airpg 1.0.5

A package to automatically access the inverted repeats of archived plastid genomes

airpg: Automatically accessing the inverted repeats of archived plastid genomes

A Python package for automatically accessing the inverted repeats of thousands of plastid genomes stored on NCBI Nucleotide

INSTALLATION

To get the most recent stable version of airpg, run:

pip install airpg

Or, alternatively, if you want to get the latest development version of airpg, run:

pip install git+https://github.com/michaelgruenstaeudl/airpg.git

EXAMPLE USAGE

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EXAMPLE 1: Very short survey (runtime ca. 5 min.; for the impatient)

Survey of all plastid genomes of flowering plants submitted to NCBI Nucleotide within the past 10 days.

TODAY=$(date +%d)
if (($TODAY >= 6 && $TODAY <= 10)); then
    STARTDATE=$(date +%Y/%m/01)
elif (($TODAY >= 11 && $TODAY <= 15)); then
    STARTDATE=$(date +%Y/%m/05)
elif (($TODAY >= 16 && $TODAY <= 20)); then
    STARTDATE=$(date +%Y/%m/10)
elif (($TODAY >= 21 && $TODAY <= 25)); then
    STARTDATE=$(date +%Y/%m/15)
else
    PREVMONTH=$(printf "%02d" $(($(date +%m)-1)))
    STARTDATE=$(date +%Y/$PREVMONTH/20)
fi
ENDDATE=$(date +%Y/%m/%d)

airpg_identify.py \
-q "complete genome[TITLE] AND \
(chloroplast[TITLE] OR plastid[TITLE]) AND \
$STARTDATE:$ENDDATE[PDAT] AND \
50000:250000[SLEN] NOT unverified[TITLE] \
NOT partial[TITLE] AND Magnoliophyta[ORGN]" \
-o output_script1.tsv \
#&> output_script1.log

mkdir -p records
mkdir -p data

airpg_analyze.py \
-i output_script1.tsv \
-m [e-mail] \
-o output_script2.tsv \
--recordsdir records/ \
--datadir data/ \
#&> output_script2.log

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EXAMPLE 2: Short survey (runtime ca. 15 min.; for testing)

Survey of all plastid genomes of flowering plants submitted to NCBI Nucleotide within the current month.

airpg_identify.py -q "complete genome[TITLE] AND \
(chloroplast[TITLE] OR plastid[TITLE]) AND \
$(date +%Y/%m/01):$(date +%Y/%m/%d)[PDAT] AND \
50000:250000[SLEN] NOT unverified[TITLE] \
NOT partial[TITLE] AND Magnoliophyta[ORGN]" \
-o output_script1.tsv # &> output_script1.log

airpg_analyze.py -i output_script1.tsv \
-m [e-mail] -o output_script2.tsv \
# &> output_script2.log

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EXAMPLE 3: Medium survey (runtime ca. 5 hours)

Survey of all plastid genomes of flowering plants submitted to NCBI Nucleotide in 2019 only. Note: The results of this survey are available on Zenodo via DOI 10.5281/zenodo.4335906

airpg_update_blocklist.py -f airpg_blocklist.txt \
-m [e-mail] -q "inverted[TITLE] AND \
repeat[TITLE] AND loss[TITLE]"

airpg_identify.py -q "complete genome[TITLE] AND \
(chloroplast[TITLE] OR plastid[TITLE]) AND \
2019/01/01:2019/12/31[PDAT] AND 50000:250000[SLEN] \
NOT unverified[TITLE] NOT partial[TITLE] AND \
Magnoliophyta[ORGN]" \
-b airpg_blocklist.txt -o output_script1.tsv

airpg_analyze.py -i output_script1.tsv \
-m [e-mail] -o output_script2.tsv

---

EXAMPLE 4: Full survey (runtime ca. 19 hours; with explanations)

Survey of all plastid genomes of flowering plants submitted to NCBI Nucleotide from start of 2000 until end of October 2020. Note: The results of this survey are available on Zenodo via DOI 10.5281/zenodo.4335906

STEP 1: Querying NCBI Nucleotide for complete plastid genomes given an Entrez search string

TESTFOLDER=./angiosperms_Start2000toEndOct2020
DATE=$(date '+%Y_%m_%d')
ENTREZSTRING='complete genome[TITLE] AND (chloroplast[TITLE] OR plastid[TITLE]) AND 2000/01/01:2020/10/31[PDAT] AND 50000:250000[SLEN] NOT unverified[TITLE] NOT partial[TITLE] AND Magnoliophyta[ORGN]' # complete plastid genomes of all flowering plants between start of 2000 and end of October 2020
RECORDSTABLE=plastome_availability_table_${DATE}.tsv
mkdir -p $TESTFOLDER

# Updating blocklist
if [ ! -f ./airpg_blocklist.txt ]; then
    touch ./airpg_blocklist.txt
    airpg_update_blocklist.py -f ./airpg_blocklist.txt
fi
airpg_update_blocklist.py -f ./airpg_blocklist.txt -m [e-mail] -q "inverted[TITLE] AND repeat[TITLE] AND loss[TITLE]"

airpg_identify.py -q "$ENTREZSTRING" -o $TESTFOLDER/$RECORDSTABLE \
    --blocklist ./airpg_blocklist.txt 1>>$TESTFOLDER/airpg_identify_${DATE}.runlog 2>&1

STEP 2: Retrieving and parsing the genome records identified in step 1, analyzing the position and length of their IR annotations

IRSTATSTABLE=reported_IR_stats_table_${DATE}.tsv
mkdir -p $TESTFOLDER/records_${DATE}
mkdir -p $TESTFOLDER/data_${DATE}

airpg_analyze.py -i $TESTFOLDER/$RECORDSTABLE \
    -r $TESTFOLDER/records_${DATE}/ -d $TESTFOLDER/data_${DATE}/ \
    -m [e-mail] -o $TESTFOLDER/$IRSTATSTABLE 1>>$TESTFOLDER/airpg_analyze_${DATE}.runlog 2>&1

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CHANGELOG

See CHANGELOG.md for a list of recent changes to the software.