File size: 5,869 Bytes
746e176 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 | # ── Subset full HCC1143 BAMs to chr17 for pipeline development ───────────────
# Input: full WES BAMs (wherever you downloaded them)
# Output: hcc1143_T_clean.bam / hcc1143_N_clean.bam (chr17 only)
#
# Why chr17: TP53 is on chr17 — the known HCC1143 driver mutation
# we use as our validated anchor epitope. Subsetting to chr17 keeps
# the test data small (~50MB vs ~23GB) while retaining the mutation
# we actually care about.
# ─────────────────────────────────────────────────────────────────────────────
TUMOR_FULL=~/melanoma-pipeline/data/full/hcc1143_T_clean.bam
NORMAL_FULL=~/melanoma-pipeline/data/full/hcc1143_N_clean.bam
OUT=~/melanoma-pipeline/data/test
mkdir -p $OUT
# Subset tumor to chr17
# -b: output BAM format, -h: include header, -@ 8: 8 threads
samtools view \
-b \
-h \
-@ 8 \
$TUMOR_FULL \
chr17 \
-o $OUT/tumor_chr17.bam
# Index tumor subset
samtools index \
-@ 8 \
$OUT/tumor_chr17.bam \
$OUT/tumor_chr17.bai
# Subset normal to chr17
samtools view \
-b \
-h \
-@ 8 \
$NORMAL_FULL \
chr17 \
-o $OUT/normal_chr17.bam
# Index normal subset
samtools index \
-@ 8 \
$OUT/normal_chr17.bam \
$OUT/normal_chr17.bai
# Verify read counts
echo "Tumor chr17 reads:"
samtools flagstat $OUT/tumor_chr17.bam
echo "Normal chr17 reads:"
samtools flagstat $OUT/normal_chr17.bam
# ── Extract HLA reads from normal BAM for OptiType ───────────────────────────
# Always use normal BAM for HLA typing — tumor DNA can have LOH
# (Loss of Heterozygosity) at HLA loci which gives wrong alleles.
#
# Three-bucket strategy to avoid missing HLA reads due to ALT contigs:
# Bucket 1 — primary MHC region on chr6
# Bucket 2 — ALT contigs (reads that overflowed from primary chr6 assembly)
# Bucket 3 — unmapped reads (too divergent to map anywhere in hg38)
# All three are merged and remapped against OptiType's HLA-specific reference.
# ─────────────────────────────────────────────────────────────────────────────
OUT_HLA=~/melanoma-pipeline/data/hla
mkdir -p $OUT_HLA
# Bucket 1 — primary MHC region on chr6
# 28510120-33480577 = full MHC locus including HLA-A, B, C and flanking genes
samtools view \
-b \
-h \
-@ 8 \
$NORMAL_FULL \
chr6:28510120-33480577 \
-o $OUT_HLA/hla_chr6_primary.bam
# Bucket 2 — ALT contigs
# Reads from patients with HLA alleles too divergent for the primary reference
# — most common in non-European populations. Dynamically finds all ALT/HLA
# contigs in the BAM header so this works regardless of hg38 build variant.
ALT_CONTIGS=$(samtools view -H $NORMAL_FULL \
| grep "^@SQ" \
| grep -iE "_alt|HLA" \
| awk '{print $2}' \
| sed 's/SN://')
if [ -n "$ALT_CONTIGS" ]; then
ALT_TMP=$(mktemp -d)
while IFS= read -r contig; do
safe_name="${contig//\//_}"
samtools view -b -h -@ 8 $NORMAL_FULL "$contig" -o "$ALT_TMP/${safe_name}.bam"
done <<< "$ALT_CONTIGS"
samtools merge -f -@ 8 $OUT_HLA/hla_alt_contigs.bam "$ALT_TMP"/*.bam
rm -rf "$ALT_TMP"
else
# No ALT contigs — create an empty BAM so downstream merge still works
samtools view -b -h $NORMAL_FULL -o $OUT_HLA/hla_alt_contigs.bam /dev/null 2>/dev/null || \
samtools view -H $NORMAL_FULL -b -o $OUT_HLA/hla_alt_contigs.bam
fi
# Bucket 3 — unmapped reads
# Small fraction of BAM but catches rare/unusual alleles that couldn't
# map anywhere in hg38 due to extreme divergence from the reference
# -f 4: flag 4 = read unmapped
samtools view \
-b \
-f 4 \
-@ 8 \
$NORMAL_FULL \
-o $OUT_HLA/hla_unmapped.bam
# Merge all three buckets into one candidate pool
samtools merge \
-f \
-@ 8 \
$OUT_HLA/hla_candidates.bam \
$OUT_HLA/hla_chr6_primary.bam \
$OUT_HLA/hla_alt_contigs.bam \
$OUT_HLA/hla_unmapped.bam
# Convert merged BAM to paired FASTQ for remapping
# Sort by name first (-n) so read pairs are adjacent
samtools sort -n -@ 8 $OUT_HLA/hla_candidates.bam \
| samtools fastq \
-1 $OUT_HLA/hla_candidates_R1.fastq \
-2 $OUT_HLA/hla_candidates_R2.fastq \
-0 /dev/null \
-s /dev/null
# Remap against OptiType's HLA-specific reference
# This is the critical step — reads that were on ALT contigs or unmapped
# now find their correct HLA allele sequence. The HLA reference contains
# sequences for thousands of known alleles across all populations.
# hla_reference_dna.fasta is bundled inside the fred2/optitype Docker image
# at /usr/local/bin/data/hla_reference_dna.fasta
# Extract it once and reuse:
# docker run --rm fred2/optitype cat /usr/local/bin/data/hla_reference_dna.fasta \
# > ~/melanoma-pipeline/reference/hla_reference_dna.fasta
HLA_REF=~/melanoma-pipeline/reference/hla_reference_dna.fasta
# Index HLA reference if not already done
if [ ! -f "${HLA_REF}.bwt" ]; then
echo "Indexing HLA reference..."
bwa index $HLA_REF
fi
bwa mem \
-t 8 \
$HLA_REF \
$OUT_HLA/hla_candidates_R1.fastq \
$OUT_HLA/hla_candidates_R2.fastq \
| samtools sort -n -@ 8 \
| samtools fastq \
-F 4 \
-1 $OUT_HLA/hla_fished_R1.fastq \
-2 $OUT_HLA/hla_fished_R2.fastq \
-0 /dev/null \
-s /dev/null
# hla_fished_R1/R2.fastq are now ready to pass to OptiType (Step 3 of the pipeline)
echo "HLA read extraction complete."
echo "Fished read pairs: $(( $(wc -l < $OUT_HLA/hla_fished_R1.fastq) / 4 ))"
echo "Ready for OptiType: $OUT_HLA/hla_fished_R1.fastq + hla_fished_R2.fastq" |