Last updated: 2022-07-07

Checks: 7 0

Knit directory: 20180328_Atkins_RatFracture/

This reproducible R Markdown analysis was created with workflowr (version 1.7.0). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.

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File Version Author Date Message
Rmd defc17e Steve Pederson 2022-07-07 Finished primary analysis
Rmd dd28879 Steve Pederson 2022-07-06 Setup initial DGE after restructure
html dd28879 Steve Pederson 2022-07-06 Setup initial DGE after restructure 
knitr::opts_chunk$set(
    message = FALSE, warning = FALSE,
    fig.height = 6, fig.width = 10
)
library(ngsReports)
library(tidyverse)
library(yaml)
library(scales)
library(pander)
library(glue)
library(plotly)
panderOptions("table.split.table", Inf)
panderOptions("big.mark", ",")
theme_set(theme_bw())
suffix <- "_L001_R1.fastq.gz"
pattern <- paste0("_CB2YGANXX_.+fastq.gz")
sp <- "Rnorvegicus"
samples <- "data/targets.csv" %>%
  here::here() %>%
  read_csv() %>% 
    mutate(
      Filename = paste0(File, suffix)
    )
group_cols <- hcl.colors(
  n = length(unique(samples$group)), 
  palette = "Zissou 1"
  ) %>%
  setNames(unique(samples$group))

Quality Assessment on Raw Data

rawFqc <- here::here("data/0_rawData/FastQC") %>%
  list.files(pattern = "zip", full.names = TRUE) %>%
  FastqcDataList() %>%
  .[fqName(.) %in% samples$Filename]
plotSummary(rawFqc, pattern = pattern)
*Overall summary of FastQC reports*

Overall summary of FastQC reports

Version Author Date
dd28879 Steve Pederson 2022-07-06

Library Sizes

A total of 6 libraries were contained in this dataset, with read totals ranging between 37,710,559 and 44,890,754 reads.

Across all libraries, reads were 100 bases.

plotReadTotals(rawFqc, pattern = pattern, usePlotly = TRUE)

Library Sizes for all supplied fastq files. Any samples run as multiple libraries are shown as the supplied multiple libraries and have not been merged.

Sequence Quality

plotBaseQuals(
  rawFqc,
  pattern = pattern, 
  usePlotly = TRUE,
  dendrogram = TRUE,
  cluster = TRUE
  )

Mean sequencing quality scores at each base position for each library

GC Content

plotGcContent(
  x = rawFqc, 
  pattern = pattern, 
  species = sp, 
  plotType = "line",
  gcType = "Trans",
  usePlotly = TRUE,
  dendrogram = TRUE,
  cluster = TRUE
  )

GC content shown as the % above and below the theoretical GC content for the Rnorvegicus transcriptome. The peaks at 62% and 71% are strongly suggestive of incomplete rRNA removal

Sequence Content

plotly::ggplotly(
  getModule(rawFqc, module = "Per_base_sequence_content") %>% 
    mutate(Base = fct_inorder(Base)) %>%
    group_by(Base) %>% 
    mutate(
      across(c("A", "C", "G", "T"), function(x){x - mean(x)}) 
    ) %>% 
    pivot_longer(
      cols = c("A", "C", "G", "T"), 
      names_to = "Nuc", 
      values_to = "resid"
    ) %>%
    left_join(samples) %>%
    ggplot(
      aes(Base, resid, group = Filename, colour = group)
    ) + 
    geom_line() +
    facet_wrap(~Nuc) + 
    scale_colour_manual(values = group_cols) +
    labs(
      x = "Read Position", y = "Residual", colour = "Group"
    ) +
    theme(
      axis.text.x = element_text(angle = 90, hjust = 1, vjust = 0.5)
    )
)

Base and Position specific residuals for each sample. The mean base content at each position was calculated for each nucleotide, and the sample-specific residuals calculated.

AdapterContent

plotAdapterContent(
  x = rawFqc, 
  pattern = pattern, 
  plotType = "line",
  dendrogram = TRUE,
  cluster = TRUE
  ) +
  scale_y_continuous(expand = expansion(c(0, 0)), limits = c(0, 10))
*Total Adapter Content for each sample shown by starting position in the read.*

Total Adapter Content for each sample shown by starting position in the read.

