GYAATCACTTGTCTTTTAAATGAAGACC	GGATTGCGCTGTTATCCCTA	16S_Prey
Sample_72_16S.3	Sample-72-16S-3_S83_L001_R1_001.fastq	Sample-72-16S-3_S83_L001_R2_001.fastq	N711	N504	C11	GYAATCACTTGTCTTTTAAATGAAGACC	GGATTGCGCTGTTATCCCTA	16S_Prey
Sample_77_16S.1	Sample-77-16S-1_S84_L001_R1_001.fastq	Sample-77-16S-1_S84_L001_R2_001.fastq	N711	N505	D11	GYAATCACTTGTCTTTTAAATGAAGACC	GGATTGCGCTGTTATCCCTA	16S_Prey
Sample_79_16S.1	Sample-79-16S-1_S85_L001_R1_001.fastq	Sample-79-16S-1_S85_L001_R2_001.fastq	N711	N506	E11	GYAATCACTTGTCTTTTAAATGAAGACC	GGATTGCGCTGTTATCCCTA	16S_Prey
Sample_79_16S.2	Sample-79-16S-2_S86_L001_R1_001.fastq	Sample-79-16S-2_S86_L001_R2_001.fastq	N711	N507	F11	GYAATCACTTGTCTTTTAAATGAAGACC	GGATTGCGCTGTTATCCCTA	16S_Prey
Sample_32_16S.1	Sample-32-16S-1_S87_L001_R1_001.fastq	Sample-32-16S-1_S87_L001_R2_001.fastq	N711	N508	G11	GYAATCACTTGTCTTTTAAATGAAGACC	GGATTGCGCTGTTATCCCTA	16S_Prey
Tilapia_16S.2	Tilapia-16S-2_S88_L001_R1_001.fastq	Tilapia-16S-2_S88_L001_R2_001.fastq	N711	N517	H11	GYAATCACTTGTCTTTTAAATGAAGACC	GGATTGCGCTGTTATCCCTA	16S_Prey