In MANO-B/MicroSEC: Sequence Error Filter for Formalin-Fixed and Paraffin-Embedded Samples

Introduction

This pipeline is designed for filtering mutations found in formalin-fixed and paraffin-embedded (FFPE) samples. The MicroSEC filter utilizes a statistical analysis, and the results for mutations with less than 10 supporting reads are not reliable. Four files are necessary for the analysis: mutation information file, BAM file, and mutation supporting read ID information file.

File 1: mutation information file (mandatory)

This tsv or tsv.gz file should contain at least these columns: Sample Mut_type Chr Pos Ref Alt SimpleRepeat_TRF Neighborhood_sequence
sample_name 1-snv chr1 108130741 C T N CTACCTGGAGAATGGGCCCATGTGTCCAGGTAGCAGTAAGC
SimpleRepeat_TRF: Whether the mutation locates at a simple repeat sequence or not ("Y" or "N").
Neighborhood_sequence: [5'-20 bases] + [Alt sequence] + [3'-20 bases]
Sample, Mut_type, Chr, Pos, Ref, and Alt should be set exactly.
If you do not know the SimpleRepeat_TRF, Mut_type, or Neighborhood_sequence, enter "-". Automatically detected.

File 2: BAM file (mandatory)

File 3: sample information tsv file

(mandatory, if multiple samples are processed in a batch)
Seven to ten columns are necessary (without column names).
Optional columns can be deleted if they are not applicable.
[sample name] [mutation information tsv file] [BAM file] [read length] [adapter sequence read 1] [optional: adapter sequence read 2] [sample type: Human or Mouse] [panel name] [optional: reference genome fastq file] [optional: simple repeat region bed file]
PC9 ./source/CCLE.tsv ./source/Cell_line/PC9.bam 127 AGATCGGAAGAGCACACGTCTGAACTCCAGTCA AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGT Human TOP
A375 ./source/CCLE.tsv.gz ./source/Cell_line/A375.bam 127 AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGT Hg38 TOP ./reference/hg38.fa ./reference/simpleRepeat.bed.gz

File 4: Reference genome: Human (hg38 or hg19) or Mouse (mm10)

(optional, but mandatory with cram files)

File 5: simple repeat region bed file

(optional, but mandatory to detect simple repeat derived artifacts)

This pipeline contains 8 filtering processes.
Filter 1 : Shorter-supporting lengths distribute too unevenly to occur (1-1 and 1-2).
Filter 1-1: P-values are less than the threshold_p(default: 10^(-6)).
Filter 1-2: The shorter-supporting lengths distributed over less than 75% of the read length.
Filter 2 : Hairpin-structure induced error detection (2-1 and 2-2).
Filter 2-1: Palindromic sequences exist within 150 bases. Filter 2-2: >=50% mutation-supporting reads contains a reverse complementary sequence of the opposite strand consisting >= 15 bases.
Filter 3 : 3’-/5’-supporting lengths are too unevenly distributed to occur (3-1 and 3-3).
Filter 3-1: P-values are less than the threshold_p(default: 10^(-6)).
Filter 3-2: The distributions of 3’-/5’-supporting lengths are within 75% of the read length.
Filter 4 : >=15% mutations were called by chimeric reads comprising two distant regions.
Filter 5 : >=50% mutations were called by soft-clipped reads.
Filter 6 : Mutations locating at simple repeat sequences.
Filter 7 : Mutations locating at a >=15 homopolymer.
Filter 8 : >=10% low quality bases (Quality score <18) in the mutation supporting reads.

Supporting lengths are adjusted considering small repeat sequences around the mutations.

How to use

Rscript MicroSEC.R [working/output directory] [sample information tsv file] [progress bar Y/N]

Example

$ Rscript MicroSEC.R ~ \
  ~/source/Sample_list_test.txt N
$ Rscript MicroSEC.R ~ \
   ~/source/sample_info_test.tsv.gz Y

If you want to know the progress visually, [progress bar Y/N] should be Y.
Results are saved in a tsv file.

github url: https://github.com/MANO-B/MicroSEC

Setting

wd <- "~"
knitr::opts_chunk$set(collapse = TRUE,
                      fig.width = 12,
                      fig.height = 8,
                      echo = TRUE,
                      warning = FALSE,
                      message = TRUE,
                      comment = "#>")
options(rmarkdown.html_vignette.check_title = FALSE,
        show.error.messages = FALSE,
        warn = -1)

progress_bar <- "N"

Necessary packages

library(MicroSEC)

Analysis

# initialize
msec <- NULL
homology_search <- NULL
mut_depth <- NULL

# test data
sample_name <- "sample"
read_length <- 150
adapter_1 <- "AGATCGGAAGAGCACACGTCTGAACTCCAGTCA"
adapter_2 <- "AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGT"
organism <- "hg38"

# load mutation information
df_mutation <- fun_load_mutation(
   system.file("extdata", "mutation_list.tsv", package = "MicroSEC"),
   "sample",
   BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38,
   24)
df_bam <- fun_load_bam(
   system.file("extdata", "sample.bam", package = "MicroSEC"))

# another example data
# data(exampleMutation)
# data(exampleBam)
# df_mutation <- exampleMutation
# df_bam <- exampleBam

# load genomic sequence
ref_genome <- fun_load_genome(organism)
chr_no <- fun_load_chr_no(organism)

# analysis
result <- fun_read_check(df_mutation = df_mutation,
                         df_bam = df_bam,
                         ref_genome = ref_genome,
                         sample_name = sample_name,
                         read_length = read_length,
                         adapter_1 = adapter_1,
                         adapter_2 = adapter_2,
                         short_homology_search_length = 4,
                         min_homology_search = 40,
                         progress_bar = progress_bar)
msec_read_checked <- result[[1]]
homology_searched <- result[[2]]
mut_depth_checked <- result[[3]]

# search homologous sequences
msec_homology_searched = fun_homology(msec = msec_read_checked,
                    df_distant = homology_searched,
                    min_homology_search = 40,
                    ref_genome = ref_genome,
                    chr_no = chr_no,
                    progress_bar = progress_bar)

# statistical analysis
msec_summarized <- fun_summary(msec_homology_searched)
msec_analyzed <- fun_analysis(msec = msec_summarized,
                    mut_depth = mut_depth_checked,
                    short_homology_search_length = 4,
                    min_homology_search = 40,
                    threshold_p = 10 ^ (-6),
                    threshold_hairpin_ratio = 0.50,
                    threshold_short_length = 0.75,
                    threshold_distant_homology = 0.15,
                    threshold_soft_clip_ratio = 0.50,
                    threshold_low_quality_rate = 0.1,
                    homopolymer_length = 15)

# save the results as a tsv.gz file.
#fun_save(msec_analyzed, "~/MicroSEC_test.tsv.gz")

Results

msec_analyzed

Information about the current R session

sessionInfo()

MANO-B/MicroSEC documentation built on Dec. 30, 2024, 4:11 a.m.