Version Author Date
dd28879 Steve Pederson 2022-07-06

Overrepresented Sequences

os <- suppressMessages(getModule(rawFqc, "Over"))
if (nrow(os)){
  if (length(unique(os$Filename)) > 1){
    suppressMessages(
      plotOverrep(
        x = rawFqc,
        pattern = suffix, 
        usePlotly = TRUE,
        dendrogram = TRUE,
        cluster = TRUE
      )
    )
  }
}

Summary of over-represented sequences across all libraries 

os %>%
  group_by(Sequence, Possible_Source) %>%
  summarise(
    `Found in` = n(),
    Total = sum(Count),
    `Largest Percent` = glue("{round(max(Percentage), 2)}%")
  ) %>%
  pander(
    caption = "*Summary of over-represented sequences within the raw data. Manual checking of over-represented sequences using BLAST indicated most were Ribosomal in origin*"
  )
Summary of over-represented sequences within the raw data. Manual checking of over-represented sequences using BLAST indicated most were Ribosomal in origin
Sequence Possible_Source Found in Total Largest Percent
ACCAGACTTGCCCTCCAATGGATCCTCGTTAAAGGATTTAAAGTGGACTC No Hit 1 45,817 0.1%
ACCAGGTCGATGCGTGGAGTGGACGGAGCAAGCTCCTATTCCAACTCCTA No Hit 6 1,602,565 1.18%
ACCGCGGCTGCTGGCACCAGACTTGCCCTCCAATGGATCCTCGTTAAAGG No Hit 1 47,849 0.11%
ACCGGGTTGGTTTTGATCTGATAAATGCACGCATCCCCCCCACGGGAAGG No Hit 1 65,603 0.15%
ACGACTTTTACTTCCTCTAGATAGTCAAGTTCGACCGTCTTCTCAGCGCT No Hit 1 65,230 0.15%
ACTCATTCCAATTACAGGGCCTCGAAAGAGTCCTGTATTGTTATTTTTCG No Hit 1 99,858 0.22%
AGACGTTCGAATGGGTCGTCGCCGCCACGGAGGGCGTGCGATCGGCCCGA No Hit 1 76,924 0.17%
CACAGTTATCCAAGTAGGAGAGGAGCGAGCGACCAAAGGAACCATAACTG No Hit 2 230,166 0.26%
CACCAGACTTGCCCTCCAATGGATCCTCGTTAAAGGATTTAAAGTGGACT No Hit 1 72,772 0.16%
CACCCCTCCTTAGGCAACCTGGTGGTCCCCCGCTCCCGGGAGGTCACCAT No Hit 6 824,551 0.52%
CACTACCACAAATTATGCAGTCGAGTTTCCCGCATTTGGGGAAATCGCAG No Hit 1 86,223 0.19%
CAGACGTTCGAATGGGTCGTCGCCGCCACGGAGGGCGTGCGATCGGCCCG No Hit 1 68,699 0.15%
CAGGTCGATGCGTGGAGTGGACGGAGCAAGCTCCTATTCCAACTCCTAGT No Hit 6 1,328,794 0.91%
CCACAGTTATCCAAGTAGGAGAGGAGCGAGCGACCAAAGGAACCATAACT No Hit 2 239,062 0.29%
CCACTACCACAAATTATGCAGTCGAGTTTCCCGCATTTGGGGAAATCGCA No Hit 1 98,089 0.22%
CCAGGTCGATGCGTGGAGTGGACGGAGCAAGCTCCTATTCCAACTCCTAG No Hit 3 414,384 0.39%
CCCACTACCACAAATTATGCAGTCGAGTTTCCCGCATTTGGGGAAATCGC No Hit 5 839,456 0.87%
CCCCACTACCACAAATTATGCAGTCGAGTTTCCCGCATTTGGGGAAATCG No Hit 5 1,131,951 1.18%
CCCCCACTACCACAAATTATGCAGTCGAGTTTCCCGCATTTGGGGAAATC No Hit 3 176,954 0.21%
CCCCGGCCGTCCCTCTTAATCATGGCCTCAGTTCCGAAAACCAACAAAAT No Hit 1 50,834 0.11%
CCCCTCCTTAGGCAACCTGGTGGTCCCCCGCTCCCGGGAGGTCACCATAT No Hit 6 2,575,389 1.38%
CCCGAGGTTATCTAGAGTCACCAAAGCCGCCGGCGCCCGACCCCCGGCCG No Hit 2 294,754 0.54%
CCCGCACTTACTGGGAATTCCTCGTTCATGGGGAATAATTGCAATCCCCG No Hit 1 54,847 0.12%
CCCGCATTTGGGGAAATCGCAGGGGTCAGCACATCCGGAGTGCAATGGAT No Hit 1 64,491 0.14%
CCCGGAAGCTGCCCGGCGGGTCATGGGAATAACGCCGCCGCATCGCCAGT No Hit 2 147,329 0.2%
CCCGGCCGTCCCTCTTAATCATGGCCTCAGTTCCGAAAACCAACAAAATA No Hit 2 155,547 0.22%
CCCGGGGCCGCAAGTGCGTTCGAAGTGTCGATGATCAATGTGTCCTGCAA No Hit 3 181,978 0.18%
CCCGGGTCGGGAGTGGGTAATTTGCGCGCCTGCTGCCTTCCTTGGATGTG No Hit 1 81,033 0.18%
CCCGTCACCCGTGGTCACCATGGTAGGCACGGCGACTACCATCGAAAGTT No Hit 1 57,751 0.13%
CCCGTCGGCATGTATTAGCTCTAGAATTACCACAGTTATCCAAGTAGGAG No Hit 2 341,322 0.48%
CCCGTGGTCACCATGGTAGGCACGGCGACTACCATCGAAAGTTGATAGGG No Hit 3 210,456 0.23%
CCCTCCTTAGGCAACCTGGTGGTCCCCCGCTCCCGGGAGGTCACCATATT No Hit 6 2,138,006 1.07%
CCGAGGTTATCTAGAGTCACCAAAGCCGCCGGCGCCCGACCCCCGGCCGG No Hit 1 108,328 0.24%
CCGGAAGCTGCCCGGCGGGTCATGGGAATAACGCCGCCGCATCGCCAGTC No Hit 1 76,694 0.17%
CCGGGTTGGTTTTGATCTGATAAATGCACGCATCCCCCCCACGGGAAGGG No Hit 2 128,537 0.19%
CCGTCGGCATGTATTAGCTCTAGAATTACCACAGTTATCCAAGTAGGAGA No Hit 2 212,925 0.29%
CCTCATTTGGATGTGTCTGGAGTCTTGGAAGCTTGACTACCCTACGTTCT No Hit 2 132,149 0.24%
CCTCCTTAGGCAACCTGGTGGTCCCCCGCTCCCGGGAGGTCACCATATTG No Hit 6 1,244,652 0.59%
CCTCGTTCATGGGGAATAATTGCAATCCCCGATCCCCATCACGAATGGGG No Hit 1 53,902 0.12%
CCTGCTTTGAACACTCTAATTTTTTCAAAGTAAACGCTTCGGGCCCCGCG No Hit 1 55,785 0.13%
CCTGTATTGTTATTTTTCGTCACTACCTCCCCGGGTCGGGAGTGGGTAAT No Hit 2 185,159 0.28%
CCTTAGGCAACCTGGTGGTCCCCCGCTCCCGGGAGGTCACCATATTGATG No Hit 6 1,363,560 0.76%
CCTTCCGTCAATTCCTTTAAGTTTCAGCTTTGCAACCATACTCCCCCCGG No Hit 1 76,012 0.17%
CGCCAGTCGGCATCGTTTATGGTCGGAACTACGACGGTATCTGATCGTCT No Hit 1 45,108 0.1%
CGCCTGCTGCCTTCCTTGGATGTGGTAGCCGTTTCTCAGGCTCCCTCTCC No Hit 2 211,183 0.31%
CGCGCCTGCTGCCTTCCTTGGATGTGGTAGCCGTTTCTCAGGCTCCCTCT No Hit 1 44,923 0.1%
CGCGGCTGCTGGCACCAGACTTGCCCTCCAATGGATCCTCGTTAAAGGAT No Hit 1 46,293 0.1%
CGCGTAACTAGTTAGCATGCCAGAGTCTCGTTCGTTATCGGAATTAACCA No Hit 1 101,017 0.23%
CGGGGAAGGTCGTCCTCTTCGACCGAGCGCGCAGCTTCGGGAGGGACGCA No Hit 1 81,803 0.22%
CGGGTTGGTTTTGATCTGATAAATGCACGCATCCCCCCCACGGGAAGGGG No Hit 1 49,280 0.11%
CGTCAATTCCTTTAAGTTTCAGCTTTGCAACCATACTCCCCCCGGAACCC No Hit 2 105,954 0.13%
CGTCGGCATGTATTAGCTCTAGAATTACCACAGTTATCCAAGTAGGAGAG No Hit 2 180,218 0.27%
CTAAGAAGTTGGGGGACGCCGACCGCTCGGGGGTCGCGTAACTAGTTAGC No Hit 1 77,886 0.17%
CTCAGTTCCGAAAACCAACAAAATAGAACCGCGGTCCTATTCCATTATTC No Hit 1 66,580 0.15%
CTCATTCCAATTACAGGGCCTCGAAAGAGTCCTGTATTGTTATTTTTCGT No Hit 1 101,980 0.23%
CTCATTTGGATGTGTCTGGAGTCTTGGAAGCTTGACTACCCTACGTTCTC No Hit 3 263,392 0.36%
CTCCAATGGATCCTCGTTAAAGGATTTAAAGTGGACTCATTCCAATTACA No Hit 1 61,149 0.14%
CTCCCATCCAAGTACTAACCAGGCCCGACCCTGCTTAGCTTCCGAGATCA No Hit 6 675,991 0.49%
CTCCGACTTTCGTTCTTGATTAATGAAAACATTCTTGGCAAATGCTTTCG No Hit 2 124,691 0.17%
CTCCGATTCTGCAATAGCAGGCTTGACCTGCCTTCACAACTGCATCTTGG No Hit 1 41,165 0.11%
CTCCGGAATCGAACCCTGATTCCCCGTCACCCGTGGTCACCATGGTAGGC No Hit 1 60,565 0.14%
CTCCGTTTCCGACCTGGGCCGGTTCACCCCTCCTTAGGCAACCTGGTGGT No Hit 6 684,533 0.45%
CTCCTATTCCAACTCCTAGTTCCAAAAATCCATTTAATATATTGTCCTCG No Hit 4 230,458 0.17%
CTCCTCTATTCGGGGAAGGTCGTCCTCTTCGACCGAGCGCGCAGCTTCGG No Hit 3 154,373 0.14%
CTCCTTAGGCAACCTGGTGGTCCCCCGCTCCCGGGAGGTCACCATATTGA No Hit 6 1,401,485 0.71%
CTCGCCACCAACATCATCAGGGTTCACCTTTCCCCACAGGCCATTAACAG No Hit 2 89,013 0.12%
CTCGTATACCCTTGACCGAAGACCGGTCCTCCTCTATTCGGGGAAGGTCG No Hit 1 49,929 0.11%
CTCGTTCATGGGGAATAATTGCAATCCCCGATCCCCATCACGAATGGGGT No Hit 1 88,581 0.2%
CTCGTTCGTTATCGGAATTAACCAGACAAATCGCTCCACCAACTAAGAAC No Hit 1 57,369 0.13%
CTCTAAGAAGTTGGGGGACGCCGACCGCTCGGGGGTCGCGTAACTAGTTA No Hit 1 61,916 0.14%
CTCTATTCGGGGAAGGTCGTCCTCTTCGACCGAGCGCGCAGCTTCGGGAG No Hit 1 45,048 0.1%
CTCTGGTCCGTCTTGCGCCGGTCCAAGAATTTCACCTCTAGCGGCGCAAT No Hit 1 129,334 0.29%
CTCTTAATCATGGCCTCAGTTCCGAAAACCAACAAAATAGAACCGCGGTC No Hit 3 443,318 0.57%
CTGCTCCGTTTCCGACCTGGGCCGGTTCACCCCTCCTTAGGCAACCTGGT No Hit 2 96,563 0.11%
CTGCTGCCTTCCTTGGATGTGGTAGCCGTTTCTCAGGCTCCCTCTCCGGA No Hit 2 218,958 0.33%
CTGGAGTCTTGGAAGCTTGACTACCCTACGTTCTCCTACAATGGACCTTG No Hit 5 1,176,836 1.08%
CTGTATTGTTATTTTTCGTCACTACCTCCCCGGGTCGGGAGTGGGTAATT No Hit 4 857,169 1.05%
CTTAATCATGGCCTCAGTTCCGAAAACCAACAAAATAGAACCGCGGTCCT No Hit 1 54,457 0.12%
CTTAGGCAACCTGGTGGTCCCCCGCTCCCGGGAGGTCACCATATTGATGC No Hit 6 386,884 0.23%
CTTCACCTTAGGGTTACCCATGATAGCAGAGGCAGAGGACAGGTCCCCAA No Hit 1 39,295 0.1%
CTTCCGTCAATTCCTTTAAGTTTCAGCTTTGCAACCATACTCCCCCCGGA No Hit 2 319,873 0.48%
CTTCCTTGGATGTGGTAGCCGTTTCTCAGGCTCCCTCTCCGGAATCGAAC No Hit 2 146,238 0.22%
CTTGATTAATGAAAACATTCTTGGCAAATGCTTTCGCTCTGGTCCGTCTT No Hit 1 164,171 0.37%
GCAGACGTTCGAATGGGTCGTCGCCGCCACGGAGGGCGTGCGATCGGCCC No Hit 1 79,199 0.18%
GCATCGTTTATGGTCGGAACTACGACGGTATCTGATCGTCTTCGAACCTC No Hit 1 54,697 0.12%
GCCAGAGTCTCGTTCGTTATCGGAATTAACCAGACAAATCGCTCCACCAA No Hit 1 56,084 0.12%
GCCCCTCCTTAGGCAACCTGGTGGTCCCCCGCTCCCGGGAGGTCACCATA No Hit 1 40,199 0.11%
GCCCGAGGTTATCTAGAGTCACCAAAGCCGCCGGCGCCCGACCCCCGGCC No Hit 1 119,886 0.27%
GCCCTTCCGTCAATTCCTTTAAGTTTCAGCTTTGCAACCATACTCCCCCC No Hit 1 78,539 0.18%
GCCGGCTTCACGCTCAGGAGGGGACGCTATGTCTCGTCCTCGTGGTTTCG No Hit 1 43,693 0.11%
GCCTCAGTTCCGAAAACCAACAAAATAGAACCGCGGTCCTATTCCATTAT No Hit 2 172,403 0.23%
GCCTCATTTGGATGTGTCTGGAGTCTTGGAAGCTTGACTACCCTACGTTC No Hit 1 74,957 0.2%
GCCTGCTGCCTTCCTTGGATGTGGTAGCCGTTTCTCAGGCTCCCTCTCCG No Hit 3 484,746 0.61%
GCCTTCCTTGGATGTGGTAGCCGTTTCTCAGGCTCCCTCTCCGGAATCGA No Hit 2 127,409 0.19%
GCGCCTGCTGCCTTCCTTGGATGTGGTAGCCGTTTCTCAGGCTCCCTCTC No Hit 2 135,401 0.2%
GCGGTGTGTACAAAGGGCAGGGACTTAATCAACGCAAGCTTATGACCCGC No Hit 1 49,415 0.11%
GCTCAATCTCGGGTGGCTGAACGCCACTTGTCCCTCTAAGAAGTTGGGGG No Hit 1 49,062 0.11%
GCTCCGTTTCCGACCTGGGCCGGTTCACCCCTCCTTAGGCAACCTGGTGG No Hit 6 413,413 0.23%
GGACGCACATGGAGCGGTGAGGGAGGAAGGGGACACCCGCCTAGCCAGCC No Hit 2 99,505 0.15%
GGACTCATTCCAATTACAGGGCCTCGAAAGAGTCCTGTATTGTTATTTTT No Hit 1 73,056 0.16%
GGAGGTTCTAGCAGGGGAGCGCAGCTACTCGTATACCCTTGACCGAAGAC No Hit 1 79,903 0.21%
GGCAGACGTTCGAATGGGTCGTCGCCGCCACGGAGGGCGTGCGATCGGCC No Hit 4 1,365,014 1.98%
GGCATCGTTTATGGTCGGAACTACGACGGTATCTGATCGTCTTCGAACCT No Hit 1 49,624 0.11%
GGCCTCAGTTCCGAAAACCAACAAAATAGAACCGCGGTCCTATTCCATTA No Hit 1 52,967 0.12%
GGCGGTGTGTACAAAGGGCAGGGACTTAATCAACGCAAGCTTATGACCCG No Hit 1 79,266 0.18%
GGGGAAGGTCGTCCTCTTCGACCGAGCGCGCAGCTTCGGGAGGGACGCAC No Hit 1 52,057 0.14%
GGGGCTTACATCAATGTGAGAGAAGTAGGTCTTGGTGGTGGGGAAGGCAG No Hit 1 39,514 0.1%
GGGGGGTCAGCGCCCGTCGGCATGTATTAGCTCTAGAATTACCACAGTTA No Hit 2 207,892 0.27%
GGGGGTCAGCGCCCGTCGGCATGTATTAGCTCTAGAATTACCACAGTTAT No Hit 1 52,050 0.12%
GGGGTCAGCGCCCGTCGGCATGTATTAGCTCTAGAATTACCACAGTTATC No Hit 2 113,824 0.13%
GGGTCGATGCGTGGAGTGGACGGAGCAAGCTCCTATTCCAACTCCTAGTT No Hit 1 52,061 0.14%
GGGTCGCGTAACTAGTTAGCATGCCAGAGTCTCGTTCGTTATCGGAATTA No Hit 1 68,510 0.15%
GGTCGATGCGTGGAGTGGACGGAGCAAGCTCCTATTCCAACTCCTAGTTC No Hit 6 1,539,951 1.09%
GGTGCCCTTCCGTCAATTCCTTTAAGTTTCAGCTTTGCAACCATACTCCC No Hit 1 47,955 0.11%
GTACAAAGGGCAGGGACTTAATCAACGCAAGCTTATGACCCGCACTTACT No Hit 1 80,575 0.18%
GTATTGTTATTTTTCGTCACTACCTCCCCGGGTCGGGAGTGGGTAATTTG No Hit 1 65,065 0.15%
GTCAATTCCTTTAAGTTTCAGCTTTGCAACCATACTCCCCCCGGAACCCA No Hit 2 109,533 0.12%
GTCACTACCTCCCCGGGTCGGGAGTGGGTAATTTGCGCGCCTGCTGCCTT No Hit 1 69,064 0.15%
GTCCCCCACTACCACAAATTATGCAGTCGAGTTTCCCGCATTTGGGGAAA No Hit 4 472,827 0.46%
GTCCCTCTTAATCATGGCCTCAGTTCCGAAAACCAACAAAATAGAACCGC No Hit 2 167,043 0.24%
GTCCTGTATTGTTATTTTTCGTCACTACCTCCCCGGGTCGGGAGTGGGTA No Hit 4 612,866 0.66%
GTCGATGCGTGGAGTGGACGGAGCAAGCTCCTATTCCAACTCCTAGTTCC No Hit 6 1,390,188 0.95%
GTCGCGTAACTAGTTAGCATGCCAGAGTCTCGTTCGTTATCGGAATTAAC No Hit 1 174,882 0.39%
GTCGGCATCGTTTATGGTCGGAACTACGACGGTATCTGATCGTCTTCGAA No Hit 1 61,947 0.14%
GTCGGCATGTATTAGCTCTAGAATTACCACAGTTATCCAAGTAGGAGAGG No Hit 4 877,632 1%
GTCTGGAGTCTTGGAAGCTTGACTACCCTACGTTCTCCTACAATGGACCT No Hit 5 805,129 0.76%
GTGCCCTTCCGTCAATTCCTTTAAGTTTCAGCTTTGCAACCATACTCCCC No Hit 2 206,070 0.31%
GTGCGATCGGCCCGAGGTTATCTAGAGTCACCAAAGCCGCCGGCGCCCGA No Hit 1 50,483 0.11%
GTGGACTCATTCCAATTACAGGGCCTCGAAAGAGTCCTGTATTGTTATTT No Hit 1 57,242 0.13%
GTGGCTATTCACAGGCGCGATCCCACTACTGATCAGCACGGGAGTTTTGA No Hit 2 139,349 0.22%
GTGTGTACAAAGGGCAGGGACTTAATCAACGCAAGCTTATGACCCGCACT No Hit 1 73,383 0.16%
GTTATTTTTCGTCACTACCTCCCCGGGTCGGGAGTGGGTAATTTGCGCGC No Hit 1 46,188 0.1%
GTTCGAAGTGTCGATGATCAATGTGTCCTGCAATTCACATTAATTCTCGC No Hit 1 57,777 0.13%
GTTCGTTATCGGAATTAACCAGACAAATCGCTCCACCAACTAAGAACGGC No Hit 1 84,329 0.19%
GTTCTTGATTAATGAAAACATTCTTGGCAAATGCTTTCGCTCTGGTCCGT No Hit 1 77,063 0.17%
GTTGGTTTTGATCTGATAAATGCACGCATCCCCCCCACGGGAAGGGGGGT No Hit 2 174,018 0.2%
TCCTTAGGCAACCTGGTGGTCCCCCGCTCCCGGGAGGTCACCATATTGAT No Hit 3 158,106 0.14%
TCTTAATCATGGCCTCAGTTCCGAAAACCAACAAAATAGAACCGCGGTCC No Hit 1 58,599 0.13%

R version 4.2.0 (2022-04-22)

Platform: x86_64-pc-linux-gnu (64-bit)

locale: LC_CTYPE=en_AU.UTF-8, LC_NUMERIC=C, LC_TIME=en_AU.UTF-8, LC_COLLATE=en_AU.UTF-8, LC_MONETARY=en_AU.UTF-8, LC_MESSAGES=en_AU.UTF-8, LC_PAPER=en_AU.UTF-8, LC_NAME=C, LC_ADDRESS=C, LC_TELEPHONE=C, LC_MEASUREMENT=en_AU.UTF-8 and LC_IDENTIFICATION=C

attached base packages: stats, graphics, grDevices, utils, datasets, methods and base

other attached packages: plotly(v.4.10.0), glue(v.1.6.2), pander(v.0.6.5), scales(v.1.2.0), yaml(v.2.3.5), forcats(v.0.5.1), stringr(v.1.4.0), dplyr(v.1.0.9), purrr(v.0.3.4), readr(v.2.1.2), tidyr(v.1.2.0), tidyverse(v.1.3.1), ngsReports(v.1.13.0), tibble(v.3.1.7), ggplot2(v.3.3.6), BiocGenerics(v.0.42.0) and workflowr(v.1.7.0)

loaded via a namespace (and not attached): bitops(v.1.0-7), fs(v.1.5.2), bit64(v.4.0.5), lubridate(v.1.8.0), RColorBrewer(v.1.1-3), httr(v.1.4.3), rprojroot(v.2.0.3), GenomeInfoDb(v.1.32.1), tools(v.4.2.0), backports(v.1.4.1), bslib(v.0.3.1), utf8(v.1.2.2), R6(v.2.5.1), DT(v.0.22), DBI(v.1.1.2), lazyeval(v.0.2.2), colorspace(v.2.0-3), withr(v.2.5.0), tidyselect(v.1.1.2), processx(v.3.5.3), bit(v.4.0.4), compiler(v.4.2.0), git2r(v.0.30.1), rvest(v.1.0.2), cli(v.3.3.0), xml2(v.1.3.3), ggdendro(v.0.1.23), labeling(v.0.4.2), sass(v.0.4.1), callr(v.3.7.0), digest(v.0.6.29), rmarkdown(v.2.14), XVector(v.0.36.0), pkgconfig(v.2.0.3), htmltools(v.0.5.2), highr(v.0.9), dbplyr(v.2.1.1), fastmap(v.1.1.0), htmlwidgets(v.1.5.4), rlang(v.1.0.2), readxl(v.1.4.0), rstudioapi(v.0.13), farver(v.2.1.0), jquerylib(v.0.1.4), generics(v.0.1.2), zoo(v.1.8-10), jsonlite(v.1.8.0), crosstalk(v.1.2.0), vroom(v.1.5.7), RCurl(v.1.98-1.6), magrittr(v.2.0.3), GenomeInfoDbData(v.1.2.8), Rcpp(v.1.0.8.3), munsell(v.0.5.0), S4Vectors(v.0.34.0), fansi(v.1.0.3), lifecycle(v.1.0.1), stringi(v.1.7.6), whisker(v.0.4), MASS(v.7.3-57), zlibbioc(v.1.42.0), plyr(v.1.8.7), grid(v.4.2.0), parallel(v.4.2.0), promises(v.1.2.0.1), crayon(v.1.5.1), lattice(v.0.20-45), Biostrings(v.2.64.0), haven(v.2.5.0), hms(v.1.1.1), knitr(v.1.39), ps(v.1.7.0), pillar(v.1.7.0), reshape2(v.1.4.4), stats4(v.4.2.0), reprex(v.2.0.1), evaluate(v.0.15), getPass(v.0.2-2), data.table(v.1.14.2), modelr(v.0.1.8), vctrs(v.0.4.1), tzdb(v.0.3.0), httpuv(v.1.6.5), cellranger(v.1.1.0), gtable(v.0.3.0), assertthat(v.0.2.1), xfun(v.0.30), broom(v.0.8.0), later(v.1.3.0), viridisLite(v.0.4.0), IRanges(v.2.30.0), ellipsis(v.0.3.2) and here(v.1.0.1)


sessionInfo()
R version 4.2.0 (2022-04-22)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.4 LTS

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0

locale:
 [1] LC_CTYPE=en_AU.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_AU.UTF-8        LC_COLLATE=en_AU.UTF-8    
 [5] LC_MONETARY=en_AU.UTF-8    LC_MESSAGES=en_AU.UTF-8   
 [7] LC_PAPER=en_AU.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_AU.UTF-8 LC_IDENTIFICATION=C       

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

other attached packages:
 [1] plotly_4.10.0       glue_1.6.2          pander_0.6.5       
 [4] scales_1.2.0        yaml_2.3.5          forcats_0.5.1      
 [7] stringr_1.4.0       dplyr_1.0.9         purrr_0.3.4        
[10] readr_2.1.2         tidyr_1.2.0         tidyverse_1.3.1    
[13] ngsReports_1.13.0   tibble_3.1.7        ggplot2_3.3.6      
[16] BiocGenerics_0.42.0 workflowr_1.7.0    

loaded via a namespace (and not attached):
 [1] bitops_1.0-7           fs_1.5.2               bit64_4.0.5           
 [4] lubridate_1.8.0        RColorBrewer_1.1-3     httr_1.4.3            
 [7] rprojroot_2.0.3        GenomeInfoDb_1.32.1    tools_4.2.0           
[10] backports_1.4.1        bslib_0.3.1            utf8_1.2.2            
[13] R6_2.5.1               DT_0.22                DBI_1.1.2             
[16] lazyeval_0.2.2         colorspace_2.0-3       withr_2.5.0           
[19] tidyselect_1.1.2       processx_3.5.3         bit_4.0.4             
[22] compiler_4.2.0         git2r_0.30.1           rvest_1.0.2           
[25] cli_3.3.0              xml2_1.3.3             ggdendro_0.1.23       
[28] labeling_0.4.2         sass_0.4.1             callr_3.7.0           
[31] digest_0.6.29          rmarkdown_2.14         XVector_0.36.0        
[34] pkgconfig_2.0.3        htmltools_0.5.2        highr_0.9             
[37] dbplyr_2.1.1           fastmap_1.1.0          htmlwidgets_1.5.4     
[40] rlang_1.0.2            readxl_1.4.0           rstudioapi_0.13       
[43] farver_2.1.0           jquerylib_0.1.4        generics_0.1.2        
[46] zoo_1.8-10             jsonlite_1.8.0         crosstalk_1.2.0       
[49] vroom_1.5.7            RCurl_1.98-1.6         magrittr_2.0.3        
[52] GenomeInfoDbData_1.2.8 Rcpp_1.0.8.3           munsell_0.5.0         
[55] S4Vectors_0.34.0       fansi_1.0.3            lifecycle_1.0.1       
[58] stringi_1.7.6          whisker_0.4            MASS_7.3-57           
[61] zlibbioc_1.42.0        plyr_1.8.7             grid_4.2.0            
[64] parallel_4.2.0         promises_1.2.0.1       crayon_1.5.1          
[67] lattice_0.20-45        Biostrings_2.64.0      haven_2.5.0           
[70] hms_1.1.1              knitr_1.39             ps_1.7.0              
[73] pillar_1.7.0           reshape2_1.4.4         stats4_4.2.0          
[76] reprex_2.0.1           evaluate_0.15          getPass_0.2-2         
[79] data.table_1.14.2      modelr_0.1.8           vctrs_0.4.1           
[82] tzdb_0.3.0             httpuv_1.6.5           cellranger_1.1.0      
[85] gtable_0.3.0           assertthat_0.2.1       xfun_0.30             
[88] broom_0.8.0            later_1.3.0            viridisLite_0.4.0     
[91] IRanges_2.30.0         ellipsis_0.3.2         here_1.0.1